The robotic airship can provide a promising aerostatic platform for many potential applications.These applications require a precise autonomous trajectory tracking control for airship.Airship has a nonlinear and uncer...The robotic airship can provide a promising aerostatic platform for many potential applications.These applications require a precise autonomous trajectory tracking control for airship.Airship has a nonlinear and uncertain dynamics.It is prone to wind disturbances that offer a challenge for a trajectory tracking control design.This paper addresses the airship trajectory tracking problem having time varying reference path.A lumped parameter estimation approach under model uncertainties and wind disturbances is opted against distributed parameters.It uses extended Kalman filter(EKF)for uncertainty and disturbance estimation.The estimated parameters are used by sliding mode controller(SMC)for ultimate control of airship trajectory tracking.This comprehensive algorithm,EKF based SMC(ESMC),is used as a robust solution to track airship trajectory.The proposed estimator provides the estimates of wind disturbances as well as model uncertainty due to the mass matrix variations and aerodynamic model inaccuracies.The stability and convergence of the proposed method are investigated using the Lyapunov stability analysis.The simulation results show that the proposed method efficiently tracks the desired trajectory.The method solves the stability,convergence,and chattering problem of SMC under model uncertainties and wind disturbances.展开更多
Hydraulic actuators are highly nonlinear when they are subjected to different types of model uncertainties and dynamic disturbances.These unfavorable factors adversely affect the control performance of the hydraulic a...Hydraulic actuators are highly nonlinear when they are subjected to different types of model uncertainties and dynamic disturbances.These unfavorable factors adversely affect the control performance of the hydraulic actuator.Although various control methods have been employed to improve the tracking precision of the dynamic system,optimizing and adjusting control gain to mitigate the hydraulic actuator model uncertainties remains elusive.This study presents an adaptive back-stepping sliding mode controller(ABSMC)to enhance the trajectory tracking precision,where the virtual control law is constructed to replace the position error.The adaptive control theory is introduced in back-stepping controller design to compensate for the model uncertainties and time-varying disturbances.Based on Lyapunov theory,the finite-time convergence of the position tracking errors is proved.Furthermore,the effectiveness of the developed control scheme is conducted via extensive comparative experiments.展开更多
Cognitive Reliability and Error Analysis Method(CREAM)is widely used in human reliability analysis(HRA).It defines nine common performance conditions(CPCs),which represent the factors thatmay affect human reliability ...Cognitive Reliability and Error Analysis Method(CREAM)is widely used in human reliability analysis(HRA).It defines nine common performance conditions(CPCs),which represent the factors thatmay affect human reliability and are used to modify the cognitive failure probability(CFP).However,the levels of CPCs are usually determined by domain experts,whichmay be subjective and uncertain.What’smore,the classicCREAMassumes that the CPCs are independent,which is unrealistic.Ignoring the dependence among CPCs will result in repeated calculations of the influence of the CPCs on CFP and lead to unreasonable reliability evaluation.To address the issue of uncertain information modeling and processing,this paper introduces evidence theory to evaluate the CPC levels in specific scenarios.To address the issue of dependence modeling,the Decision-Making Trial and Evaluation Laboratory(DEMATEL)method is used to process the dependence among CPCs and calculate the relative weights of each CPC,thus modifying the multiplier of the CPCs.The detailed process of the proposed method is illustrated in this paper and the CFP estimated by the proposed method is more reasonable.展开更多
The quality of the micro-mechanical machining outcome depends significantly on the tracking performance of the miniaturized linear motor drive precision stage. The tracking behavior of a direct drive design is prone t...The quality of the micro-mechanical machining outcome depends significantly on the tracking performance of the miniaturized linear motor drive precision stage. The tracking behavior of a direct drive design is prone to uncertainties such as model parameter variations and disturbances. Robust optimal tracking controller design for this kind of precision stages with mass and damping ratio uncertainties was researched. The mass and damping ratio uncertainties were modeled as the structured parametric uncertainty model. An identification method for obtaining the parametric uncertainties was developed by using unbiased least square technique. The instantaneous frequency bandwidth of the external disturbance signals was analyzed by using short time Fourier transform technique. A two loop tracking control strategy that combines the p-synthesis and the disturbance observer （DOB） techniques was proposed. The p-synthesis technique was used to design robust optimal controllers based on structured uncertainty models. By complementing the/z controller, the DOB was applied to further improving the disturbance rejection performance. To evaluate the positioning performance of the proposed control strategy, the comparative experiments were conducted on a prototype micro milling machine among four control schemes： the proposed two-loop tracking control, the single loop μ control, the PID control and the PID with DOB control. The disturbance rejection performances, the root mean square （RMS） tracking errors and the performance robustness of different control schemes were studied. The results reveal that the proposed control scheme has the best positioning performance. It reduces the maximal errors caused by disturbance forces such as friction force by 60% and the RMS errors by 63.4% compared with the PID control. Compared to PID with DOB control, it reduces the RMS errors by 29.6%.展开更多
This research develops a comprehensive method to solve a combinatorial problem consisting of distribution system reconfiguration, capacitor allocation, and renewable energy resources sizing and siting simultaneously a...This research develops a comprehensive method to solve a combinatorial problem consisting of distribution system reconfiguration, capacitor allocation, and renewable energy resources sizing and siting simultaneously and to improve power system's accountability and system performance parameters. Due to finding solution which is closer to realistic characteristics, load forecasting, market price errors and the uncertainties related to the variable output power of wind based DG units are put in consideration. This work employs NSGA-II accompanied by the fuzzy set theory to solve the aforementioned multi-objective problem. The proposed scheme finally leads to a solution with a minimum voltage deviation, a maximum voltage stability, lower amount of pollutant and lower cost. The cost includes the installation costs of new equipment, reconfiguration costs, power loss cost, reliability cost, cost of energy purchased from power market, upgrade costs of lines and operation and maintenance costs of DGs. Therefore, the proposed methodology improves power quality, reliability and security in lower costs besides its preserve, with the operational indices of power distribution networks in acceptable level. To validate the proposed methodology's usefulness, it was applied on the IEEE 33-bus distribution system then the outcomes were compared with initial configuration.展开更多
Decision making to mitigate the effects of natural hazards is a complex undertaking fraught with uncertainty. Models to describe risks associated with natural hazards have proliferated in recent years. Concurrently, t...Decision making to mitigate the effects of natural hazards is a complex undertaking fraught with uncertainty. Models to describe risks associated with natural hazards have proliferated in recent years. Concurrently, there is a growing body of work focused on developing best practices for natural hazard modeling and to create structured evaluation criteria for complex environmental models. However, to our knowledge there has been less focus on the conditions where decision makers can confidently rely on results from these models. In this review we propose a preliminary set of conditions necessary for the appropriate application of modeled results to natural hazard decision making and provide relevant examples within US wildfire management programs.展开更多
Hydraulic servo system plays an important role in industrial fields due to the advantages of high response,small size-to-power ratio and large driving force.However,inherent nonlinear behaviors and modeling uncertaint...Hydraulic servo system plays an important role in industrial fields due to the advantages of high response,small size-to-power ratio and large driving force.However,inherent nonlinear behaviors and modeling uncertainties are the main obstacles for hydraulic servo system to achieve high tracking perfor-mance.To deal with these difficulties,this paper presents a backstepping sliding mode controller to improve the dynamic tracking performance and anti-interfer-ence ability.For this purpose,the nonlinear dynamic model is firstly established,where the nonlinear behaviors and modeling uncertainties are lumped as one term.Then,the extended state observer is introduced to estimate the lumped distur-bance.The system stability is proved by using the Lyapunov stability theorem.Finally,comparative simulation and experimental are conducted on a hydraulic servo system platform to verify the efficiency of the proposed control scheme.展开更多
The calculation results of marine environmental design parameters obtained from different data sampling methods,model distributions,and parameter estimation methods often vary greatly.To better analyze the uncertainti...The calculation results of marine environmental design parameters obtained from different data sampling methods,model distributions,and parameter estimation methods often vary greatly.To better analyze the uncertainties in the calculation of marine environmental design parameters,a general model uncertainty assessment method is necessary.We proposed a new multivariate model uncertainty assessment method for the calculation of marine environmental design parameters.The method divides the overall model uncertainty into two categories:aleatory uncertainty and epistemic uncertainty.The aleatory uncertainty of the model is obtained by analyzing the influence of the number and the dispersion degree of samples on the information entropy of the model.The epistemic uncertainty of the model is calculated using the information entropy of the model itself and the prediction error.The advantages of this method are that it does not require many-year-observation data for the marine environmental elements,and the method can be used to analyze any specific factors that cause model uncertainty.Results show that by applying the method to the South China Sea,the aleatory uncertainty of the model increases with the number of samples and then stabilizes.A positive correlation was revealed between the dispersion of the samples and the aleatory uncertainty of the model.Both the distribution of the model and the parameter estimation results of the model have significant effects on the epistemic uncertainty of the model.When the goodness-of-fit of the model is relatively close,the best model can be selected according to the criterion of the lowest overall uncertainty of the models,which can both ensure a better model fit and avoid too much uncertainty in the model calculation results.The presented multivariate model uncertainty assessment method provides a criterion to measure the advantages and disadvantages of the marine environmental design parameter calculation model from the aspect of uncertainty,which is of great significance to analyze the uncertainties in the calculation of marine environmental design parameters and improve the accuracy of the calculation results.展开更多
Recently,research on uncertainty modeling has been progressing rapidly,and many essential and breakthrough studies have already been done.There are various ways to handle these uncertainties,such as fuzzy and intuitio...Recently,research on uncertainty modeling has been progressing rapidly,and many essential and breakthrough studies have already been done.There are various ways to handle these uncertainties,such as fuzzy and intuitionistic fuzzy sets.Although these concepts can take incomplete information in various real-world issues,they cannot address all types of uncertainty,such as indeterminate and inconsistent information.The neutrosophic theory founded by Florentin Smarandache in 1998 constitutes a further generalization of fuzzy set,intuitionistic fuzzy set,picture fuzzy set,Pythagorean fuzzy set,spherical fuzzy set,etc.Since then,this logic has been applied in various science and engineering domains.展开更多
A larger number of uncertain factors in energy systems influence their evolution.Owing to the complexity of energy system modeling,incorporating uncertainty analysis to energy system modeling is essential for future e...A larger number of uncertain factors in energy systems influence their evolution.Owing to the complexity of energy system modeling,incorporating uncertainty analysis to energy system modeling is essential for future energy system planning and resource allocation.This study focusses on long-term energy system optimization model.The important uncertain parameters in the model are analyzed and divided into policy,economic,and technical factors.This study specifically addresses the challenges related to carbon emission reduction and energy transition.It involves collecting and organizing relevant research on uncertainty analysis of long-term energy systems.Various energy system uncertainty modeling methods and their applications from the literature are summarized in this review.Finally,important uncertainty factors and uncertainty modeling methods for long-term energy system modeling are discussed,and future research directions are proposed.展开更多
In this paper,a novel robust composite sliding mode controller(RCSMC)is proposed to accommodate actuator faults for a quadrotor UAV subject to unknown disturbances.The closed-loop system is divided into two parts:the ...In this paper,a novel robust composite sliding mode controller(RCSMC)is proposed to accommodate actuator faults for a quadrotor UAV subject to unknown disturbances.The closed-loop system is divided into two parts:the nominal system without disturbances which is controlled by the designed baseline controller,and the equivalent total disturbances including parameter uncertainties and actuator faults,which is estimated by the developed adaptive finite-time extended state observer(AFTESO).The estimated total disturbances are rejected by RCSMC and the asymptotic stability of flight control system is guaranteed.The proposed method is verified through numerical simulations.展开更多
Dynamic operating envelopes(DOEs),as key enablers to facilitate distributed energy resource(DER)integration,have attracted increasing attention in the past years.However,uncertainties,which may come from load forecast...Dynamic operating envelopes(DOEs),as key enablers to facilitate distributed energy resource(DER)integration,have attracted increasing attention in the past years.However,uncertainties,which may come from load forecasting errors or inaccurate network parameters,have been rarely discussed in DOE calculation,leading to compromised quality of the hosting capacity allocation strategy.This letter studies how to calculate DOEs that are immune to such uncertainties based on a linearised unbalanced three-phase optimal power flow(UTOPF)model.With uncertain parameters constrained by norm balls,formulations for calculating robust DOEs(RDOEs)are presented along with discussions on their tractability.Two cases,including a 2-bus illustrative network and a representative Australian network,are tested to demonstrate the effectiveness and efficiency of the proposed approach.展开更多
Internal model control （IMC） yields very good performance for set point tracking, but gives sluggish response for disturbance rejection problem. A two-degree-of-freedom IMC （2DOF-IMC） has been developed to overcom...Internal model control （IMC） yields very good performance for set point tracking, but gives sluggish response for disturbance rejection problem. A two-degree-of-freedom IMC （2DOF-IMC） has been developed to overcome the weakness. However, the setting of parameter becomes a complicated matter if there is an uncertainty model. The present study proposes a new tuning method for the controller. The proposed tuning method consists of three steps. Firstly, the worst case of the model uncertainty is determined. Secondly, the parameter of set point con- troller using maximum peak （Mp） criteria is specified, and finally, the parameter of the disturbance rejection con- troller using gain margin （GM） criteria is obtained. The proposed method is denoted as Mp-GM tuning method. The effectiveness of Mp-GM tuning method has evaluated and compared with IMC-controller tuning program （IMCTUNE） as bench mark. The evaluation and comparison have been done through the simulation on a number of first order plus dead time （FOPDT） and higher order processes. The FOPDT process tested includes processes with controllability ratio in the range 0.7 to 2.5. The higher processes include second order with underdarnped and third order with nonminimum phase processes. Although the two of higher order processes are considered as difficult processes, the proposed Mp-GM tuning method are able to obtain the good controller parameter even under process uncertainties.展开更多
This paper develops a robust control methodology for a class of morphing aircraft,which is called innovative control effector（ICE） aircraft.For the ICE morphing aircraft,the distributed arrays of hundreds of shape-c...This paper develops a robust control methodology for a class of morphing aircraft,which is called innovative control effector（ICE） aircraft.For the ICE morphing aircraft,the distributed arrays of hundreds of shape-change devices are employed to stabilize and maneuver the air vehicle.Because the morphing aircraft have the inherent uncertainty and varying dynamics due to the alteration of their configuration,a desired control performance can not be satisfied with a fixed feedback controller.Therefore,a novel control framework including an adaptive flight control law and an adaptive allocation algorithm is proposed.Firstly,a state feedback adaptive control law is designed to guarantee closed-loop stability and state tracking in the presence of uncertain dynamics caused by the wing shape change due to different flight missions.In the control allocation,many distributed arrays are managed in an optimal way to improve the robustness of the system.The scheme is used to an uncertain morphing aircraft model,and the simulation results demonstrate their performance.展开更多
El Nino-Southern Oscillation(ENSO) is the strongest interannual signal that is producedby basinscale processes in the tropical Pacific,with significant effects on weather and climate worldwide.In the past,extensive an...El Nino-Southern Oscillation(ENSO) is the strongest interannual signal that is producedby basinscale processes in the tropical Pacific,with significant effects on weather and climate worldwide.In the past,extensive and intensive international efforts have been devoted to coupled model developments for ENSO studies.A hierarchy of coupled ocean-atmo sphere models has been formulated;in terms of their complexity,they can be categorized into intermediate coupled models(ICMs),hybrid coupled models(HCMs),and fully coupled general circulation models(CGCMs).ENSO modeling has made significant progress over the past decades,reaching a stage where coupled models can now be used to successfully predict ENSO events 6 months to one year in advance.Meanwhile,ENSO exhibits great diversity and complexity as observed in nature,which still cannot be adequately captured by current state-of-the-art coupled models,presenting a challenge to ENSO modeling.We primarily reviewed the long-term efforts in ENSO modeling continually and steadily made at different institutions in China;some selected representative examples are presented here to review the current status of ENSO model developments and applications,which have been actively pursued with noticeable progress being made recently.As ENSO simulations are very sensitive to model formulations and process representations etc.,dedicated efforts have been devoted to ENSO model developments and improvements.Now,different ocean-atmosphere coupled models have been available in China,which exhibit good model performances and have already had a variety of applications to climate modeling,including the Coupled Model Intercomparison Project Phase 6(CMIP6).Nevertheless,large biases and uncertainties still exist in ENSO simulations and predictions,and there are clear rooms for their improvements,which are still an active area of researches and applications.Here,model performances of ENSO simulations are assessed in terms of advantages and disadvantages with these differently formulated coupled models,pinpointing to the areas where they need to be further improved for ENSO studies.These analyses provide valuable guidance for future improvements in ENSO simulations and predictions.展开更多
Joint parameter identification is a key problem in the modeling of complex structures. The behavior of joint may be random due to the random properties of preload and joint geometries, contact surface and its finish, ...Joint parameter identification is a key problem in the modeling of complex structures. The behavior of joint may be random due to the random properties of preload and joint geometries, contact surface and its finish, etc. A method is presented to simulate the joint parameters as probabilistic variables. In this method the response surface based model updating method and probabilistic approaches are employed to identify the parameters. The study implies that joint parameters of some structures have normal or nearly normal distributions, and a linear FE model with probabilistic variables could illustrate dynamic characteristics of joints.展开更多
Different performance levels may be obtained for sideway collapse evaluation of steel moment frames depending on the evaluation procedure used to handle uncertainties. In this article, the process of representing mode...Different performance levels may be obtained for sideway collapse evaluation of steel moment frames depending on the evaluation procedure used to handle uncertainties. In this article, the process of representing modelling uncertainties, record to record （RTR） variations and cognitive uncertainties for moment resisting steel frames of various heights is discussed in detail. RTR uncertainty is used by incremental dynamic analysis （IDA）, modelling uncertainties are considered through backbone curves and hysteresis loops of component, and cognitive uncertainty is presented in three levels of material quality. IDA is used to evaluate RTR uncertainty based on strong ground motion records selected by the k-means algorithm, which is favoured over Monte Carlo selection due to its time saving appeal. Analytical equations of the Response Surface Method are obtained through IDA results by the Cuckoo algorithm, which predicts the mean and standard deviation of the collapse fragility curve. The Takagi-Sugeno-Kang model is used to represent material quality based on the response surface coefficients. Finally, collapse fragility curves with the various sources of uncertainties mentioned are derived through a large number of material quality values and meta variables inferred by the Takagi-Sugeno-Kang fuzzy model based on response surface method coefficients. It is concluded that a better risk management strategy in countries where material quality control is weak, is to account for cognitive uncertainties in fragility curves and the mean annual frequency.展开更多
The robust attitude control for a novel coaxial twelve-rotor UAV which has much greater payload capacity,higher drive capability and damage tolerance than a quad-rotor UAV is studied. Firstly,a dynamical and kinematic...The robust attitude control for a novel coaxial twelve-rotor UAV which has much greater payload capacity,higher drive capability and damage tolerance than a quad-rotor UAV is studied. Firstly,a dynamical and kinematical model for the coaxial twelve-rotor UAV is designed. Considering model uncertainties and external disturbances,a robust backstepping sliding mode control( BSMC) with self recurrent wavelet neural network( SRWNN) method is proposed as the attitude controller for the coaxial twelve-rotor. A combinative algorithm of backstepping control and sliding mode control has simplified design procedures with much stronger robustness benefiting from advantages of both controllers. SRWNN as the uncertainty observer is able to estimate the lumped uncertainties effectively.Then the uniformly ultimate stability of the twelve-rotor system is proved by Lyapunov stability theorem. Finally,the validity of the proposed robust control method adopted in the twelve-rotor UAV under model uncertainties and external disturbances are demonstrated via numerical simulations and twelve-rotor prototype experiments.展开更多
Uncertainty on the geological contacts and the block volumes of the models along boundaries is often a major part of the global uncertainty of reserve estimation.This work introduces a geostatistical technique that ha...Uncertainty on the geological contacts and the block volumes of the models along boundaries is often a major part of the global uncertainty of reserve estimation.This work introduces a geostatistical technique that has been developed and tested in an iron ore deposit at Bafq mining district,in central Iran,and that,based on a probability criterion,helps to objectively model the geometry of this iron ore deposit.The main problem in reserve estimation of this ore body is its geometrical modeling and uncertainty in geological boundaries.This work deals with the geostatistical method of multiple indicator kriging,which is used to determine the real boundaries of ore body in different categories.This approach has potential to improve project performance and decrease operational risk.For this purpose,the ore body is separated into two categories including rich iron zone(w(Fe)>45%)and poor iron zone(20%<w(Fe)<45%).It significantly benefits to decrease the risk of reserve evaluation in the deposit.This case study also highlights the value of multiple indicator kriging as a tool for estimates the position of grade boundaries within the deposit.Comparison of the resultant probability maps with the real ore/waste contacts on the extracted levels shows that the first indicator model could separate the whole ore body(poor plus rich)from the waste zone by probability of more than 0.35,which concludes the total reserve of 53 million tons.The second indicator model applied to separate the rich and poor domains and the results show that the blocks with the estimated probability of equal to or more than 0.4 lay within the rich ore zone consisting of 15.8 million tons reserve.展开更多
文摘The robotic airship can provide a promising aerostatic platform for many potential applications.These applications require a precise autonomous trajectory tracking control for airship.Airship has a nonlinear and uncertain dynamics.It is prone to wind disturbances that offer a challenge for a trajectory tracking control design.This paper addresses the airship trajectory tracking problem having time varying reference path.A lumped parameter estimation approach under model uncertainties and wind disturbances is opted against distributed parameters.It uses extended Kalman filter(EKF)for uncertainty and disturbance estimation.The estimated parameters are used by sliding mode controller(SMC)for ultimate control of airship trajectory tracking.This comprehensive algorithm,EKF based SMC(ESMC),is used as a robust solution to track airship trajectory.The proposed estimator provides the estimates of wind disturbances as well as model uncertainty due to the mass matrix variations and aerodynamic model inaccuracies.The stability and convergence of the proposed method are investigated using the Lyapunov stability analysis.The simulation results show that the proposed method efficiently tracks the desired trajectory.The method solves the stability,convergence,and chattering problem of SMC under model uncertainties and wind disturbances.
基金supported by the fund of Henan Key Laboratory of Superhard Abrasives and Grinding Equipment,Henan University of Technology(Grant No.JDKFJJ2023005)the Key Science and Technology Program of Henan Province(Grant Nos.242102221001 and 232102220085)the Science and Technology Key Project Foundation of Henan Provincial Education Department(Grant No.23A460014).
文摘Hydraulic actuators are highly nonlinear when they are subjected to different types of model uncertainties and dynamic disturbances.These unfavorable factors adversely affect the control performance of the hydraulic actuator.Although various control methods have been employed to improve the tracking precision of the dynamic system,optimizing and adjusting control gain to mitigate the hydraulic actuator model uncertainties remains elusive.This study presents an adaptive back-stepping sliding mode controller(ABSMC)to enhance the trajectory tracking precision,where the virtual control law is constructed to replace the position error.The adaptive control theory is introduced in back-stepping controller design to compensate for the model uncertainties and time-varying disturbances.Based on Lyapunov theory,the finite-time convergence of the position tracking errors is proved.Furthermore,the effectiveness of the developed control scheme is conducted via extensive comparative experiments.
基金Shanghai Rising-Star Program(Grant No.21QA1403400)Shanghai Sailing Program(Grant No.20YF1414800)Shanghai Key Laboratory of Power Station Automation Technology(Grant No.13DZ2273800).
文摘Cognitive Reliability and Error Analysis Method(CREAM)is widely used in human reliability analysis(HRA).It defines nine common performance conditions(CPCs),which represent the factors thatmay affect human reliability and are used to modify the cognitive failure probability(CFP).However,the levels of CPCs are usually determined by domain experts,whichmay be subjective and uncertain.What’smore,the classicCREAMassumes that the CPCs are independent,which is unrealistic.Ignoring the dependence among CPCs will result in repeated calculations of the influence of the CPCs on CFP and lead to unreasonable reliability evaluation.To address the issue of uncertain information modeling and processing,this paper introduces evidence theory to evaluate the CPC levels in specific scenarios.To address the issue of dependence modeling,the Decision-Making Trial and Evaluation Laboratory(DEMATEL)method is used to process the dependence among CPCs and calculate the relative weights of each CPC,thus modifying the multiplier of the CPCs.The detailed process of the proposed method is illustrated in this paper and the CFP estimated by the proposed method is more reasonable.
基金Project(50875257) supported by the National Natural Science Foundation of China
文摘The quality of the micro-mechanical machining outcome depends significantly on the tracking performance of the miniaturized linear motor drive precision stage. The tracking behavior of a direct drive design is prone to uncertainties such as model parameter variations and disturbances. Robust optimal tracking controller design for this kind of precision stages with mass and damping ratio uncertainties was researched. The mass and damping ratio uncertainties were modeled as the structured parametric uncertainty model. An identification method for obtaining the parametric uncertainties was developed by using unbiased least square technique. The instantaneous frequency bandwidth of the external disturbance signals was analyzed by using short time Fourier transform technique. A two loop tracking control strategy that combines the p-synthesis and the disturbance observer （DOB） techniques was proposed. The p-synthesis technique was used to design robust optimal controllers based on structured uncertainty models. By complementing the/z controller, the DOB was applied to further improving the disturbance rejection performance. To evaluate the positioning performance of the proposed control strategy, the comparative experiments were conducted on a prototype micro milling machine among four control schemes： the proposed two-loop tracking control, the single loop μ control, the PID control and the PID with DOB control. The disturbance rejection performances, the root mean square （RMS） tracking errors and the performance robustness of different control schemes were studied. The results reveal that the proposed control scheme has the best positioning performance. It reduces the maximal errors caused by disturbance forces such as friction force by 60% and the RMS errors by 63.4% compared with the PID control. Compared to PID with DOB control, it reduces the RMS errors by 29.6%.
文摘This research develops a comprehensive method to solve a combinatorial problem consisting of distribution system reconfiguration, capacitor allocation, and renewable energy resources sizing and siting simultaneously and to improve power system's accountability and system performance parameters. Due to finding solution which is closer to realistic characteristics, load forecasting, market price errors and the uncertainties related to the variable output power of wind based DG units are put in consideration. This work employs NSGA-II accompanied by the fuzzy set theory to solve the aforementioned multi-objective problem. The proposed scheme finally leads to a solution with a minimum voltage deviation, a maximum voltage stability, lower amount of pollutant and lower cost. The cost includes the installation costs of new equipment, reconfiguration costs, power loss cost, reliability cost, cost of energy purchased from power market, upgrade costs of lines and operation and maintenance costs of DGs. Therefore, the proposed methodology improves power quality, reliability and security in lower costs besides its preserve, with the operational indices of power distribution networks in acceptable level. To validate the proposed methodology's usefulness, it was applied on the IEEE 33-bus distribution system then the outcomes were compared with initial configuration.
文摘Decision making to mitigate the effects of natural hazards is a complex undertaking fraught with uncertainty. Models to describe risks associated with natural hazards have proliferated in recent years. Concurrently, there is a growing body of work focused on developing best practices for natural hazard modeling and to create structured evaluation criteria for complex environmental models. However, to our knowledge there has been less focus on the conditions where decision makers can confidently rely on results from these models. In this review we propose a preliminary set of conditions necessary for the appropriate application of modeled results to natural hazard decision making and provide relevant examples within US wildfire management programs.
基金Thework issupportedby the Key Scienceand Technology Programof Henan Province(Grant No.222102220104)the Science and Technology Key Project Foundation of Henan Provincial Education Department(Grant No.23A460014)the High Level Talent Foundation of Henan University of Technology(Grant No.2020BS043).
文摘Hydraulic servo system plays an important role in industrial fields due to the advantages of high response,small size-to-power ratio and large driving force.However,inherent nonlinear behaviors and modeling uncertainties are the main obstacles for hydraulic servo system to achieve high tracking perfor-mance.To deal with these difficulties,this paper presents a backstepping sliding mode controller to improve the dynamic tracking performance and anti-interfer-ence ability.For this purpose,the nonlinear dynamic model is firstly established,where the nonlinear behaviors and modeling uncertainties are lumped as one term.Then,the extended state observer is introduced to estimate the lumped distur-bance.The system stability is proved by using the Lyapunov stability theorem.Finally,comparative simulation and experimental are conducted on a hydraulic servo system platform to verify the efficiency of the proposed control scheme.
基金support for this work provided by the Children’s Hospital of Fudan University:Big Data and Artificial Intelligence Project(2020DSJ07)the National Natural Science Foundation of China(U2001209,61902076,and 81670281)+1 种基金scientific research project of Shanghai Municipal Health Commission(20204Y0100)Natural Science Foundation of Shanghai(21ZR1406600).
基金Supported by the National Natural Science Foundation of China(No.52071306)the Natural Science Foundation of Shandong Province(No.ZR2019MEE050)。
文摘The calculation results of marine environmental design parameters obtained from different data sampling methods,model distributions,and parameter estimation methods often vary greatly.To better analyze the uncertainties in the calculation of marine environmental design parameters,a general model uncertainty assessment method is necessary.We proposed a new multivariate model uncertainty assessment method for the calculation of marine environmental design parameters.The method divides the overall model uncertainty into two categories:aleatory uncertainty and epistemic uncertainty.The aleatory uncertainty of the model is obtained by analyzing the influence of the number and the dispersion degree of samples on the information entropy of the model.The epistemic uncertainty of the model is calculated using the information entropy of the model itself and the prediction error.The advantages of this method are that it does not require many-year-observation data for the marine environmental elements,and the method can be used to analyze any specific factors that cause model uncertainty.Results show that by applying the method to the South China Sea,the aleatory uncertainty of the model increases with the number of samples and then stabilizes.A positive correlation was revealed between the dispersion of the samples and the aleatory uncertainty of the model.Both the distribution of the model and the parameter estimation results of the model have significant effects on the epistemic uncertainty of the model.When the goodness-of-fit of the model is relatively close,the best model can be selected according to the criterion of the lowest overall uncertainty of the models,which can both ensure a better model fit and avoid too much uncertainty in the model calculation results.The presented multivariate model uncertainty assessment method provides a criterion to measure the advantages and disadvantages of the marine environmental design parameter calculation model from the aspect of uncertainty,which is of great significance to analyze the uncertainties in the calculation of marine environmental design parameters and improve the accuracy of the calculation results.
文摘Recently,research on uncertainty modeling has been progressing rapidly,and many essential and breakthrough studies have already been done.There are various ways to handle these uncertainties,such as fuzzy and intuitionistic fuzzy sets.Although these concepts can take incomplete information in various real-world issues,they cannot address all types of uncertainty,such as indeterminate and inconsistent information.The neutrosophic theory founded by Florentin Smarandache in 1998 constitutes a further generalization of fuzzy set,intuitionistic fuzzy set,picture fuzzy set,Pythagorean fuzzy set,spherical fuzzy set,etc.Since then,this logic has been applied in various science and engineering domains.
基金supported by Global Energy Interconnection Group Co.,Ltd.:Assessment of China’s carbon neutrality implementation path and simulation research on policy tool combination(SGGEIG00JYJS2200059).
文摘A larger number of uncertain factors in energy systems influence their evolution.Owing to the complexity of energy system modeling,incorporating uncertainty analysis to energy system modeling is essential for future energy system planning and resource allocation.This study focusses on long-term energy system optimization model.The important uncertain parameters in the model are analyzed and divided into policy,economic,and technical factors.This study specifically addresses the challenges related to carbon emission reduction and energy transition.It involves collecting and organizing relevant research on uncertainty analysis of long-term energy systems.Various energy system uncertainty modeling methods and their applications from the literature are summarized in this review.Finally,important uncertainty factors and uncertainty modeling methods for long-term energy system modeling are discussed,and future research directions are proposed.
基金supported by the Innovation Fund of Key Laboratory of High-Altitude Simulating Technology,AECC Sichuan Turbine Research Institute(18zd9101).
文摘In this paper,a novel robust composite sliding mode controller(RCSMC)is proposed to accommodate actuator faults for a quadrotor UAV subject to unknown disturbances.The closed-loop system is divided into two parts:the nominal system without disturbances which is controlled by the designed baseline controller,and the equivalent total disturbances including parameter uncertainties and actuator faults,which is estimated by the developed adaptive finite-time extended state observer(AFTESO).The estimated total disturbances are rejected by RCSMC and the asymptotic stability of flight control system is guaranteed.The proposed method is verified through numerical simulations.
基金supported by the CSIRO Strategic Project on Network Optimisation&Decarbonisation(No.OD-107890).
文摘Dynamic operating envelopes(DOEs),as key enablers to facilitate distributed energy resource(DER)integration,have attracted increasing attention in the past years.However,uncertainties,which may come from load forecasting errors or inaccurate network parameters,have been rarely discussed in DOE calculation,leading to compromised quality of the hosting capacity allocation strategy.This letter studies how to calculate DOEs that are immune to such uncertainties based on a linearised unbalanced three-phase optimal power flow(UTOPF)model.With uncertain parameters constrained by norm balls,formulations for calculating robust DOEs(RDOEs)are presented along with discussions on their tractability.Two cases,including a 2-bus illustrative network and a representative Australian network,are tested to demonstrate the effectiveness and efficiency of the proposed approach.
基金Supported by Postgraduate Fellowship of UMP,Fundamental Research Grant Scheme of Malaysia(GRS070120)Joint Research Grant between Universiti Malaysia Pahang (UMP) and Institut Teknologi Sepuluh Nopember (ITS) Surabaya
文摘Internal model control （IMC） yields very good performance for set point tracking, but gives sluggish response for disturbance rejection problem. A two-degree-of-freedom IMC （2DOF-IMC） has been developed to overcome the weakness. However, the setting of parameter becomes a complicated matter if there is an uncertainty model. The present study proposes a new tuning method for the controller. The proposed tuning method consists of three steps. Firstly, the worst case of the model uncertainty is determined. Secondly, the parameter of set point con- troller using maximum peak （Mp） criteria is specified, and finally, the parameter of the disturbance rejection con- troller using gain margin （GM） criteria is obtained. The proposed method is denoted as Mp-GM tuning method. The effectiveness of Mp-GM tuning method has evaluated and compared with IMC-controller tuning program （IMCTUNE） as bench mark. The evaluation and comparison have been done through the simulation on a number of first order plus dead time （FOPDT） and higher order processes. The FOPDT process tested includes processes with controllability ratio in the range 0.7 to 2.5. The higher processes include second order with underdarnped and third order with nonminimum phase processes. Although the two of higher order processes are considered as difficult processes, the proposed Mp-GM tuning method are able to obtain the good controller parameter even under process uncertainties.
基金supported by the National Natural Science Foundation of China(61074063)
文摘This paper develops a robust control methodology for a class of morphing aircraft,which is called innovative control effector（ICE） aircraft.For the ICE morphing aircraft,the distributed arrays of hundreds of shape-change devices are employed to stabilize and maneuver the air vehicle.Because the morphing aircraft have the inherent uncertainty and varying dynamics due to the alteration of their configuration,a desired control performance can not be satisfied with a fixed feedback controller.Therefore,a novel control framework including an adaptive flight control law and an adaptive allocation algorithm is proposed.Firstly,a state feedback adaptive control law is designed to guarantee closed-loop stability and state tracking in the presence of uncertain dynamics caused by the wing shape change due to different flight missions.In the control allocation,many distributed arrays are managed in an optimal way to improve the robustness of the system.The scheme is used to an uncertain morphing aircraft model,and the simulation results demonstrate their performance.
基金the National Key Research and Development Program of China (Nos.2017YFC1404102,2017YFC1404100)the Strategic Priority Research Program of Chinese Academy of Sciences (Nos.XDB 40000000,XDB 42000000)+4 种基金the National Natural Science Foundation of China (Nos.41690122(41690120),41705082,41421005)the Shandong Taishan Scholarship,the China Postdoctoral Science Foundation (Nos.2018M640659,2019M662453)YU Yongqiang is jointly supported by the Strategic Priority Research Program of Chinese Academy of Sciences (Nos.XDA 19060102.XDB 42000000)REN Hong-Li is jointly supported by the China National Science Foundation (No.41975094)the China National Key Research and Development Program on Monitoring,Early Warning and Prevention of Major Natural Disaster (No.2018YFC1506004)
文摘El Nino-Southern Oscillation(ENSO) is the strongest interannual signal that is producedby basinscale processes in the tropical Pacific,with significant effects on weather and climate worldwide.In the past,extensive and intensive international efforts have been devoted to coupled model developments for ENSO studies.A hierarchy of coupled ocean-atmo sphere models has been formulated;in terms of their complexity,they can be categorized into intermediate coupled models(ICMs),hybrid coupled models(HCMs),and fully coupled general circulation models(CGCMs).ENSO modeling has made significant progress over the past decades,reaching a stage where coupled models can now be used to successfully predict ENSO events 6 months to one year in advance.Meanwhile,ENSO exhibits great diversity and complexity as observed in nature,which still cannot be adequately captured by current state-of-the-art coupled models,presenting a challenge to ENSO modeling.We primarily reviewed the long-term efforts in ENSO modeling continually and steadily made at different institutions in China;some selected representative examples are presented here to review the current status of ENSO model developments and applications,which have been actively pursued with noticeable progress being made recently.As ENSO simulations are very sensitive to model formulations and process representations etc.,dedicated efforts have been devoted to ENSO model developments and improvements.Now,different ocean-atmosphere coupled models have been available in China,which exhibit good model performances and have already had a variety of applications to climate modeling,including the Coupled Model Intercomparison Project Phase 6(CMIP6).Nevertheless,large biases and uncertainties still exist in ENSO simulations and predictions,and there are clear rooms for their improvements,which are still an active area of researches and applications.Here,model performances of ENSO simulations are assessed in terms of advantages and disadvantages with these differently formulated coupled models,pinpointing to the areas where they need to be further improved for ENSO studies.These analyses provide valuable guidance for future improvements in ENSO simulations and predictions.
文摘Joint parameter identification is a key problem in the modeling of complex structures. The behavior of joint may be random due to the random properties of preload and joint geometries, contact surface and its finish, etc. A method is presented to simulate the joint parameters as probabilistic variables. In this method the response surface based model updating method and probabilistic approaches are employed to identify the parameters. The study implies that joint parameters of some structures have normal or nearly normal distributions, and a linear FE model with probabilistic variables could illustrate dynamic characteristics of joints.
文摘Different performance levels may be obtained for sideway collapse evaluation of steel moment frames depending on the evaluation procedure used to handle uncertainties. In this article, the process of representing modelling uncertainties, record to record （RTR） variations and cognitive uncertainties for moment resisting steel frames of various heights is discussed in detail. RTR uncertainty is used by incremental dynamic analysis （IDA）, modelling uncertainties are considered through backbone curves and hysteresis loops of component, and cognitive uncertainty is presented in three levels of material quality. IDA is used to evaluate RTR uncertainty based on strong ground motion records selected by the k-means algorithm, which is favoured over Monte Carlo selection due to its time saving appeal. Analytical equations of the Response Surface Method are obtained through IDA results by the Cuckoo algorithm, which predicts the mean and standard deviation of the collapse fragility curve. The Takagi-Sugeno-Kang model is used to represent material quality based on the response surface coefficients. Finally, collapse fragility curves with the various sources of uncertainties mentioned are derived through a large number of material quality values and meta variables inferred by the Takagi-Sugeno-Kang fuzzy model based on response surface method coefficients. It is concluded that a better risk management strategy in countries where material quality control is weak, is to account for cognitive uncertainties in fragility curves and the mean annual frequency.
基金Supported by the National Natural Science Foundation of China(No.11372309,61304017)Science and Technology Development Plan Key Project of Jilin Province(No.20150204074GX)the Science and Technology Special Fund Project of Provincial Academy Cooperation(No.2017SYHZ00024)
文摘The robust attitude control for a novel coaxial twelve-rotor UAV which has much greater payload capacity,higher drive capability and damage tolerance than a quad-rotor UAV is studied. Firstly,a dynamical and kinematical model for the coaxial twelve-rotor UAV is designed. Considering model uncertainties and external disturbances,a robust backstepping sliding mode control( BSMC) with self recurrent wavelet neural network( SRWNN) method is proposed as the attitude controller for the coaxial twelve-rotor. A combinative algorithm of backstepping control and sliding mode control has simplified design procedures with much stronger robustness benefiting from advantages of both controllers. SRWNN as the uncertainty observer is able to estimate the lumped uncertainties effectively.Then the uniformly ultimate stability of the twelve-rotor system is proved by Lyapunov stability theorem. Finally,the validity of the proposed robust control method adopted in the twelve-rotor UAV under model uncertainties and external disturbances are demonstrated via numerical simulations and twelve-rotor prototype experiments.
基金supported by Iron Ore Research Center of Yazd University
文摘Uncertainty on the geological contacts and the block volumes of the models along boundaries is often a major part of the global uncertainty of reserve estimation.This work introduces a geostatistical technique that has been developed and tested in an iron ore deposit at Bafq mining district,in central Iran,and that,based on a probability criterion,helps to objectively model the geometry of this iron ore deposit.The main problem in reserve estimation of this ore body is its geometrical modeling and uncertainty in geological boundaries.This work deals with the geostatistical method of multiple indicator kriging,which is used to determine the real boundaries of ore body in different categories.This approach has potential to improve project performance and decrease operational risk.For this purpose,the ore body is separated into two categories including rich iron zone(w(Fe)>45%)and poor iron zone(20%<w(Fe)<45%).It significantly benefits to decrease the risk of reserve evaluation in the deposit.This case study also highlights the value of multiple indicator kriging as a tool for estimates the position of grade boundaries within the deposit.Comparison of the resultant probability maps with the real ore/waste contacts on the extracted levels shows that the first indicator model could separate the whole ore body(poor plus rich)from the waste zone by probability of more than 0.35,which concludes the total reserve of 53 million tons.The second indicator model applied to separate the rich and poor domains and the results show that the blocks with the estimated probability of equal to or more than 0.4 lay within the rich ore zone consisting of 15.8 million tons reserve.
