For multisensor systems,when the model parameters and the noise variances are unknown,the consistent fused estimators of the model parameters and noise variances are obtained,based on the system identification algorit...For multisensor systems,when the model parameters and the noise variances are unknown,the consistent fused estimators of the model parameters and noise variances are obtained,based on the system identification algorithm,correlation method and least squares fusion criterion.Substituting these consistent estimators into the optimal weighted measurement fusion Kalman filter,a self-tuning weighted measurement fusion Kalman filter is presented.Using the dynamic error system analysis （DESA） method,the convergence of the self-tuning weighted measurement fusion Kalman filter is proved,i.e.,the self-tuning Kalman filter converges to the corresponding optimal Kalman filter in a realization.Therefore,the self-tuning weighted measurement fusion Kalman filter has asymptotic global optimality.One simulation example for a 4-sensor target tracking system verifies its effectiveness.展开更多
For the multisensor system with correlated measurement noises and unknown noise statistics, based on the solution of the matrix equations for correlation function, the on-line estimators of the noise variances and cro...For the multisensor system with correlated measurement noises and unknown noise statistics, based on the solution of the matrix equations for correlation function, the on-line estimators of the noise variances and cross-covariances is obtained. Further, a self-tuning weighted measurement fusion Kalman filter is presented, based on the Riccati equation. By the Dynamic Error System Analysis (DESA) method, it rigorously proved that the presented self-tuning weighted measurement fusion Kalman filter converges to the optimal weighted measurement fusion steady-state Kalman filter in a realization or with probability one, so that it has asymptotic global optimality. A simulation example for a target tracking system with 3-sensor shows that the presented self-tuning measurement fusion Kalman fuser converges to the optimal steady-state measurement fusion Kalman fuser.展开更多
A self-tuning reaching law based sliding mode control(SMC)theory is proposed to stabilize the nonlinear continuous stirred tank reactor(CSTR).T-S fuzzy logic is used to build a global fuzzy state-space linear model.Co...A self-tuning reaching law based sliding mode control(SMC)theory is proposed to stabilize the nonlinear continuous stirred tank reactor(CSTR).T-S fuzzy logic is used to build a global fuzzy state-space linear model.Combing the traits of SMC and CSTR,three fuzzy rules can meet the requirements of controlled system.The self-tuning switch control law which can drive the state variables to the sliding surface as soon as possible is designed to ensure the robustness of uncertain fuzzy system.Lyapunov equation is applied to proving the stability of the sliding surface.The simulations show that the proposed approach can achieve desired performance with less chattering problem.展开更多
For the multisensor linear discrete time-invariant stochastic systems with correlated noises and unknown noise statistics,an on-line noise statistics estimator is presented by using the correlation method.Substituting...For the multisensor linear discrete time-invariant stochastic systems with correlated noises and unknown noise statistics,an on-line noise statistics estimator is presented by using the correlation method.Substituting it into the steady-state Riccati equation,the self-tuning Riccati equation is obtained.Using the Kalman filtering method,based on the self-tuning Riccati equation,a self-tuning weighted measurement fusion white noise deconvolution estimator is presented.By the dynamic error system analysis（DESA） method,it is proved that the self-tuning fusion white noise deconvolution estimator converges to the optimal fusion steadystate white noise deconvolution estimator in a realization,so that it has the asymptotic global optimality.A simulation example for Bernoulli-Gaussian input white noise shows its effectiveness.展开更多
This paper presents an efficient way to implement an interpolation filter in a 20bit ∑-△ DAC with an oversampling ratio of 128. A multistage structure is used to reduce the complexity of filter coefficients and the ...This paper presents an efficient way to implement an interpolation filter in a 20bit ∑-△ DAC with an oversampling ratio of 128. A multistage structure is used to reduce the complexity of filter coefficients and the fi- nite word length effect. A novel method based on mixed-radix number representation is proposed to realize a poly- phase multiplier-free half-band subfilter with a high resolution. This approach reduces the complexity of the con- trol system and saves chip area dramatically. The IC is realized in a standard 0.13μm CMOS process and the inter- polation filter occupies less than 0.63mm^2 . This realization has desirable properties of regularity with simple hard- ware devices which are suitable for VLSI and can be applied to many other high resolution data converters.展开更多
Dynamic load imposed on the bridge by mov- ing vehicle depends on several bridge-vehicle parameters with various uncertainties. In the present paper, particle filter technique based on conditional probability has been...Dynamic load imposed on the bridge by mov- ing vehicle depends on several bridge-vehicle parameters with various uncertainties. In the present paper, particle filter technique based on conditional probability has been used to identify vehicle mass, suspension stiffness, and damping including tyre parameters from simulated bridge accelerations at different locations. A closed-form expres- sion is derived to generate independent response samples for the idealized bridge-vehicle coupled system consider- ing spatially non-homogeneous pavement unevenness. Thereafter, it is interfaced with the iterative process of particle filtering algorithm. The generated response sam- ples are contaminated by adding artificial noise in order to reflect field condition. The mean acceleration time history is utilized in particle filtering technique. The vehicle- imposed dynamic load is reconstructed with the identified parameters and compared with the simulated results. The present identification technique is examined in the presence of different levels of artificial noise with bridge response simulated at different locations. The effect of vehicle velocity, bridge surface roughness, and choice of prior probability density parameters on the efficiency of the method is discussed.展开更多
In the field of mobile robotics,human tracking has emerged as an important objective for facilitating human-robot interaction.In this paper,we propose a particle-filter-based walking prediction model that will address...In the field of mobile robotics,human tracking has emerged as an important objective for facilitating human-robot interaction.In this paper,we propose a particle-filter-based walking prediction model that will address an occlusion situation.Since the target being tracked is a human leg,a motion model for a leg is required.The validity of the proposed model is verified experimentally.展开更多
This paper clarifies the steady-state properties and performance of an α-β filter for moving target tracking using both position and velocity measurements. We call this filter velocity measured α-β (VM-α-β) filt...This paper clarifies the steady-state properties and performance of an α-β filter for moving target tracking using both position and velocity measurements. We call this filter velocity measured α-β (VM-α-β) filter. We first derive the stability condition and steady-state predicted errors as fundamental properties of the VM-α-β filter. The optimal gains for representative motion models are then derived from the Kalman filter equations. Theoretical and numerical analyses verify that VM-α-β filters with these optimal gains realize more accurate tracking than conventional α-β filters when the filter gains are relatively large. Our study reveals the conditions under which the predicted errors of the VM-α-β filters are less than those of conventional α-β filters. Moreover, numerical simulations clarify that the variance of the tracking error of the VM-α-β filters is approximately 3/4 of that of the conventional α-β filters in realistic situations, even when the accuracy of the position/velocity measurements is the same.展开更多
The conceptions of the knowledge screen generated by S-rough sets are given: f- screen and - screen , and then puts forward - filter theorem, - filter theorem of knowledge. At last, the applications of knowledge separ...The conceptions of the knowledge screen generated by S-rough sets are given: f- screen and - screen , and then puts forward - filter theorem, - filter theorem of knowledge. At last, the applications of knowledge separation are given according to - screen and - screen.展开更多
Excellent drilling fluid techniques are one of the significant guaranteed measures to insure safety, qual- ity, efficiency, and speediness of drilling operations. Dril- ling fluids are generally discarded after the co...Excellent drilling fluid techniques are one of the significant guaranteed measures to insure safety, qual- ity, efficiency, and speediness of drilling operations. Dril- ling fluids are generally discarded after the completion of drilling operations and become waste, which can have a large negative impact on the environment. Drilling mate- rials and additives together with drill cuttings, oil, and water constitute waste drilling fluids, which ultimately are dumped onto soil, surface water, groundwater, and air. Environmental pollution is found to be a serious threat while drilling complex wells or high-temperature deep wells as these types of wells involve the use of oil-based drilling fluid systems and high-performance water-based drilling fluid systems. The preservation of the environment on a global level is now important as various organizations have set up initiatives to drive the usage of toxic chemicals as drilling fluid additives. This paper presents an approach where grass is introduced as a sustainable drilling fluid additive with no environmental problems. Simple water- based drilling fluids were formulated using bentonite, powdered grass, and water to analyze the rheological and filtration characteristics of the new drilling fluid. A particle size distribution test was conducted to determine the par- ticle size of the grass sample by the sieve analysis method. Experiments were conducted on grass samples of 300, 90, and 35 μm to study the characteristics and behavior of the newly developed drilling fluid at room temperature. The results show that grass samples with varying particle sizes and concentrations may improve the viscosity, gel strength, and filtration of the bentonite drilling fluid. These obser- vations recommend the use of grass as a rheological modifier, filtration control agent, and pH control agent to substitute toxic materials from drilling fluids.展开更多
DWDM technology is developing rapidly. Thin film narrow bandpass filter plays an important role in this field. This article presents some achievements in developing the DWDM narrow bandpass filters and also describes ...DWDM technology is developing rapidly. Thin film narrow bandpass filter plays an important role in this field. This article presents some achievements in developing the DWDM narrow bandpass filters and also describes the results achieved by us.展开更多
A velocity determination algorithm of GNSS receiver for high speed and high acceleration carrier in motion is mainly discussed in this paper. For this algorithm, the Doppler frequency value is extracted from the satel...A velocity determination algorithm of GNSS receiver for high speed and high acceleration carrier in motion is mainly discussed in this paper. For this algorithm, the Doppler frequency value is extracted from the satellite carrier tracking loop, and(α, β, γ) filter is adopted for smoothing, and least square is adopted to calculate the receiver speed and local clock drift. To get accurate determination value, a kind of fault detection and exclusion technology(FDE) is designed in this paper; the satellite Doppler frequency value with large error is detected and exclusion. Finally, the signal of GNSS signal simulator and actual navigational satellite signal are received for test, getting good velocity determination result.展开更多
An online noise variance estimator for multi-sensor systems with unknown noise variances is proposed by using the correlation method.Based on the Riccati equa-tion and optimal fusion rule weighted by scalars for state...An online noise variance estimator for multi-sensor systems with unknown noise variances is proposed by using the correlation method.Based on the Riccati equa-tion and optimal fusion rule weighted by scalars for state components,a self-tuning component decoupled informa-tion fusion Kalman filter is presented.It is proved that the filter converges to the optimal fusion Kalman filter in a realization by dynamic error system analysis method,so that it has asymptotic optimality.Its effectiveness is demon-strated by simulation for a tracking system with 3 sensors.展开更多
This paper presents a video-tracking system composed of two cameras. One camera acts for producing an in-focus image of the object and the other one ensures an extended vision field under monitoring. Such a system sch...This paper presents a video-tracking system composed of two cameras. One camera acts for producing an in-focus image of the object and the other one ensures an extended vision field under monitoring. Such a system scheme can achieve an excellent tracking performance,especially under various unfavorable conditions. A projection algorithm is used for the calculation of the displacement of the moving object. As a result, the computational cost is reduced greatly.In order that the tracking action of the system persists even if the object is sheltered or ns acceleration is larger than a specified threshold, a dedicated tracking algorithm on the basis of the α-β filtering is designed. Experiments show that the algorithm is efficient and the system works very well.展开更多
In the step processing a digitalized signal,noises are generated by internal or external causes of the system.In order to eliminate these noises,various methods are researched.Among these noise elimination methods,Fou...In the step processing a digitalized signal,noises are generated by internal or external causes of the system.In order to eliminate these noises,various methods are researched.Among these noise elimination methods,Fourier fast transform(FFT)and short-time Fourier transform(STFT)are widely used.Because they are expressed as a fixed time-frequency domain,they have the disadvantage that the time information about the signal is unknown.In order to overcome these limitations,by using the wavelet transform that provides a variety of time-frequency resolution,multi-resolution analysis can be analysed and a varying noise depending on the time characteristics can be removed more efficiently.Therefore,in this paper,a denoising method of underwater vehicle using discrete wavelet transform(DWT)is proposed.展开更多
This paper proposes a steady-state errors correction(SSEC)method for eliminating measurement errors.This method is based on the detections of error signal E(s)and output C(s)which generate an expected output R(s).In c...This paper proposes a steady-state errors correction(SSEC)method for eliminating measurement errors.This method is based on the detections of error signal E(s)and output C(s)which generate an expected output R(s).In comparison with the conventional solutions which are based on detecting the expected output R(s)and output C(s)to obtain error signal E(s),the measurement errors are eliminated even the error might be at a significant level.Moreover,it is possible that the individual debugging by regulating the coefficient K for every member of the multiple objectives achieves the optimization of the open loop gain.Therefore,this simple method can be applied to the weak coupling and multiple objectives system,which is usually controlled by complex controller.The principle of eliminating measurement errors is derived analytically,and the advantages comparing with the conventional solutions are depicted.Based on the SSEC method analysis,an application of this method for an active power filter(APF)is investigated and the effectiveness and viability of the scheme are demonstrated through the simulation and experimental verifications.展开更多
This paper studies the nonstationary filtering problem of Markov jump system under <span style="white-space:nowrap;"><i>l</i><sub>2</sub> - <i>l</i><sub>...This paper studies the nonstationary filtering problem of Markov jump system under <span style="white-space:nowrap;"><i>l</i><sub>2</sub> - <i>l</i><sub>∞</sub> </span>performance. Due to the difference in propagation channels, signal strength and phase will inevitably change randomly and cause the waste of signals resources. In response to this problem, a channel fading model with multiplicative noise is introduced. And then a nonstationary filter, which receives signals more efficiently is designed. Meanwhile Lyapunov function is constructed for error analysis. Finally, the gain matrix for filtering is obtained by solving the matrix inequality, and the results showed that the nonstationary filter converges to the stable point more quickly than the traditional asynchronous filter, the stability of the designed filter is verified.展开更多
For the linear discrete time-invariant stochastic system with correlated noises, and with unknown model parameters and noise statistics, substituting the online consistent estimators of the model parameters and noise ...For the linear discrete time-invariant stochastic system with correlated noises, and with unknown model parameters and noise statistics, substituting the online consistent estimators of the model parameters and noise statistics into the optimal time-varying Riccati equation, a self-tuning Riccati equation is presented. By the dynamic variance error system analysis （DVESA） method, it is rigorously proved that the self-tuning Riccati equation converges to the optimal time-varying Riccati equation. Based on this, by the dynamic error system analysis （DESA） method, it is proved that the corresponding self-tuning Kalman filter converges to the optimal time-varying Kalman filter in a realization, so that it has asymptotic optimality. As an application to adaptive signal processing, a self-tuning Kalman signal filter with the self-tuning Riccati equation is presented. A simulation example shows the effectiveness.展开更多
For linear discrete time-invariant stochastic system with correlated noises,and with unknown state transition matrix and unknown noise statistics,substituting the online consistent estimators of the state transition m...For linear discrete time-invariant stochastic system with correlated noises,and with unknown state transition matrix and unknown noise statistics,substituting the online consistent estimators of the state transition matrix and noise statistics into steady-state optimal Riccati equation,a new self-tuning Riccati equation is presented.A dynamic variance error system analysis(DVESA)method is presented,which transforms the convergence problem of self-tuning Riccati equation into the stability problem of a time-varying Lyapunov equation.Two decision criterions of the stability for the Lyapunov equation are presented.Using the DVESA method and Kalman filtering stability theory,it proves that with probability 1,the solution of self-tuning Riccati equation converges to the solution of the steady-state optimal Riccati equation or time-varying optimal Riccati equation.The proposed method can be applied to design a new selftuning information fusion Kalman filter and will provide the theoretical basis for solving the convergence problem of self-tuning filters.A numerical simulation example shows the effectiveness of the proposed method.展开更多
基金supported by the National Natural Science Foundation of China(No.60874063)the Innovation Scientific Research Foundation for Graduate Students of Heilongjiang Province(No.YJSCX2008-018HLJ),and the Automatic Control Key Laboratory of Heilongjiang University
文摘For multisensor systems,when the model parameters and the noise variances are unknown,the consistent fused estimators of the model parameters and noise variances are obtained,based on the system identification algorithm,correlation method and least squares fusion criterion.Substituting these consistent estimators into the optimal weighted measurement fusion Kalman filter,a self-tuning weighted measurement fusion Kalman filter is presented.Using the dynamic error system analysis （DESA） method,the convergence of the self-tuning weighted measurement fusion Kalman filter is proved,i.e.,the self-tuning Kalman filter converges to the corresponding optimal Kalman filter in a realization.Therefore,the self-tuning weighted measurement fusion Kalman filter has asymptotic global optimality.One simulation example for a 4-sensor target tracking system verifies its effectiveness.
基金Supported by the National Natural Science Foundation of China (No.60874063)Science and Technology Research Foundation of Heilongjiang Education Department (No.11521214)Open Fund of Key Laboratory of Electronics Engineering, College of Heilongjiang Province (Heilongjiang University)
文摘For the multisensor system with correlated measurement noises and unknown noise statistics, based on the solution of the matrix equations for correlation function, the on-line estimators of the noise variances and cross-covariances is obtained. Further, a self-tuning weighted measurement fusion Kalman filter is presented, based on the Riccati equation. By the Dynamic Error System Analysis (DESA) method, it rigorously proved that the presented self-tuning weighted measurement fusion Kalman filter converges to the optimal weighted measurement fusion steady-state Kalman filter in a realization or with probability one, so that it has asymptotic global optimality. A simulation example for a target tracking system with 3-sensor shows that the presented self-tuning measurement fusion Kalman fuser converges to the optimal steady-state measurement fusion Kalman fuser.
文摘A self-tuning reaching law based sliding mode control(SMC)theory is proposed to stabilize the nonlinear continuous stirred tank reactor(CSTR).T-S fuzzy logic is used to build a global fuzzy state-space linear model.Combing the traits of SMC and CSTR,three fuzzy rules can meet the requirements of controlled system.The self-tuning switch control law which can drive the state variables to the sliding surface as soon as possible is designed to ensure the robustness of uncertain fuzzy system.Lyapunov equation is applied to proving the stability of the sliding surface.The simulations show that the proposed approach can achieve desired performance with less chattering problem.
基金supported by the National Natural Science Foundation of China(60874063)Science and Technology Research Foundation of Heilongjiang Education Department(11551355)Key Laboratory of Electronics Engineering,College of Heilongjiang Province(DZZD20105)
文摘For the multisensor linear discrete time-invariant stochastic systems with correlated noises and unknown noise statistics,an on-line noise statistics estimator is presented by using the correlation method.Substituting it into the steady-state Riccati equation,the self-tuning Riccati equation is obtained.Using the Kalman filtering method,based on the self-tuning Riccati equation,a self-tuning weighted measurement fusion white noise deconvolution estimator is presented.By the dynamic error system analysis（DESA） method,it is proved that the self-tuning fusion white noise deconvolution estimator converges to the optimal fusion steadystate white noise deconvolution estimator in a realization,so that it has the asymptotic global optimality.A simulation example for Bernoulli-Gaussian input white noise shows its effectiveness.
文摘This paper presents an efficient way to implement an interpolation filter in a 20bit ∑-△ DAC with an oversampling ratio of 128. A multistage structure is used to reduce the complexity of filter coefficients and the fi- nite word length effect. A novel method based on mixed-radix number representation is proposed to realize a poly- phase multiplier-free half-band subfilter with a high resolution. This approach reduces the complexity of the con- trol system and saves chip area dramatically. The IC is realized in a standard 0.13μm CMOS process and the inter- polation filter occupies less than 0.63mm^2 . This realization has desirable properties of regularity with simple hard- ware devices which are suitable for VLSI and can be applied to many other high resolution data converters.
文摘Dynamic load imposed on the bridge by mov- ing vehicle depends on several bridge-vehicle parameters with various uncertainties. In the present paper, particle filter technique based on conditional probability has been used to identify vehicle mass, suspension stiffness, and damping including tyre parameters from simulated bridge accelerations at different locations. A closed-form expres- sion is derived to generate independent response samples for the idealized bridge-vehicle coupled system consider- ing spatially non-homogeneous pavement unevenness. Thereafter, it is interfaced with the iterative process of particle filtering algorithm. The generated response sam- ples are contaminated by adding artificial noise in order to reflect field condition. The mean acceleration time history is utilized in particle filtering technique. The vehicle- imposed dynamic load is reconstructed with the identified parameters and compared with the simulated results. The present identification technique is examined in the presence of different levels of artificial noise with bridge response simulated at different locations. The effect of vehicle velocity, bridge surface roughness, and choice of prior probability density parameters on the efficiency of the method is discussed.
基金The MKE(Ministry of Knowledge Economy),Korea,under the ITRC(Information Technology Research Center)support program(NIPA-2013-H0301-13-2006)supervised by the NIPA(National IT Industry Promotion Agency)The National Research Foundation of Korea(NRF)grant funded by the Korea government(MEST)(2013-029812)The MKE(Ministry of Knowledge Economy),Korea,under the Human Resources Development Program for Convergence Robot Specialists support program supervised by the NIPA(National IT Industry Promotion Agency)(NIPA-2013-H1502-13-1001)
文摘In the field of mobile robotics,human tracking has emerged as an important objective for facilitating human-robot interaction.In this paper,we propose a particle-filter-based walking prediction model that will address an occlusion situation.Since the target being tracked is a human leg,a motion model for a leg is required.The validity of the proposed model is verified experimentally.
文摘This paper clarifies the steady-state properties and performance of an α-β filter for moving target tracking using both position and velocity measurements. We call this filter velocity measured α-β (VM-α-β) filter. We first derive the stability condition and steady-state predicted errors as fundamental properties of the VM-α-β filter. The optimal gains for representative motion models are then derived from the Kalman filter equations. Theoretical and numerical analyses verify that VM-α-β filters with these optimal gains realize more accurate tracking than conventional α-β filters when the filter gains are relatively large. Our study reveals the conditions under which the predicted errors of the VM-α-β filters are less than those of conventional α-β filters. Moreover, numerical simulations clarify that the variance of the tracking error of the VM-α-β filters is approximately 3/4 of that of the conventional α-β filters in realistic situations, even when the accuracy of the position/velocity measurements is the same.
文摘The conceptions of the knowledge screen generated by S-rough sets are given: f- screen and - screen , and then puts forward - filter theorem, - filter theorem of knowledge. At last, the applications of knowledge separation are given according to - screen and - screen.
基金the support provided by the Deanship of Scientific Research(DSR)at King Fahd University of Petroleum&Minerals(KFUPM)for funding this work through Project No.IN 141008
文摘Excellent drilling fluid techniques are one of the significant guaranteed measures to insure safety, qual- ity, efficiency, and speediness of drilling operations. Dril- ling fluids are generally discarded after the completion of drilling operations and become waste, which can have a large negative impact on the environment. Drilling mate- rials and additives together with drill cuttings, oil, and water constitute waste drilling fluids, which ultimately are dumped onto soil, surface water, groundwater, and air. Environmental pollution is found to be a serious threat while drilling complex wells or high-temperature deep wells as these types of wells involve the use of oil-based drilling fluid systems and high-performance water-based drilling fluid systems. The preservation of the environment on a global level is now important as various organizations have set up initiatives to drive the usage of toxic chemicals as drilling fluid additives. This paper presents an approach where grass is introduced as a sustainable drilling fluid additive with no environmental problems. Simple water- based drilling fluids were formulated using bentonite, powdered grass, and water to analyze the rheological and filtration characteristics of the new drilling fluid. A particle size distribution test was conducted to determine the par- ticle size of the grass sample by the sieve analysis method. Experiments were conducted on grass samples of 300, 90, and 35 μm to study the characteristics and behavior of the newly developed drilling fluid at room temperature. The results show that grass samples with varying particle sizes and concentrations may improve the viscosity, gel strength, and filtration of the bentonite drilling fluid. These obser- vations recommend the use of grass as a rheological modifier, filtration control agent, and pH control agent to substitute toxic materials from drilling fluids.
文摘DWDM technology is developing rapidly. Thin film narrow bandpass filter plays an important role in this field. This article presents some achievements in developing the DWDM narrow bandpass filters and also describes the results achieved by us.
基金supported by the National High-Tech R&D Program (863 Program) No. 2015AA01A705the National Natural Science Foundation of China under Grant No. 61572072+1 种基金the National Science, Technology Major Project No. 2015ZX03001041Fundamental Research Funds for the Central Universities No. FRF-TP-15-027A3
文摘A velocity determination algorithm of GNSS receiver for high speed and high acceleration carrier in motion is mainly discussed in this paper. For this algorithm, the Doppler frequency value is extracted from the satellite carrier tracking loop, and(α, β, γ) filter is adopted for smoothing, and least square is adopted to calculate the receiver speed and local clock drift. To get accurate determination value, a kind of fault detection and exclusion technology(FDE) is designed in this paper; the satellite Doppler frequency value with large error is detected and exclusion. Finally, the signal of GNSS signal simulator and actual navigational satellite signal are received for test, getting good velocity determination result.
基金supported by the National Natural Science Foundation of China(Grant No.60374026)the Science and Technology Research Foundation of Heilongjiang Education Department(11523037),Automation Control Key Laboratory of Heilongjiang University.
文摘An online noise variance estimator for multi-sensor systems with unknown noise variances is proposed by using the correlation method.Based on the Riccati equa-tion and optimal fusion rule weighted by scalars for state components,a self-tuning component decoupled informa-tion fusion Kalman filter is presented.It is proved that the filter converges to the optimal fusion Kalman filter in a realization by dynamic error system analysis method,so that it has asymptotic optimality.Its effectiveness is demon-strated by simulation for a tracking system with 3 sensors.
文摘This paper presents a video-tracking system composed of two cameras. One camera acts for producing an in-focus image of the object and the other one ensures an extended vision field under monitoring. Such a system scheme can achieve an excellent tracking performance,especially under various unfavorable conditions. A projection algorithm is used for the calculation of the displacement of the moving object. As a result, the computational cost is reduced greatly.In order that the tracking action of the system persists even if the object is sheltered or ns acceleration is larger than a specified threshold, a dedicated tracking algorithm on the basis of the α-β filtering is designed. Experiments show that the algorithm is efficient and the system works very well.
文摘In the step processing a digitalized signal,noises are generated by internal or external causes of the system.In order to eliminate these noises,various methods are researched.Among these noise elimination methods,Fourier fast transform(FFT)and short-time Fourier transform(STFT)are widely used.Because they are expressed as a fixed time-frequency domain,they have the disadvantage that the time information about the signal is unknown.In order to overcome these limitations,by using the wavelet transform that provides a variety of time-frequency resolution,multi-resolution analysis can be analysed and a varying noise depending on the time characteristics can be removed more efficiently.Therefore,in this paper,a denoising method of underwater vehicle using discrete wavelet transform(DWT)is proposed.
基金National Natural Science Foundation of China(No.61273172)
文摘This paper proposes a steady-state errors correction(SSEC)method for eliminating measurement errors.This method is based on the detections of error signal E(s)and output C(s)which generate an expected output R(s).In comparison with the conventional solutions which are based on detecting the expected output R(s)and output C(s)to obtain error signal E(s),the measurement errors are eliminated even the error might be at a significant level.Moreover,it is possible that the individual debugging by regulating the coefficient K for every member of the multiple objectives achieves the optimization of the open loop gain.Therefore,this simple method can be applied to the weak coupling and multiple objectives system,which is usually controlled by complex controller.The principle of eliminating measurement errors is derived analytically,and the advantages comparing with the conventional solutions are depicted.Based on the SSEC method analysis,an application of this method for an active power filter(APF)is investigated and the effectiveness and viability of the scheme are demonstrated through the simulation and experimental verifications.
文摘This paper studies the nonstationary filtering problem of Markov jump system under <span style="white-space:nowrap;"><i>l</i><sub>2</sub> - <i>l</i><sub>∞</sub> </span>performance. Due to the difference in propagation channels, signal strength and phase will inevitably change randomly and cause the waste of signals resources. In response to this problem, a channel fading model with multiplicative noise is introduced. And then a nonstationary filter, which receives signals more efficiently is designed. Meanwhile Lyapunov function is constructed for error analysis. Finally, the gain matrix for filtering is obtained by solving the matrix inequality, and the results showed that the nonstationary filter converges to the stable point more quickly than the traditional asynchronous filter, the stability of the designed filter is verified.
基金supported by the National Natural Science Foundation of China (No. 60874063)the Automatic Control Key Laboratory of Heilongjiang Universitythe Science and Technology Research Foundation of Heilongjiang Education Department (No. 11553101)
文摘For the linear discrete time-invariant stochastic system with correlated noises, and with unknown model parameters and noise statistics, substituting the online consistent estimators of the model parameters and noise statistics into the optimal time-varying Riccati equation, a self-tuning Riccati equation is presented. By the dynamic variance error system analysis （DVESA） method, it is rigorously proved that the self-tuning Riccati equation converges to the optimal time-varying Riccati equation. Based on this, by the dynamic error system analysis （DESA） method, it is proved that the corresponding self-tuning Kalman filter converges to the optimal time-varying Kalman filter in a realization, so that it has asymptotic optimality. As an application to adaptive signal processing, a self-tuning Kalman signal filter with the self-tuning Riccati equation is presented. A simulation example shows the effectiveness.
基金supported by the National Natural Science Foundation of China (Grant No.60874063).
文摘For linear discrete time-invariant stochastic system with correlated noises,and with unknown state transition matrix and unknown noise statistics,substituting the online consistent estimators of the state transition matrix and noise statistics into steady-state optimal Riccati equation,a new self-tuning Riccati equation is presented.A dynamic variance error system analysis(DVESA)method is presented,which transforms the convergence problem of self-tuning Riccati equation into the stability problem of a time-varying Lyapunov equation.Two decision criterions of the stability for the Lyapunov equation are presented.Using the DVESA method and Kalman filtering stability theory,it proves that with probability 1,the solution of self-tuning Riccati equation converges to the solution of the steady-state optimal Riccati equation or time-varying optimal Riccati equation.The proposed method can be applied to design a new selftuning information fusion Kalman filter and will provide the theoretical basis for solving the convergence problem of self-tuning filters.A numerical simulation example shows the effectiveness of the proposed method.
