基于T-S 模糊模型的网络控制系统非脆弱H∞ 跟踪控制

针对一类T-S 模糊模型描述的网络控制系统(NCSs) 非脆弱H_∞跟踪控制问题进行研究. 首先, 综合考虑网络中数据传输时滞和数据丢包的影响, 采用输入时滞法和并行分布补偿(PDC) 技术, 建立基于T-S 模糊模型的NCSs 状态跟踪误差模型; 然后, 利用Lyapunov 方法和改进的自由权矩阵方法, 基于线性矩阵不等式(LMI), 给出满足系统H_∞ 跟踪性能的条件, 并给出非脆弱模糊控制器设计方法; 最后, 通过仿真实例表明了该方法的有效性.     

不确定非线性网络化系统的鲁棒H_∞控制

用T-S(Takagi-Sugeno)模糊方法研究了带有参数不确定的非线性网络化系统的鲁棒控制.首先,考虑到诱导时延和数据丢包等网络因素的影响,基于事件驱动的保持器的更新序列建立闭环反馈系统的采样模型,并将其转化为状态中附加两个时滞变量的连续T-S模糊系统.然后,利用时滞系统方法,分析不确定闭环模糊系统的鲁棒H∞性能,并设计相应的鲁棒H∞模糊控制器.最后,仿真例子表明了方法的有效性.     

基于T-S模糊模型非线性网络控制系统改进H∞跟踪控制

研究一类非线性网络控制系统改进H∞跟踪控制问题, 该类网络控制系统中非线性被控对象和被跟踪对象分别采用Takagi-Sugeno(T-S)模糊模型和线性稳定参考模型描述. 首先通过综合考虑网络中的数据传输时滞和数据丢包影响, 采用输入时滞法和并行分布补偿技术, 建立基于零阶保持器刷新时刻的系统状态跟踪误差模型. 然后利用改进的自由权矩阵方法, 并结合Lyapunov直接法给出系统满足H∞跟踪性能的充分条件以及模糊控制器的设计方法. 最后仿真实例表明本文方法的有效性和相比已有方法的优越性.     

时滞系统基于观测器的H ∞模糊控制器设计

研究一类T-S模糊模型描述的非线性时滞系统的H∞控制问题.基于一种新的时滞独立稳定性准则,分别给出了经状态反馈和基于模糊观测器的输出反馈对系统进行H∞控制的方法.基于线性矩阵不等式的可解性,给出了H∞控制器存在的充分条件.仿真例子验证了所提出方法的有效性.     

基于模糊模型的时滞不确定系统的模糊H∞鲁棒反馈控制

讨论了一类具有状态和控制时滞的不确定非线性系统的模糊H∞状态反馈控制问题.采用具有时滞的不确定Takagi-Sugeno(T-S)模糊模型对非线性系统进行建模,提出了一套基于LMI的模糊鲁棒控制器的系统设计方法,给出了模糊H∞状态反馈控制器存在的充分条件,以保证闭环模糊系统渐近稳定并满足从干扰输入到控制输出的H∞范数界约束.示例仿真表明了该方法的有效性.     

双率采样系统的基于观测器的网络化H∞控制

研究一类带有网络传输时滞和丢包的双率采样系统的网络化H∞控制问题. 假设对象状态变量被分成两个分向量, 同一分向量的状态变量由同一类传感器以相同周期采样, 且两类传感器的采样频率不同. 采样后的分向量分别通过非理想网络传输到控制器端. 考虑到双率采样、网络传输时滞和丢包现象, 引入同步观测器来估计对象状态并设计基于估计状态的控制器来镇定双率采样系统. 基于这个思路, 将双率采样的网络化控制系统建模为带有两个时变时滞的连续系统. 利用Lyapunov-Krasovskii泛函方法, 以矩阵不等式形式给出该系统的稳定性判据和控制器设计方法. 最后, 通过数值例子验证所提方法的有效性.     

非线性系统广义模糊跟踪控制

研究一种给定 H∞ 模型参考跟踪特性的非线性系统的 T-S 广义模糊跟踪控制问题. 通过把一般的模糊模型等价变换到广义模糊模型, 引入了松弛变量, 并基于线性矩阵不等式 (LMI) 给出了新的 H∞ 跟踪控制器设计方法. 控制器参数在一组线性矩阵不等式中同时得到求解, 避免了原有方法分步求解的困难, 方法简单易行且具有鲁棒性. 两个算例表明了结论的有效性.     

一类非线性时滞互联系统模糊分散输出反馈控制

对于一类状态不可测非线性互联时滞系统,给出一种基于观测器的模糊分散输出反馈控制方法.首先采用模糊T-S模型对非线性互联时滞系统进行模糊建模,在此基础上给出了模糊分散观测器和基于观测器的模糊分散输出控制器的设计.应用李亚普诺夫函数法和线性矩阵不等式方法给出了模糊分散控制系统稳定的充分条件.仿真结果进一步验证了所提出的模糊分散控制方法的有效性.     

一类非线性系统的模糊可靠H_2/H_∞混合控制器设计的LMI方法

基于T-S模糊模型,利用线性矩阵不等式(LMI)方法,研究一类非线性系统的模糊可靠H2/H∞混合控制器设计问题.首先,分别以LMI形式给出了系统模糊可靠H2及H∞控制器存在的充分条件和控制器设计方法;然后.给出系统混合H2/H∞性能的可靠控制器设计方法,所设计的控制器使得故障闭环系统二次稳定,同时满足H∞性能,且优化系统的H2性能指标,最后,通过数值例子验证了结论的正确性和控制器设计方法的有效性.     

考虑随机时滞的非线性网控系统鲁棒L2-L∞控制

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.     

Output feedback LMI tracking control conditions with H∞ criterion for uncertain and disturbed T-S models

This work concerns the tracking problem of uncertain Takagi-Sugeno (T-S) continuous fuzzy model with external disturbances. The objective is to get a model reference based output feedback tracking control law. The control scheme is based on a PDC structure, a fuzzy observer and a H_∞ performance to attenuate the external disturbances. The stability of the whole closed-loop model is investigated using the well-known quadratic Lyapunov function. The key point of the proposed approaches is to achieve conditions under a LMI (linear matrix inequalities) formulation in the case of an uncertain and disturbed T-S fuzzy model. This formulation facilitates obtaining solutions through interior point optimization methods for some nonlinear output tracking control problems. Finally, a simulation is provided on the well-known inverted pendulum testbed to show the efficiency of the proposed approach.     

A new approach to robust and non-fragile H∞ control for uncertain fuzzy systems

This paper investigates the robust H_∞ control and non-fragile control problems for Takagi-Sugeno (T-S) fuzzy systems with linear fractional parametric uncertainties. The robust H_∞ control problem is to design a state feedback controller such that the robust stability and a prescribed H_∞ performance of the resulting closed-loop system is ensured. And the non-fragile H_∞ control problem is to design a state feedback controller with parameter uncertainties. Based on the linear matrix inequality (LMI) approach, new sufficient conditions for the solvability of the two problems are obtained. It is shown that the desired state feedback fuzzy controller can be constructed by solving a set of LMIs. Numerical examples are also provided to demonstrate the effectiveness of the proposed design method.     

State feedback tracking control for indirect field-oriented induction motor using fuzzy approach

This paper deals with the synthesis of fuzzy controller applied to the induction motor with a guaranteed model reference tracking performance. First, the Takagi-Sugeno (T-S) fuzzy model is used to approximate the nonlinear system in the synchronous d-q frame rotating with field-oriented control strategy. Then, a fuzzy state feedback controller is designed to reduce the tracking error by minimizing the disturbance level. The proposed controller is based on a T-S reference model in which the desired trajectory has been specified. The inaccessible rotor flux is estimated by a T-S fuzzy observer. The developed approach for the controller design is based on the synthesis of an augmented fuzzy model which regroups the model of induction machine, fuzzy observer, and reference model. The gains of the observer and controller are obtained by solving a set of linear matrix inequalities (LMIs). Finally, simulation and experimental results are given to show the performance of the observer-based tracking controller.     

New approaches to H∞ controller designs based on fuzzy observers for T-S fuzzy systems via LMI

The problems of relaxed quadratic stability conditions, fuzzy observer designs and H_∞ controller designs for T-S fuzzy systems have been studied. First new stability conditions are obtained by relaxing the stability conditions derived in previous papers. Secondly, new fuzzy observers based on the relaxed stability conditions for the T-S fuzzy systems have been proposed. Thirdly two sufficient LMI conditions, which guarantee the existence of the H_∞ controllers based on fuzzy observers for the T-S fuzzy systems have been proposed. The conditions are not only simple, but also consider the interactions among the fuzzy subsystems. Finally by some examples, using the LMI technique, we show that the regulators, the fuzzy observers and the H_∞ controller designs based on new observers for the T-S fuzzy systems are very practical and efficient.     

Delay-range-dependent robust stabilisation and H ∞ control for nonlinear uncertain stochastic fuzzy systems with mode-dependent time delays and Markovian jump parameters

This article focuses on the problems of robust stabilisation and H _∞ control for nonlinear uncertain stochastic systems with mode-dependent time delay and Markovian jump parameters represented by the Takagi–Sugeno (T-S) fuzzy model approach. The system under consideration involves parameter uncertainties, Itô-type stochastic disturbances, Markovian jump parameters and unknown nonlinear disturbances. The purpose is to design a state feedback controller such that the closed-loop system is robustly exponentially stable in the mean square and satisfies a prescribed H _∞ performance level. Novel delay-range-dependent conditions in the form of linear matrix inequalities (LMIs) are derived for the solvability of robust stabilisation and H _∞ control problem. A desired fuzzy controller can be constructed by solving a set solutions of LMIs and can be easily calculated by Matlab LMI control toolbox. Finally, a numerical example is presented to illustrate the proposed method.     

Robust H ∞ networked control for discrete-time fuzzy systems with state quantisation

The problem of robust H _∞ control for uncertain discrete-time Takagi and Sugeno (T-S) fuzzy networked control systems (NCSs) with state quantisation is investigated. A new model of network-based control with simultaneous consideration of network-induced delays and packet dropouts is proposed. By using a fuzzy Lyapunov–Krasovskii functional (LKF), we derive a less conservative delay-dependent stability condition for the closed-loop NCSs. Robust H _∞ fuzzy controller is developed for the asymptotical stabilisation of the NCSs. Since it is not expressed as strict LMI conditions, the cone complementary linearisation procedure is exploited to solve the nonconvex feasibility problem. A numerical example shows the feasibility applications of the proposed technique.     

H ∞ approach to T-S fuzzy controller for limiting reconstruction errors

In this article, the reconstruction error between a real system to be controlled and its Takagi–Sugeno (T-S) fuzzy model is considered in the context of control system design. Accordingly, we propose an H _∞ approach to an adaptive controller that consists of two parts: one is obtained by solving certain linear matrix inequalities (fixed part) and the other is acquired using a fuzzy approximator in which the related parameters are tuned by an adaptive law (variable part). The proposed controller can guarantee a convergent and uniformly bounded control state while maintaining the stability of all the signals involved.     

Delay-dependent robust stabilization and H ∞ control for uncertain stochastic T-S fuzzy systems with discrete interval and distributed time-varying delays

In this paper, delay-dependent robust stabilization and H∞ control for uncertain stochastic Takagi-Sugeno (T-S) fuzzy systems with discrete interval and distributed time-varying delays are discussed. The purpose of the robust stochastic stabilization problem is to design a memoryless state feedback controller such that the closed-loop system is mean-square asymptotically stable for all admissible uncertainties. In the robust H∞ control problem, in addition to the mean-square asymptotic stability requirement, a prescribed H∞ performance is required to be achieved. Sufficient conditions for the solvability of these problems are proposed in terms of a set of linear matrix inequalities (LMIs) and solving these LMIs, a desired controller can be obtained. Finally, two numerical examples are given to illustrate the effectiveness and less conservativeness of our results over the existing ones.