An observer-based adaptive fuzzy control is presented for a class of nonlinear systems with unknown time delays. The state observer is first designed, and then the controller is designed via the adaptive fuzzy control...An observer-based adaptive fuzzy control is presented for a class of nonlinear systems with unknown time delays. The state observer is first designed, and then the controller is designed via the adaptive fuzzy control method based on the observed states. Both the designed observer and controller are independent of time delays. Using an appropriate Lyapunov-Krasovskii functional, the uncertainty of the unknown time delay is compensated, and then the fuzzy logic system in Mamdani type is utilized to approximate the unknown nonlinear functions. Based on the Lyapunov stability theory, the constructed observer-based controller and the closed-loop system are proved to be asymptotically stable. The designed control law is independent of the time delays and has a simple form with only one adaptive parameter vector, which is to be updated on-line. Simulation results are presented to demonstrate the effectiveness of the proposed approach.展开更多
Security and reliability must be focused on control sys- tems firstly, and fault detection and diagnosis （FDD） is the main theory and technology. Now, there are many positive results in FDD for linear networked cont...Security and reliability must be focused on control sys- tems firstly, and fault detection and diagnosis （FDD） is the main theory and technology. Now, there are many positive results in FDD for linear networked control systems （LNCSs）, but nonlinear networked control systems （NNCSs） are less involved. Based on the T-S fuzzy-modeling theory, NNCSs are modeled and network random time-delays are changed into the unknown bounded uncertain part without changing its structure. Then a fuzzy state observer is designed and an observer-based fault detection approach for an NNCS is presented. The main results are given and the relative theories are proved in detail. Finally, some simulation results are given and demonstrate the proposed method is effective.展开更多
本文考虑了由Takagi-Sugeno(T-S)模糊模型描述的一类连续非线性网络控制系统基于观测器的鲁棒L_2–L_∞控制器设计问题.假设网络环境下存在的时变时滞具有特定的随机特性,通过引入一个伯努利随机变量表示时滞在不同区间上分布的概率,建...本文考虑了由Takagi-Sugeno(T-S)模糊模型描述的一类连续非线性网络控制系统基于观测器的鲁棒L_2–L_∞控制器设计问题.假设网络环境下存在的时变时滞具有特定的随机特性,通过引入一个伯努利随机变量表示时滞在不同区间上分布的概率,建立一个新的具有概率分布信息的系统模型.根据平行分布补偿法(parallel distribution compensation,PDC)和Lyapunov稳定性理论,建立基于T-S模糊模型的使系统均方指数稳定且满足L_2–L_∞的性能判据.并利用线性矩阵不等式(linear matrix inequality,LMI)技术同时得到状态观测器增益矩阵和控制器增益矩阵.最后,仿真结果验证了该方法的有效性.展开更多
This paper presents the construction of an active suspension control of a one-wheel car model using fuzzy reasoning and a disturbance observer. The one-wheel car model to be treated here can be approximately described...This paper presents the construction of an active suspension control of a one-wheel car model using fuzzy reasoning and a disturbance observer. The one-wheel car model to be treated here can be approximately described as a nonlinear two degrees of freedom system subject to excitation from a road profile. The active control is designed as the fuzzy control inferred by using single input rule modules fuzzy reasoning, and the active control force is released by actuating a pneumatic actuator. The excitation from the road profile is estimated by using a disturbance observer, and the estimate is denoted as one of the variables in the precondition part of the fuzzy control rules. A compensator is inserted to counter the performance degradation due to the delay of the pneumatic actuator. The experimental result indicates that the proposed active suspension system improves much the vibration suppression of the car model. Key words One-wheel car model - Active suspension system - Single input rule modules fuzzy reasoning - Pneumatic actuator - Disturbance observer Document code A CLC number TH16展开更多
This paper addresses the problem on sensor fault estimation and fault-tolerant control for a class of Takagi-Sugeno Markovian jump systems,which are subjected to sensor faults and partially unknown transition rates.Fi...This paper addresses the problem on sensor fault estimation and fault-tolerant control for a class of Takagi-Sugeno Markovian jump systems,which are subjected to sensor faults and partially unknown transition rates.First,the original plant is extended to a descriptor system,where the original states and the sensor faults are assembled into the new state vector.Then,a novel reduced- order observer is designed for the extended system to simultaneously estimate the immeasurable states and sensor faults.Second,by using the estimated states obtained from the designed observer,a state- feedback fault-tolerant control strategy is developed to make the resulting closed-loop control system stochastically stable.Based on linear matrix inequality technique,algorithms are presented to compute the observer gains and control gains.The effectiveness of the proposed observer and controller are validated by a numerical example and a compared study,respectively,and the simulation results reveal that the proposed method can successfully estimate the sensor faults and guarantee the stochastic stability of the resulting closed-loop system.展开更多
文摘An observer-based adaptive fuzzy control is presented for a class of nonlinear systems with unknown time delays. The state observer is first designed, and then the controller is designed via the adaptive fuzzy control method based on the observed states. Both the designed observer and controller are independent of time delays. Using an appropriate Lyapunov-Krasovskii functional, the uncertainty of the unknown time delay is compensated, and then the fuzzy logic system in Mamdani type is utilized to approximate the unknown nonlinear functions. Based on the Lyapunov stability theory, the constructed observer-based controller and the closed-loop system are proved to be asymptotically stable. The designed control law is independent of the time delays and has a simple form with only one adaptive parameter vector, which is to be updated on-line. Simulation results are presented to demonstrate the effectiveness of the proposed approach.
文摘Security and reliability must be focused on control sys- tems firstly, and fault detection and diagnosis （FDD） is the main theory and technology. Now, there are many positive results in FDD for linear networked control systems （LNCSs）, but nonlinear networked control systems （NNCSs） are less involved. Based on the T-S fuzzy-modeling theory, NNCSs are modeled and network random time-delays are changed into the unknown bounded uncertain part without changing its structure. Then a fuzzy state observer is designed and an observer-based fault detection approach for an NNCS is presented. The main results are given and the relative theories are proved in detail. Finally, some simulation results are given and demonstrate the proposed method is effective.
文摘本文考虑了由Takagi-Sugeno(T-S)模糊模型描述的一类连续非线性网络控制系统基于观测器的鲁棒L_2–L_∞控制器设计问题.假设网络环境下存在的时变时滞具有特定的随机特性,通过引入一个伯努利随机变量表示时滞在不同区间上分布的概率,建立一个新的具有概率分布信息的系统模型.根据平行分布补偿法(parallel distribution compensation,PDC)和Lyapunov稳定性理论,建立基于T-S模糊模型的使系统均方指数稳定且满足L_2–L_∞的性能判据.并利用线性矩阵不等式(linear matrix inequality,LMI)技术同时得到状态观测器增益矩阵和控制器增益矩阵.最后,仿真结果验证了该方法的有效性.
文摘This paper presents the construction of an active suspension control of a one-wheel car model using fuzzy reasoning and a disturbance observer. The one-wheel car model to be treated here can be approximately described as a nonlinear two degrees of freedom system subject to excitation from a road profile. The active control is designed as the fuzzy control inferred by using single input rule modules fuzzy reasoning, and the active control force is released by actuating a pneumatic actuator. The excitation from the road profile is estimated by using a disturbance observer, and the estimate is denoted as one of the variables in the precondition part of the fuzzy control rules. A compensator is inserted to counter the performance degradation due to the delay of the pneumatic actuator. The experimental result indicates that the proposed active suspension system improves much the vibration suppression of the car model. Key words One-wheel car model - Active suspension system - Single input rule modules fuzzy reasoning - Pneumatic actuator - Disturbance observer Document code A CLC number TH16
基金supported by the National Natural Science Foundation under Grant No.61803256Shanghai Sailing Plan under Grant No.17YF1407300in part by the Talent Program of Shanghai University of Engineering Science
文摘This paper addresses the problem on sensor fault estimation and fault-tolerant control for a class of Takagi-Sugeno Markovian jump systems,which are subjected to sensor faults and partially unknown transition rates.First,the original plant is extended to a descriptor system,where the original states and the sensor faults are assembled into the new state vector.Then,a novel reduced- order observer is designed for the extended system to simultaneously estimate the immeasurable states and sensor faults.Second,by using the estimated states obtained from the designed observer,a state- feedback fault-tolerant control strategy is developed to make the resulting closed-loop control system stochastically stable.Based on linear matrix inequality technique,algorithms are presented to compute the observer gains and control gains.The effectiveness of the proposed observer and controller are validated by a numerical example and a compared study,respectively,and the simulation results reveal that the proposed method can successfully estimate the sensor faults and guarantee the stochastic stability of the resulting closed-loop system.
