A novel control scheme of active disturbance rejection internal model control(ADRIMC) is proposed to improve the anti-interference ability and robustness for the dead-time process. The active anti-interference concept...A novel control scheme of active disturbance rejection internal model control(ADRIMC) is proposed to improve the anti-interference ability and robustness for the dead-time process. The active anti-interference concept is introduced into the internal model control(IMC) by analyzing the relationship between IMC and disturbance observer control(DOB). Further, a design process of disturbance filter is presented to realize the active anti-interference ability for ADRIMC scheme. The disturbance filter is used to estimate an equivalent disturbance consisting of both external disturbances and internal disturbances caused by model mismatches.Simulation results demonstrate that the proposed method possesses a good disturbance rejection performance, though losing some partial dynamic performance. In other words, the proposed method shows a tradeoff between the dynamic performance and the system robust.展开更多
A modified two-degrees-of-freedom( M-TDOF) internal model control( IMC) method is proposed for non-square systems with multiple time delays and right-half-plane( RHP) zeros. In this method,pseudo-inverse is introduced...A modified two-degrees-of-freedom( M-TDOF) internal model control( IMC) method is proposed for non-square systems with multiple time delays and right-half-plane( RHP) zeros. In this method,pseudo-inverse is introduced to design the internal model controller,and a desired closed-loop transfer function is designed to eliminate the unrealizable factors of the derived controller. In addition,set-point tracking and load-disturbance rejection of each process are separately controlled by two controllers. The simulation results show that in addition to high decoupling performance and robustness,the proposed control method also effectively improves loaddisturbance rejection and simultaneously optimizes the input tracking performance and disturbance rejection performance by selecting the parameters of controllers. Furthermore,the higher tolerance of model mismatch is achieved in this paper.展开更多
In this paper,a multi-loop internal model control(IMC) scheme in conjunction with feed-forward strategy based on the dynamic partial least squares(DyPLS) framework is proposed.Unlike the traditional methods to decoupl...In this paper,a multi-loop internal model control(IMC) scheme in conjunction with feed-forward strategy based on the dynamic partial least squares(DyPLS) framework is proposed.Unlike the traditional methods to decouple multi-input multi-output(MIMO) systems,the DyPLS framework automatically decomposes the MIMO process into a multi-loop system in the PLS subspace in the modeling stage.The dynamic filters with identical structure are used to build the dynamic PLS model,which retains the orthogonality among the latent variables.To address the model mismatch problem,an off-line least squares method is applied to obtain a set of optimal filter parameters in each latent space.Without losing the merits of model-based control,a simple and easy-tuned IMC structure is readily carried over to the dynamic PLS control framework.In addition,by projecting the measurable disturbance into the latent subspace,a multi-loop feed-forward control is yielded to achieve better performance for disturbance rejection.Simulation results of a distillation column are used to further demonstrate this new strategy outperforms conventional control schemes in servo behavior and disturbance rejection.展开更多
Because of vehicle＇s external disturbances and model uncertainties,robust control algorithms have obtained popularity in vehicle stability control.The robust control usually gives up performance in order to guarantee...Because of vehicle＇s external disturbances and model uncertainties,robust control algorithms have obtained popularity in vehicle stability control.The robust control usually gives up performance in order to guarantee the robustness of the control algorithm,therefore an improved robust internal model control（IMC） algorithm blending model tracking and internal model control is put forward for active steering system in order to reach high performance of yaw rate tracking with certain robustness.The proposed algorithm inherits the good model tracking ability of the IMC control and guarantees robustness to model uncertainties.In order to separate the design process of model tracking from the robustness design process,the improved 2 degree of freedom（DOF） robust internal model controller structure is given from the standard Youla parameterization.Simulations of double lane change maneuver and those of crosswind disturbances are conducted for evaluating the robust control algorithm,on the basis of a nonlinear vehicle simulation model with a magic tyre model.Results show that the established 2-DOF robust IMC method has better model tracking ability and a guaranteed level of robustness and robust performance,which can enhance the vehicle stability and handling,regardless of variations of the vehicle model parameters and the external crosswind interferences.Contradiction between performance and robustness of active steering control algorithm is solved and higher control performance with certain robustness to model uncertainties is obtained.展开更多
This paper proposes a design of internal model control systems for process with delay by using support vector regression(SVR).The proposed system fully uses the excellent nonlinear estimation performance of SVR with t...This paper proposes a design of internal model control systems for process with delay by using support vector regression(SVR).The proposed system fully uses the excellent nonlinear estimation performance of SVR with the structural risk minimization principle.Closed-system stability and steady error are analyzed for the existence of modeling errors.The simulations show that the proposed control systems have the better control performance than that by neural networks in the cases of the training samples with small size and noises.展开更多
An adaptive internal mode control is proposed to eliminate effectively periodic disturbance with uncertain frequency caused by input error angle of PIGA （Pendulous Integrating Gyro Accelerometer）. An adaptive algori...An adaptive internal mode control is proposed to eliminate effectively periodic disturbance with uncertain frequency caused by input error angle of PIGA （Pendulous Integrating Gyro Accelerometer）. An adaptive algorithm with periodic disturbance frequency identification on line is applied and the internal model controller parameters are adjusted to eliminate disturbance. Then the convergence of this algorithm and the stability of the system are proved by the averaging method. Simulation results verify the proposed scheme can eliminate periodic disturbance and improve the test precision for PIGA effectively.展开更多
A design method is presented for Takagi-Sugeno （T-S） fuzzy model based nonlinear sliding model controller. First, the closed-loop fuzzy system is divided into a set of dominant local linear systems according to oper...A design method is presented for Takagi-Sugeno （T-S） fuzzy model based nonlinear sliding model controller. First, the closed-loop fuzzy system is divided into a set of dominant local linear systems according to operating sub-regions. In each sub-region the fuzzy system consists of nominal linear system and a group of interacting systems. Then the controller composed two parts is designed. One part is designed to control the nominal system, the other is designed to control the interacting systems with sliding mode theory. The proposed controller can improve the robusmess and gnarantee tracking performance of the fuzzy system. Stability is guaranteed without finding a common positive definite matrix.展开更多
A new chaos control method is proposed to take advantage of chaos or avoid it. The hybrid Internal Model Control and Proportional Control learning scheme are introduced. In order to gain the desired robust performance...A new chaos control method is proposed to take advantage of chaos or avoid it. The hybrid Internal Model Control and Proportional Control learning scheme are introduced. In order to gain the desired robust performance and ensure the system's stability, Adaptive Momentum Algorithms are also developed. Through properly designing the neural network plant model and neural network controller, the chaotic dynamical systems are controlled while the parameters of the BP neural network are modified. Taking the Lorenz chaotic system as example, the results show that chaotic dynamical systems can be stabilized at the desired orbits by this control strategy.展开更多
Dynamic model control technologies of secondary cooling and soft reduction of Baosteel are introduced. Model principle and control system architecture are summarized, as well as functions and features. Finally, applic...Dynamic model control technologies of secondary cooling and soft reduction of Baosteel are introduced. Model principle and control system architecture are summarized, as well as functions and features. Finally, applications of model technologies are discussed. The self-developed dynamic secondary cooling model and the dynamic soft reduction model have been applied on several casting machines inside and outside Baosteel, desired control effects were achieved with good stability and reliability. Temperature measurement results verified the correctness of model.展开更多
One synthetical control method of AGC/LPC system based on intelligence control theory-neural networks internal model control method is presented. Genetic algorithm (GA) is applied to optimize the parameters of the neu...One synthetical control method of AGC/LPC system based on intelligence control theory-neural networks internal model control method is presented. Genetic algorithm (GA) is applied to optimize the parameters of the neural networks. Simulation results prove that this method is effective.展开更多
Nonlinearity is an important characteristic in electrostatic suspension system (ESS). This paper concludes the nonlinear parts in ESS, which generally result from the relationships between rotor displacement and capac...Nonlinearity is an important characteristic in electrostatic suspension system (ESS). This paper concludes the nonlinear parts in ESS, which generally result from the relationships between rotor displacement and capacitance, rotor displacement and electrostatic force, and control voltage and electrostatic force. In terms of the nonlinearities, a new control method with modified internal model control (IMC) was proposed to analyze the ESS, deduce the transfer function of the modified IMC controller in ESS, and simulate this new application in ESS. Comparing with proportional integral derivative (PID) control, IMC has only a parameter, and has better performance. As a result, IMC solves nonlinearity error well in ESS with only one uncertain parameter, and performs well when the rotor has large displacement.展开更多
Finite control set model predictive torque control(FCS-MPTC)has become increasingly prevalent for induction motors(IM)owing to its simple concept,easy incorporation of constraints and strong flexibility.In traditional...Finite control set model predictive torque control(FCS-MPTC)has become increasingly prevalent for induction motors(IM)owing to its simple concept,easy incorporation of constraints and strong flexibility.In traditional FCS-MPTC speed controller design,a classical proportional integral(PI)controller is typically chosen to generate the torque reference.However,the PI controller is dependent on system parameters and sensitive to the load torque variation,which seriously affects control performance.In this paper,a model predictive torque control using sliding mode control(MPTC+SMC)for IM is proposed to enhance the robust performance of the drive system.First,the influence of the parameter mismatches for FCS-MPTC is analyzed.Second,the shortcomings of traditional PI controller are derived.Then,the proposed MPTC+SMC method is designed,and the MPTC+PI and MPTC+SMC are compared theoretically.Finally,experimental results demonstrate the correctness and effectiveness of the proposed MPTC+SMC.In comparison with MPTC+PI,MPTC+SMC has the better dynamic performance and stronger robust performance against parameter variations and load disturbance.展开更多
A novel approach to design Internal Model Controller(IMC)is proposed in this paper directly from measuredinput and output plant data,which are assumed to becontaminated by measurement noise.In order to avoidthe compli...A novel approach to design Internal Model Controller(IMC)is proposed in this paper directly from measuredinput and output plant data,which are assumed to becontaminated by measurement noise.In order to avoidthe complicated structure-identification problem inmost cases,two Finite Impulse Response(FIR)modelsare taken to represent the plant model and the internalmodel controller respectively.Taking account of mea-surement noise both in the plant input and its output,anESD based Total Least Squares(TLS)solution is appliedfor the unbiased identification of the plant model and itsinverse model,the latter constitutes the internal modelcontroller according to the principle that the internalmodel controller approximates the inverse dynamics ofthe plant model.Simulations are given for a testifica-tion.展开更多
An inverse model control based on TS-fuzzy support vector regression( TS-fuzzy SVR) for a quadrotor aircraft is developed. The TS-kernel is the product of linear combination of input and a cluster of output correspond...An inverse model control based on TS-fuzzy support vector regression( TS-fuzzy SVR) for a quadrotor aircraft is developed. The TS-kernel is the product of linear combination of input and a cluster of output corresponding to a cluster of TS-type fuzzy rules. The output of TS-fuzzy SVR is a linear weighted sum of the TSkernels. The dynamical model of the quad-rotor aircraft is derived. A new control scheme combined with TSfuzzy SVR inverse model control and PID control is presented so that the TS-fuzzy SVR inverse model control enhances capabilities of disturbance rejection and the robustness while the PID control enhances fast responsiveness and reliability of the system. Simulation results show the capabilities of the developed control for the attitude system of quad-rotor aircraft.展开更多
This work concerns the study of problems relating to the adaptive internal model control of DC motor in both cases conventional and neural. The most important aspects of design building blocks of adaptive internal mod...This work concerns the study of problems relating to the adaptive internal model control of DC motor in both cases conventional and neural. The most important aspects of design building blocks of adaptive internal model control are the choice of architectures, learning algorithms, and examples of learning. The choice of parametric adaptation algorithm for updating elements of the conventional adaptive internal model control shows limitations. To overcome these limitations, we chose the architectures of neural networks deduced from the conventional models and the Levenberg-marquardt during the adjustment of system parameters of the adaptive neural internal model control. The results of this latest control showed compensation for disturbance, good trajectory tracking performance and system stability.展开更多
In this paper, we introduce a new Control Lyapunov Function (CLF) approach for controlling the behavior of nonlinear uncertain HIV-1 models. The uncertainty is in decay parameters and also external control setting. CL...In this paper, we introduce a new Control Lyapunov Function (CLF) approach for controlling the behavior of nonlinear uncertain HIV-1 models. The uncertainty is in decay parameters and also external control setting. CLF is then applied to different strategies. One such strategy considers input into infected cells population stage and the other considers input into a virus population stage. Furthermore, by adding noise to the HIV-1 model a realistic comparison between control strategies is presented to evaluate the system’s dynamics. It has been demonstrated that nonlinear control has effectiveness and robustness, in reducing virus loading to an undetectable level.展开更多
This paper investigates integration of distributed energy resources(DERs)in microgrids(MGs)through two-stage power conversion structures consisting of DC-DC boost converter and DC-AC voltage source converter(VSC)subsy...This paper investigates integration of distributed energy resources(DERs)in microgrids(MGs)through two-stage power conversion structures consisting of DC-DC boost converter and DC-AC voltage source converter(VSC)subsystems.In contrast to existing investigations that treated DC-link voltage as an ideal constant voltage,this paper considers the non-ideal dynamic coupling between both subsystems for completeness and higher accuracy,which introduces additional DC-side dynamics to the VSC.The analysis shows parameters of the boost converter’s power model that impact stability through the DC-link.Carefully selecting these parameters can mitigate this effect on stability and improve dynamic performance across the DC-link.Hence,an optimization framework is developed to facilitate in selecting adequate boost converter parameters in designing a stable voltage source converter-based microgrid(VSC-MG).The developed optimization framework,based on particle swarm optimization,considers dynamic coupling between both subsystems and is also effective in avoiding inadequate boost converter parameters capable of propagating instability through the DC-link to the VSC.Simulations are performed with MATLAB/Simulink to validate theoretical analyses.展开更多
Increasing attention has been paid to the efficiency improvement of the induction traction system of high-speed trains due to the high demand for energy saving. In emergency self-propelled mode, however, the dc-link v...Increasing attention has been paid to the efficiency improvement of the induction traction system of high-speed trains due to the high demand for energy saving. In emergency self-propelled mode, however, the dc-link voltage and the traction power of the motor are significantly reduced, resulting in decreased traction efficiency due to the low load and low speed operations. Aiming to tackle this problem, a novel efficiency improved control method is introduced to the emergency mode of high-speed train traction system in this paper. In the proposed method, a total loss model of induction motor considering the behaviors of both iron and copper loss is established. An improved iterative algorithm with decreased computational burden is then introduced, resulting in a fast solving of the optimal flux reference for loss minimization at each control period. In addition, considering the parameter variation problem due to the low load and low speed operations, a parameter estimation method is integrated to improve the controller's robustness. The effectiveness of the proposed method on efficiency improvement at low voltage and low load conditions is demonstrated by simulated and experimental results.展开更多
This article focuses on dynamic event-triggered mechanism(DETM)-based model predictive control(MPC) for T-S fuzzy systems.A hybrid dynamic variables-dependent DETM is carefully devised,which includes a multiplicative ...This article focuses on dynamic event-triggered mechanism(DETM)-based model predictive control(MPC) for T-S fuzzy systems.A hybrid dynamic variables-dependent DETM is carefully devised,which includes a multiplicative dynamic variable and an additive dynamic variable.The addressed DETM-based fuzzy MPC issue is described as a “min-max” optimization problem(OP).To facilitate the co-design of the MPC controller and the weighting matrix of the DETM,an auxiliary OP is proposed based on a new Lyapunov function and a new robust positive invariant(RPI) set that contain the membership functions and the hybrid dynamic variables.A dynamic event-triggered fuzzy MPC algorithm is developed accordingly,whose recursive feasibility is analysed by employing the RPI set.With the designed controller,the involved fuzzy system is ensured to be asymptotically stable.Two examples show that the new DETM and DETM-based MPC algorithm have the advantages of reducing resource consumption while yielding the anticipated performance.展开更多
基金Project(61273132)supported by the National Natural Foundation of ChinaProject(20110010010)supported by Higher School Specialized Research Fund for the Doctoral Program,China
文摘A novel control scheme of active disturbance rejection internal model control(ADRIMC) is proposed to improve the anti-interference ability and robustness for the dead-time process. The active anti-interference concept is introduced into the internal model control(IMC) by analyzing the relationship between IMC and disturbance observer control(DOB). Further, a design process of disturbance filter is presented to realize the active anti-interference ability for ADRIMC scheme. The disturbance filter is used to estimate an equivalent disturbance consisting of both external disturbances and internal disturbances caused by model mismatches.Simulation results demonstrate that the proposed method possesses a good disturbance rejection performance, though losing some partial dynamic performance. In other words, the proposed method shows a tradeoff between the dynamic performance and the system robust.
基金Sponsored by the Fundamental Research Funds for the Central Universities(Grant No.N110304008)the National Natural Science Foundation of China(Grant No.61374137)
文摘A modified two-degrees-of-freedom( M-TDOF) internal model control( IMC) method is proposed for non-square systems with multiple time delays and right-half-plane( RHP) zeros. In this method,pseudo-inverse is introduced to design the internal model controller,and a desired closed-loop transfer function is designed to eliminate the unrealizable factors of the derived controller. In addition,set-point tracking and load-disturbance rejection of each process are separately controlled by two controllers. The simulation results show that in addition to high decoupling performance and robustness,the proposed control method also effectively improves loaddisturbance rejection and simultaneously optimizes the input tracking performance and disturbance rejection performance by selecting the parameters of controllers. Furthermore,the higher tolerance of model mismatch is achieved in this paper.
基金Supported by the National Natural Science Foundation of China（60574047） the National High Technology Research and Development Program of China（2007AA04Z168 2009AA04Z154） the Research Fund for the Doctoral Program of Higher Education in China（20050335018）
文摘In this paper,a multi-loop internal model control(IMC) scheme in conjunction with feed-forward strategy based on the dynamic partial least squares(DyPLS) framework is proposed.Unlike the traditional methods to decouple multi-input multi-output(MIMO) systems,the DyPLS framework automatically decomposes the MIMO process into a multi-loop system in the PLS subspace in the modeling stage.The dynamic filters with identical structure are used to build the dynamic PLS model,which retains the orthogonality among the latent variables.To address the model mismatch problem,an off-line least squares method is applied to obtain a set of optimal filter parameters in each latent space.Without losing the merits of model-based control,a simple and easy-tuned IMC structure is readily carried over to the dynamic PLS control framework.In addition,by projecting the measurable disturbance into the latent subspace,a multi-loop feed-forward control is yielded to achieve better performance for disturbance rejection.Simulation results of a distillation column are used to further demonstrate this new strategy outperforms conventional control schemes in servo behavior and disturbance rejection.
基金Supported by National Natural Science Foundation of China(Grant No.51375009)PhD Research Foundation of Liaocheng University,China(Grant No.318051523)Tsinghua University Initiative Scientific Research Program,China
文摘Because of vehicle＇s external disturbances and model uncertainties,robust control algorithms have obtained popularity in vehicle stability control.The robust control usually gives up performance in order to guarantee the robustness of the control algorithm,therefore an improved robust internal model control（IMC） algorithm blending model tracking and internal model control is put forward for active steering system in order to reach high performance of yaw rate tracking with certain robustness.The proposed algorithm inherits the good model tracking ability of the IMC control and guarantees robustness to model uncertainties.In order to separate the design process of model tracking from the robustness design process,the improved 2 degree of freedom（DOF） robust internal model controller structure is given from the standard Youla parameterization.Simulations of double lane change maneuver and those of crosswind disturbances are conducted for evaluating the robust control algorithm,on the basis of a nonlinear vehicle simulation model with a magic tyre model.Results show that the established 2-DOF robust IMC method has better model tracking ability and a guaranteed level of robustness and robust performance,which can enhance the vehicle stability and handling,regardless of variations of the vehicle model parameters and the external crosswind interferences.Contradiction between performance and robustness of active steering control algorithm is solved and higher control performance with certain robustness to model uncertainties is obtained.
文摘This paper proposes a design of internal model control systems for process with delay by using support vector regression(SVR).The proposed system fully uses the excellent nonlinear estimation performance of SVR with the structural risk minimization principle.Closed-system stability and steady error are analyzed for the existence of modeling errors.The simulations show that the proposed control systems have the better control performance than that by neural networks in the cases of the training samples with small size and noises.
文摘An adaptive internal mode control is proposed to eliminate effectively periodic disturbance with uncertain frequency caused by input error angle of PIGA （Pendulous Integrating Gyro Accelerometer）. An adaptive algorithm with periodic disturbance frequency identification on line is applied and the internal model controller parameters are adjusted to eliminate disturbance. Then the convergence of this algorithm and the stability of the system are proved by the averaging method. Simulation results verify the proposed scheme can eliminate periodic disturbance and improve the test precision for PIGA effectively.
文摘A design method is presented for Takagi-Sugeno （T-S） fuzzy model based nonlinear sliding model controller. First, the closed-loop fuzzy system is divided into a set of dominant local linear systems according to operating sub-regions. In each sub-region the fuzzy system consists of nominal linear system and a group of interacting systems. Then the controller composed two parts is designed. One part is designed to control the nominal system, the other is designed to control the interacting systems with sliding mode theory. The proposed controller can improve the robusmess and gnarantee tracking performance of the fuzzy system. Stability is guaranteed without finding a common positive definite matrix.
文摘A new chaos control method is proposed to take advantage of chaos or avoid it. The hybrid Internal Model Control and Proportional Control learning scheme are introduced. In order to gain the desired robust performance and ensure the system's stability, Adaptive Momentum Algorithms are also developed. Through properly designing the neural network plant model and neural network controller, the chaotic dynamical systems are controlled while the parameters of the BP neural network are modified. Taking the Lorenz chaotic system as example, the results show that chaotic dynamical systems can be stabilized at the desired orbits by this control strategy.
文摘Dynamic model control technologies of secondary cooling and soft reduction of Baosteel are introduced. Model principle and control system architecture are summarized, as well as functions and features. Finally, applications of model technologies are discussed. The self-developed dynamic secondary cooling model and the dynamic soft reduction model have been applied on several casting machines inside and outside Baosteel, desired control effects were achieved with good stability and reliability. Temperature measurement results verified the correctness of model.
文摘One synthetical control method of AGC/LPC system based on intelligence control theory-neural networks internal model control method is presented. Genetic algorithm (GA) is applied to optimize the parameters of the neural networks. Simulation results prove that this method is effective.
基金Weaponry Advanced FundItem of China(No51409030101JW03)
文摘Nonlinearity is an important characteristic in electrostatic suspension system (ESS). This paper concludes the nonlinear parts in ESS, which generally result from the relationships between rotor displacement and capacitance, rotor displacement and electrostatic force, and control voltage and electrostatic force. In terms of the nonlinearities, a new control method with modified internal model control (IMC) was proposed to analyze the ESS, deduce the transfer function of the modified IMC controller in ESS, and simulate this new application in ESS. Comparing with proportional integral derivative (PID) control, IMC has only a parameter, and has better performance. As a result, IMC solves nonlinearity error well in ESS with only one uncertain parameter, and performs well when the rotor has large displacement.
基金supported in part by the National Natural Science Funds of China under Grants 5217071282 and 5210071275in part by China Postdoctoral Science Foundation under Grant 2020M683524+7 种基金in part by Nature Science Basic Research Plan in Shaanxi Province under Grant 2020JQ-631 and 2021JQ-477in part by State Key Laboratory of Electrical Insulation and Power Equipment under Grant EIPE20201in part by State Key Laboratory of Large Electric Drive System and Equipment Technology under Grant SKLLDJ012016006in part by Key Research and Development Project of ShaanXi Province under Grant 2019GY-060in part by Key Laboratory of Industrial Automation in ShaanXi Province under Grant SLGPT2019KF01-12in part by the Key R&D plan of Shaanxi Province under Grant 2021GY-282in part by Shaanxi Outstanding Youth Fund under Grant 2020JC-40in part by Key Laboratory of Power Electronic Devices and High Efficiency Power Conversion in Xi’an under Grant 2019219814SYS013CG035。
文摘Finite control set model predictive torque control(FCS-MPTC)has become increasingly prevalent for induction motors(IM)owing to its simple concept,easy incorporation of constraints and strong flexibility.In traditional FCS-MPTC speed controller design,a classical proportional integral(PI)controller is typically chosen to generate the torque reference.However,the PI controller is dependent on system parameters and sensitive to the load torque variation,which seriously affects control performance.In this paper,a model predictive torque control using sliding mode control(MPTC+SMC)for IM is proposed to enhance the robust performance of the drive system.First,the influence of the parameter mismatches for FCS-MPTC is analyzed.Second,the shortcomings of traditional PI controller are derived.Then,the proposed MPTC+SMC method is designed,and the MPTC+PI and MPTC+SMC are compared theoretically.Finally,experimental results demonstrate the correctness and effectiveness of the proposed MPTC+SMC.In comparison with MPTC+PI,MPTC+SMC has the better dynamic performance and stronger robust performance against parameter variations and load disturbance.
文摘A novel approach to design Internal Model Controller(IMC)is proposed in this paper directly from measuredinput and output plant data,which are assumed to becontaminated by measurement noise.In order to avoidthe complicated structure-identification problem inmost cases,two Finite Impulse Response(FIR)modelsare taken to represent the plant model and the internalmodel controller respectively.Taking account of mea-surement noise both in the plant input and its output,anESD based Total Least Squares(TLS)solution is appliedfor the unbiased identification of the plant model and itsinverse model,the latter constitutes the internal modelcontroller according to the principle that the internalmodel controller approximates the inverse dynamics ofthe plant model.Simulations are given for a testifica-tion.
基金Sponsored by the Science and Technology Support Program of Jiangsu Province(Grant No.SBE2014070836)
文摘An inverse model control based on TS-fuzzy support vector regression( TS-fuzzy SVR) for a quadrotor aircraft is developed. The TS-kernel is the product of linear combination of input and a cluster of output corresponding to a cluster of TS-type fuzzy rules. The output of TS-fuzzy SVR is a linear weighted sum of the TSkernels. The dynamical model of the quad-rotor aircraft is derived. A new control scheme combined with TSfuzzy SVR inverse model control and PID control is presented so that the TS-fuzzy SVR inverse model control enhances capabilities of disturbance rejection and the robustness while the PID control enhances fast responsiveness and reliability of the system. Simulation results show the capabilities of the developed control for the attitude system of quad-rotor aircraft.
文摘This work concerns the study of problems relating to the adaptive internal model control of DC motor in both cases conventional and neural. The most important aspects of design building blocks of adaptive internal model control are the choice of architectures, learning algorithms, and examples of learning. The choice of parametric adaptation algorithm for updating elements of the conventional adaptive internal model control shows limitations. To overcome these limitations, we chose the architectures of neural networks deduced from the conventional models and the Levenberg-marquardt during the adjustment of system parameters of the adaptive neural internal model control. The results of this latest control showed compensation for disturbance, good trajectory tracking performance and system stability.
文摘In this paper, we introduce a new Control Lyapunov Function (CLF) approach for controlling the behavior of nonlinear uncertain HIV-1 models. The uncertainty is in decay parameters and also external control setting. CLF is then applied to different strategies. One such strategy considers input into infected cells population stage and the other considers input into a virus population stage. Furthermore, by adding noise to the HIV-1 model a realistic comparison between control strategies is presented to evaluate the system’s dynamics. It has been demonstrated that nonlinear control has effectiveness and robustness, in reducing virus loading to an undetectable level.
基金supported by the U.S.National Science Foundation under Grant#2124849.
文摘This paper investigates integration of distributed energy resources(DERs)in microgrids(MGs)through two-stage power conversion structures consisting of DC-DC boost converter and DC-AC voltage source converter(VSC)subsystems.In contrast to existing investigations that treated DC-link voltage as an ideal constant voltage,this paper considers the non-ideal dynamic coupling between both subsystems for completeness and higher accuracy,which introduces additional DC-side dynamics to the VSC.The analysis shows parameters of the boost converter’s power model that impact stability through the DC-link.Carefully selecting these parameters can mitigate this effect on stability and improve dynamic performance across the DC-link.Hence,an optimization framework is developed to facilitate in selecting adequate boost converter parameters in designing a stable voltage source converter-based microgrid(VSC-MG).The developed optimization framework,based on particle swarm optimization,considers dynamic coupling between both subsystems and is also effective in avoiding inadequate boost converter parameters capable of propagating instability through the DC-link to the VSC.Simulations are performed with MATLAB/Simulink to validate theoretical analyses.
基金supported in part by the Science Foundation of the Chinese Academy of Railway Sciences under Grant Number:2023QT001。
文摘Increasing attention has been paid to the efficiency improvement of the induction traction system of high-speed trains due to the high demand for energy saving. In emergency self-propelled mode, however, the dc-link voltage and the traction power of the motor are significantly reduced, resulting in decreased traction efficiency due to the low load and low speed operations. Aiming to tackle this problem, a novel efficiency improved control method is introduced to the emergency mode of high-speed train traction system in this paper. In the proposed method, a total loss model of induction motor considering the behaviors of both iron and copper loss is established. An improved iterative algorithm with decreased computational burden is then introduced, resulting in a fast solving of the optimal flux reference for loss minimization at each control period. In addition, considering the parameter variation problem due to the low load and low speed operations, a parameter estimation method is integrated to improve the controller's robustness. The effectiveness of the proposed method on efficiency improvement at low voltage and low load conditions is demonstrated by simulated and experimental results.
基金supported by the National Natural Science Foundation of China (62073303,61673356)Hubei Provincial Natural Science Foundation of China (2015CFA010)the 111 Project(B17040)。
文摘This article focuses on dynamic event-triggered mechanism(DETM)-based model predictive control(MPC) for T-S fuzzy systems.A hybrid dynamic variables-dependent DETM is carefully devised,which includes a multiplicative dynamic variable and an additive dynamic variable.The addressed DETM-based fuzzy MPC issue is described as a “min-max” optimization problem(OP).To facilitate the co-design of the MPC controller and the weighting matrix of the DETM,an auxiliary OP is proposed based on a new Lyapunov function and a new robust positive invariant(RPI) set that contain the membership functions and the hybrid dynamic variables.A dynamic event-triggered fuzzy MPC algorithm is developed accordingly,whose recursive feasibility is analysed by employing the RPI set.With the designed controller,the involved fuzzy system is ensured to be asymptotically stable.Two examples show that the new DETM and DETM-based MPC algorithm have the advantages of reducing resource consumption while yielding the anticipated performance.
