This paper considers the design problem of static output feedback H ∞ controllers for descriptor linear systems with linear matrix inequality (LMI) approach. Necessary and sufficient conditions for the existence of...This paper considers the design problem of static output feedback H ∞ controllers for descriptor linear systems with linear matrix inequality (LMI) approach. Necessary and sufficient conditions for the existence of a static output feedback H ∞ controller are given in terms of LMIs. Furthermore, the design method of H ∞ controllers is provided using the solutions to the LMIs.展开更多
Multimodal control for seismic responses of tall buildings is performed by using MTMDs. Installation and main parameters of MTMDs are described, equations of motion of the coupled system of tall buildings and MTMDs ar...Multimodal control for seismic responses of tall buildings is performed by using MTMDs. Installation and main parameters of MTMDs are described, equations of motion of the coupled system of tall buildings and MTMDs are built under earthquake excitations, and parametrical optimization for multimodal control is carried out under excitations of harmonic ground motion. An 11 story frame building controlled by MTMDs is simulated under the excitation of El Centro earthquake (1940, NS), and its displacement response at the top floor in the case of multimodal control is reduced by 20% more than the case of single modal control. Some conclusions are given as the MTMDs is an effective, reliable and practical passive measurement for controlling seismic responses of tall buildings and the multimodal control has better adaptability and reliability by comparison with the single modal control.展开更多
A sliding mode control methodology is presented for nonlinear systems represented by input output models, which does not depend on the state variables. There are two parts in the controller design, one is the sliding...A sliding mode control methodology is presented for nonlinear systems represented by input output models, which does not depend on the state variables. There are two parts in the controller design, one is the sliding controller design and the other is the design of linear feedback system. Simulation results demonstrate the validity of the control scheme.展开更多
The optimum theory and methods were adopted to design the laser beam riding guidance anti tank missile's control system in the short run. Through building the mathematical model of system, selecting a proper meth...The optimum theory and methods were adopted to design the laser beam riding guidance anti tank missile's control system in the short run. Through building the mathematical model of system, selecting a proper method and taking advantage of computer's high speed calculation and logic traits, an optimal controller was designed. Simulation results showed that the designed control system has fair performance and it satisfies the tactical and technical requirements. The results also demonstrate that by the combination of the optimizing methods and the computer the control system could be designed as soon as possible.展开更多
Backstepping method is applied to the problems of synchronization for chaotic systems. Synchronization controller is designed via selecting a series of Lyapunov functions on the basis of recursive idea. The method is ...Backstepping method is applied to the problems of synchronization for chaotic systems. Synchronization controller is designed via selecting a series of Lyapunov functions on the basis of recursive idea. The method is systematic and can deal with a class of chaotic system′s synchronization problems, which are important in safe communication with chaotic signal. Due to the nature of backstepping method, the designed controller possesses perfect robustness and adaptation. As an example, the controller based on backstepping method is employed to synchronize Lorenz system. The numerical simulation illustrates that the method is effective. Compared with the linear feedback synchronization controller, the control law can stabilize synchronization systems at a smaller synchronization error. Therefore the controller has a good performance.展开更多
In this paper, we study chaos control of the new 3D chaotic system. We use three feedback methods （the linear, speed, doubly-periodic function controller） to suppress the chaos to unstable equilibrium. As a result, ...In this paper, we study chaos control of the new 3D chaotic system. We use three feedback methods （the linear, speed, doubly-periodic function controller） to suppress the chaos to unstable equilibrium. As a result, some controllers are obtained. Moreover, numerical simulations are used to verify the effectiveness of the obtained controllers.展开更多
Based on the LaSalle invariance principle, we propose a simple adaptive-feedback for controlling the unified chaotic system. We show explicitly with numerical proofs that our method can easily achieve the control of c...Based on the LaSalle invariance principle, we propose a simple adaptive-feedback for controlling the unified chaotic system. We show explicitly with numerical proofs that our method can easily achieve the control of chaos in the unified chaotic system using only a single variable feedback. The present controller, to our knowledge, is the simplest control scheme for controlling a unified chaotic system.展开更多
Advanced feedback control for optimal operation of mineral grinding process is usually based on the model predictive control (MPC) dynamic optimization. Since the MPC does not handle disturbances directly by controlle...Advanced feedback control for optimal operation of mineral grinding process is usually based on the model predictive control (MPC) dynamic optimization. Since the MPC does not handle disturbances directly by controller design, it cannot achieve satisfactory effects in controlling complex grinding processes in the presence of strong disturbances and large uncertainties. In this paper, an improved disturbance observer (DOB) based MPC advanced feedback control is proposed to control the multivariable grinding operation. The improved DOB is based on the optimal achievable H 2 performance and can deal with disturbance observation for the nonminimum-phase delay systems. In this DOB-MPC advanced feedback control, the higher-level optimizer computes the optimal operation points by maximize the profit function and passes them to the MPC level. The MPC acts as a presetting controller and is employed to generate proper pre-setpoint for the lower-level basic feedback control system. The DOB acts as a compensator and improves the operation performance by dynamically compensating the setpoints for the basic control system according to the observed various disturbances and plant uncertainties. Several simulations are performed to demonstrate the proposed control method for grinding process operation.展开更多
In this work, the analysis of robust stability and design of robust H∞ output feedback controllers for a class of Lur'e systems with both time-delays and parameter uncertainties were studied. A robust H∞ output ...In this work, the analysis of robust stability and design of robust H∞ output feedback controllers for a class of Lur'e systems with both time-delays and parameter uncertainties were studied. A robust H∞ output feedback controller based on Linear Matrix Inequalities (LMIs) was developed to guarantee the robust stability and H∞ performance of the resultant closed-loop system. The presented design approach is based on the application of descriptor model transformation and Park's inequality for the bounding of cross terms and is expected to be less conservative compared to reported design methods. Finally, illustrative examples are advanced to demonstrate the superiority of the obtained method.展开更多
The performance of Smith prediction monitoring automatic gauge control(AGC) system is influenced by model mismatching greatly in strip rolling process. Aiming at this problem, a feedback-assisted iterative learning co...The performance of Smith prediction monitoring automatic gauge control(AGC) system is influenced by model mismatching greatly in strip rolling process. Aiming at this problem, a feedback-assisted iterative learning control strategy, which learned unknown modeling error by using previous control information repeatedly, was introduced into Smith prediction monitoring AGC system. Firstly, conventional Smith predictor and improved Smith predictor with PI-P controller were analyzed. Secondly, on the basis of establishing of feedback-assisted iterative learning control strategy for improved Smith predictor, process control signal update law and control error were deduced, then convergence condition of this strategy was put forward and proved. Finally, after modeling the automatic position control system, the PI-P Smith prediction monitoring AGC system with feedback-assisted iterative learning control was researched through simulation. Simulation results indicate that this system remains stable during model mismatching. The robustness and response of monitoring AGC is improved by development of feedback-assisted iterative learning control strategy for PI-P Smith predictor.展开更多
Abstract--In this paper, an adaptive neural network （NN） control approach is proposed for nonlinear pure-feedback sys- tems with time-varying full state constraints. The pure-feedback systems of this paper are assum...Abstract--In this paper, an adaptive neural network （NN） control approach is proposed for nonlinear pure-feedback sys- tems with time-varying full state constraints. The pure-feedback systems of this paper are assumed to possess nonlinear function uncertainties. By using the mean value theorem, pure-feedback systems can be transformed into strict feedback forms. For the newly generated systems, NNs are employed to approximate unknown items. Based on the adaptive control scheme and backstepping algorithm, an intelligent controller is designed. At the same time, time-varying Barrier Lyapunov functions （BLFs） with error variables are adopted to avoid violating full state constraints in every step of the backstepping design. All closed- loop signals are uniformly ultimately bounded and the output tracking error converges to the neighborhood of zero, which can be verified by using the Lyapunov stability theorem. Two simulation examples reveal the performance of the adaptive NN control approach. Index TermsmAdaptive control, neural networks （NNs）, non- linear pure-feedback systems, time-varying constraints.展开更多
文摘This paper considers the design problem of static output feedback H ∞ controllers for descriptor linear systems with linear matrix inequality (LMI) approach. Necessary and sufficient conditions for the existence of a static output feedback H ∞ controller are given in terms of LMIs. Furthermore, the design method of H ∞ controllers is provided using the solutions to the LMIs.
文摘Multimodal control for seismic responses of tall buildings is performed by using MTMDs. Installation and main parameters of MTMDs are described, equations of motion of the coupled system of tall buildings and MTMDs are built under earthquake excitations, and parametrical optimization for multimodal control is carried out under excitations of harmonic ground motion. An 11 story frame building controlled by MTMDs is simulated under the excitation of El Centro earthquake (1940, NS), and its displacement response at the top floor in the case of multimodal control is reduced by 20% more than the case of single modal control. Some conclusions are given as the MTMDs is an effective, reliable and practical passive measurement for controlling seismic responses of tall buildings and the multimodal control has better adaptability and reliability by comparison with the single modal control.
文摘A sliding mode control methodology is presented for nonlinear systems represented by input output models, which does not depend on the state variables. There are two parts in the controller design, one is the sliding controller design and the other is the design of linear feedback system. Simulation results demonstrate the validity of the control scheme.
文摘The optimum theory and methods were adopted to design the laser beam riding guidance anti tank missile's control system in the short run. Through building the mathematical model of system, selecting a proper method and taking advantage of computer's high speed calculation and logic traits, an optimal controller was designed. Simulation results showed that the designed control system has fair performance and it satisfies the tactical and technical requirements. The results also demonstrate that by the combination of the optimizing methods and the computer the control system could be designed as soon as possible.
文摘Backstepping method is applied to the problems of synchronization for chaotic systems. Synchronization controller is designed via selecting a series of Lyapunov functions on the basis of recursive idea. The method is systematic and can deal with a class of chaotic system′s synchronization problems, which are important in safe communication with chaotic signal. Due to the nature of backstepping method, the designed controller possesses perfect robustness and adaptation. As an example, the controller based on backstepping method is employed to synchronize Lorenz system. The numerical simulation illustrates that the method is effective. Compared with the linear feedback synchronization controller, the control law can stabilize synchronization systems at a smaller synchronization error. Therefore the controller has a good performance.
基金The project supported by Natural Science Foundations of Zhejiang Province of China under Grant No.Y604056the Doctoral Foundation of Ningbo City under Grant No.2005A61030+1 种基金National Natural Science Foundation of China under Grant No.10401039National Key Basic Research Program of China under Grant No.2004CB318000,and the NDEF,CAS
文摘In this paper, we study chaos control of the new 3D chaotic system. We use three feedback methods （the linear, speed, doubly-periodic function controller） to suppress the chaos to unstable equilibrium. As a result, some controllers are obtained. Moreover, numerical simulations are used to verify the effectiveness of the obtained controllers.
文摘Based on the LaSalle invariance principle, we propose a simple adaptive-feedback for controlling the unified chaotic system. We show explicitly with numerical proofs that our method can easily achieve the control of chaos in the unified chaotic system using only a single variable feedback. The present controller, to our knowledge, is the simplest control scheme for controlling a unified chaotic system.
基金Supported by the National Natural Science Foundation of China (61104084, 61290323)the Guangdong Education University-Industry Cooperation Projects (2010B090400410)
文摘Advanced feedback control for optimal operation of mineral grinding process is usually based on the model predictive control (MPC) dynamic optimization. Since the MPC does not handle disturbances directly by controller design, it cannot achieve satisfactory effects in controlling complex grinding processes in the presence of strong disturbances and large uncertainties. In this paper, an improved disturbance observer (DOB) based MPC advanced feedback control is proposed to control the multivariable grinding operation. The improved DOB is based on the optimal achievable H 2 performance and can deal with disturbance observation for the nonminimum-phase delay systems. In this DOB-MPC advanced feedback control, the higher-level optimizer computes the optimal operation points by maximize the profit function and passes them to the MPC level. The MPC acts as a presetting controller and is employed to generate proper pre-setpoint for the lower-level basic feedback control system. The DOB acts as a compensator and improves the operation performance by dynamically compensating the setpoints for the basic control system according to the observed various disturbances and plant uncertainties. Several simulations are performed to demonstrate the proposed control method for grinding process operation.
基金Project supported by the National Outstanding Young Science Foundation of China (No. 60025308)Teach and Research Award Program for Outstanding Young Teachers in Higher Education Institutions of Ministry of Education, China
文摘In this work, the analysis of robust stability and design of robust H∞ output feedback controllers for a class of Lur'e systems with both time-delays and parameter uncertainties were studied. A robust H∞ output feedback controller based on Linear Matrix Inequalities (LMIs) was developed to guarantee the robust stability and H∞ performance of the resultant closed-loop system. The presented design approach is based on the application of descriptor model transformation and Park's inequality for the bounding of cross terms and is expected to be less conservative compared to reported design methods. Finally, illustrative examples are advanced to demonstrate the superiority of the obtained method.
基金Project(51074051)supported by the National Natural Science Foundation of China
文摘The performance of Smith prediction monitoring automatic gauge control(AGC) system is influenced by model mismatching greatly in strip rolling process. Aiming at this problem, a feedback-assisted iterative learning control strategy, which learned unknown modeling error by using previous control information repeatedly, was introduced into Smith prediction monitoring AGC system. Firstly, conventional Smith predictor and improved Smith predictor with PI-P controller were analyzed. Secondly, on the basis of establishing of feedback-assisted iterative learning control strategy for improved Smith predictor, process control signal update law and control error were deduced, then convergence condition of this strategy was put forward and proved. Finally, after modeling the automatic position control system, the PI-P Smith prediction monitoring AGC system with feedback-assisted iterative learning control was researched through simulation. Simulation results indicate that this system remains stable during model mismatching. The robustness and response of monitoring AGC is improved by development of feedback-assisted iterative learning control strategy for PI-P Smith predictor.
基金supported in part by the National Natural Science Foundation of China(61622303,61603164,61773188)the Program for Liaoning Innovative Research Team in University(LT2016006)+1 种基金the Fundamental Research Funds for the Universities of Liaoning Province(JZL201715402)the Program for Distinguished Professor of Liaoning Province
文摘Abstract--In this paper, an adaptive neural network （NN） control approach is proposed for nonlinear pure-feedback sys- tems with time-varying full state constraints. The pure-feedback systems of this paper are assumed to possess nonlinear function uncertainties. By using the mean value theorem, pure-feedback systems can be transformed into strict feedback forms. For the newly generated systems, NNs are employed to approximate unknown items. Based on the adaptive control scheme and backstepping algorithm, an intelligent controller is designed. At the same time, time-varying Barrier Lyapunov functions （BLFs） with error variables are adopted to avoid violating full state constraints in every step of the backstepping design. All closed- loop signals are uniformly ultimately bounded and the output tracking error converges to the neighborhood of zero, which can be verified by using the Lyapunov stability theorem. Two simulation examples reveal the performance of the adaptive NN control approach. Index TermsmAdaptive control, neural networks （NNs）, non- linear pure-feedback systems, time-varying constraints.
