基于观测器的一类模糊时滞系统的容错控制

针对一类带有传感器故障的模糊时滞系统,提出了一种实现对系统的状态和传感器故障估计的观测嚣设计方法.在此基础上,给出了模糊容错控制方法及保证模糊控制系统的渐近稳定充分条件.应用广义Lyapunov函数和线性矩阵不等式方法,证明了模糊闭环时滞系统的渐近稳定性.仿真结果进一步验证了所提出的方法和条件的有效性.     

非线性网络控制系统的保性能控制

针对网络诱导时延小于一个采样周期的非线性网络控制系统,研究了系统的稳定性和保性能控制问题.对于T-S模糊模型描述的非线性被控对象,将时延的不确定性转化为系统参数的不确定性,从而将这一类非线性网络控制系统建模为具有参数不确定性的离散T-S模糊模型.基于建立的模型,提出了存在稳定保性能控制器的充分条件,并得出了相应的线性矩阵不等式(LMI)形式.最后通过对永磁同步电动机混沌系统进行控制和仿真研究,验证了所提出方法的有效性.     

一类模糊T-S模型互联系统的自适应容错跟踪控制

针对一类带有执行器故障的T-S模糊互联的容错跟踪控制问题,提出了一种模糊自适应容错控制器。该控制器由一个模糊控制器和一个自适应控制器组成,模糊控制器能够保证系统没有故障时闭环系统渐近稳定,而自适应控制器能够补偿系统的执行器故障。所提出的容错控制方法不但使得闭环系统渐近稳定、系统的输出渐近跟踪给定的参考信号,并获得H∞控制性能。最后应用Lyapunov函数和线性矩阵不等式的方法,给出和证明了带有执行器故障的T-S模糊互联系统的稳定的充分条件。仿真结果进一步验证了所提出方法的有效性。     

一类基于模糊T-S模型的有执行器故障的自适应容错跟踪控制

研究了一类带有执行器故障的T-S模糊系统的容错跟踪控制问题。设计中,把模糊控制与自适应控制相结合,提出了一种新的容错控制方法。该控制器由正常控制器和一个自适应控制器组成,能够使得闭环系统稳定,故障状态模型渐近跟踪正常模型,并获得优化的控制性能。应用Lyapunov函数和线性矩阵不等式方法,给出和证明了带有执行器故障的T-S模糊系统的稳定的充分条件。仿真结果进一步验证了所提出的方法的有效性。     

基于观测器的一类时滞不确定非线性离散系统的鲁棒模糊控制

讨论一类基于Takagi-Sugeno(T-S)模糊模型的具有时滞的不确定非线性离散系统的模糊鲁棒控制问题。在系统状态不可测的情况下。设计模糊观测器。利用LMI方法，得到模糊控制系统鲁棒稳定的充分条件。     

一类模糊互联系统的新时滞依赖稳定性条件

针对一类连续模糊定常时滞互联系统,提出了一种模糊分散控制器的控制方法,给出了新的时滞依赖稳定性条件.应用Lyapunov函数法,自由权重矩阵,及线性矩阵不等式(LMIs)方法证明了模糊分散控制系统稳定.仿真结果进一步验证了所提出模糊分散控制方法的有效性.     

一类随机时延网络控制系统的神经网络自适应容错控制

针对一类随机时延网络控制系统,提出一种基于RBF神经网络自适应动态补偿的容错控制策略.该方法通过在线估计时延将系统建模为随机切换系统,并在模型参考自适应方法的基础上设计RBF神经网络动态补偿容错控制器,利用Lyapunov稳定性理论给出神经网络补偿器的在线权值学习算法,以保证网络控制系统在故障情况下的跟踪性能和状态一致最终有界稳定.最后通过仿真验证了该方法的有效性.     

非仿射高阶关联大系统的分散模糊输出反馈控制

针对一类仅子系统输出变量可测的非仿射不确定非线性关联大系统,考虑其关联项是关于系统状态的普通高阶多项式,在无须严格正实(SPR)的条件下采用Leunberger观测器观测未知状态向量,结合模糊系统的万能逼近原理,监督控制技术和自适应控制技术,借助反证法提出一种新的分散自适应模糊输出反馈控制方案,该方案不仅取消了逼近误差平方可积的假设条件,而且控制增益隐含数一阶导数的上界是更具一般性的未知非线性函数,基于Lyapunov稳定理论分析证明了闭环系统的全局稳定性,跟踪误差收敛到零,仿真结果表明所提控制方案的有效性.     

模糊输入时滞系统的输出反馈控制及稳定性分析

针对一类状态不可测的模糊输入时滞系统,应用平行分布补偿算法(PDC),设计了模糊观测器,提出了基于模糊观测器的输出反馈控制方法,给出了保证模糊时滞系统渐近稳定的新的充分条件.应用广义Lyapunov函数和线性矩阵不等式方法,证明了模糊输入时滞系统的渐近稳定性,同时给出了控制和观测增益矩阵的分离设计算法.仿真结果进一步验证了所提出的方法和条件的有效性.     

一类非线性系统的输出反馈控制及全局渐近稳定性研究

考虑不可测状态是非线性的非严格三角形非线性系统的全局渐近稳定性问题.提出了一种新的反馈控制设计方法,构造一个线性动态输出补偿器,并全局稳定所控制的非线性系统.     

Fuzzy Impulsive Control and Synchronization of General Chaotic System

In this paper, by utilizing impulsive control theory and T-S fuzzy model, the fuzzy impulsive control and synchronization of general chaotic system are proposed. Some less conservative and more general conditions are obtained to guarantee the globally asymptotical stability for the impulsive control and synchronization of general chaotic system based on T-S fuzzy model. Moreover, some criteria of globally exponential stability of chaotic system are also derived. Finally, some numerical simulations are given to demonstrate the effectiveness of the proposed control method.     

基于T-S模型的Lurie混沌系统的模糊控制

针对Lurie混沌控制系统,进行了T-S模糊建模和模糊控制器设计,从而实现了Lurie混沌系统的稳定.在用T-S模糊模型精确重构Lurie系统结构的基础上,利用反馈同步思想,基于并行分布补偿(PDC)技术,得到了简单且易实现的控制器.仿真结果验证了该控制方法的有效性.     

基于模糊双线性模型的非线性系统的跟踪控制

研究一种基于T-S模糊双线性系统的跟踪控制器设计及稳定性分析.使用分布并行补偿法(PDC)设计了模糊控制器,得到模糊双线性系统跟踪控制渐近稳定的充分条件,仿真结果验证了该方法改进了闭环系统的性能.     

Indirect adaptive fuzzy observer and controller design based on interval type-2 T-S fuzzy model

This paper presents the design scheme of the indirect adaptive fuzzy observer and controller based on the interval type-2 (IT2) T-S fuzzy model. The nonlinear systems can be well approximated by IT2 T-S fuzzy model, in which the fuzzy rules’ antecedents are interval type-2 fuzzy sets and consequents are linear state equations. The proposed IT2 T-S fuzzy model is a combination of IT2 fuzzy system and T-S fuzzy model, and also inherits the benefits of type-2 fuzzy logic systems, which is able to directly handle uncertainties and can minimize the effects of uncertainties in rule-based fuzzy system. These characteristics can improve the accuracy of the system modeling and reduce the number of system rules. The proposed method using feedback control, adaptive laws, and on-line object parameters are adjusted to ensure observation error bounded. In addition, using Lyapunov synthesis approach and Lipschitz condition, the stability analysis is conducted. The simulation results show that the proposed method can handle unpredicted disturbance and data uncertainties very well in advantage of the effectiveness of observation and control.     

Trajectory stabilization of a model car via fuzzy control

This paper deals with trajectory stabilization of a computer simulated model car via fuzzy control. Stability conditions of fuzzy systems are given in accordance with the definition of stability in the sense of Lyapunov. First, we approximate a computer simulated model car, whose dynamics is nonlinear, by T-S (Takagi and Sugeno) fuzzy model. Fuzzy control rules, which guarantee stability of the control system under a condition, are derived from the approximated fuzzy model. The simulation results show that the fuzzy control rules effectively realize trajectory stabilization of the model car along a given reference trajectory from all initial positions under a condition and the dynamics of the approximated fuzzy model agrees well with that of the model car.     

模糊不确定时滞系统的保成本控制

讨论了基于T-S模型的不确定时滞系统的保成本控制问题.文章采用并行补偿状态反馈控制方法和时滞相关稳定性分析方法,通过引入一个带调节因子的Lyapunov-Krasovskii泛函,利用线性矩阵不等式的形式给出了状态反馈控制器存在的充分条件.当调节因子取不同值时,最小保成本值和反馈增益也是不同的,不同的反馈增益导致不同的动态性能,因此,可以通过选取合适的调节因子来优化闭环系统的动态性能. 最小保成本值可以看作调节因子的函数,因此,可以通过求解一个凸优化问题来求得最小的保成本值和最优的调节因子,文章给出了一个求解最小保成本值的算法.并利用仿真示例验证了所给方法的有效性.     

Reliable control for nonlinear systems with stochastic actuators fault and random delays through a T-S fuzzy model approach

This paper considers the reliable control design for T-S fuzzy systems with probabilistic actuators faults and random time-varying delays. The faults of each actuator occurs randomly and its failure rates are governed by a set of unrelated random variables satisfying certain probabilistic distribution. In terms of the probabilistic failures of each actuator and time-varying random delays, new fault model is proposed. Based on the new fuzzy model, reliable controller is designed and sufficient conditions for the exponentially mean square stability (EMSS) of T-S fuzzy systems are derived by using Lyapunov functional method and linear matrix inequality (LMI) technique. It should be noted that the obtained criteria depend on not only the size of the delay, but also the probability distribution of it. Finally, a numerical example is given to show the effectiveness of the proposed method.     

Development of stability research on Takagi-Sugeno fuzzy control systems and approximation of the necessary and sufficient conditions

The controller’s design and analysis based on Takagi-Sugeno (T-S) models play important roles in the research of fuzzy control. When fuzzy control is being widely applied, the stability research on T-S fuzzy control supports the applications on the theoretical standpoint. The development of the stability research on T-S fuzzy control is surveyed in this paper. For the Lyapunov functions, this paper considers common quadratic Lyapunov functions, piecewise quadratic Lyapunov functions, fuzzy Lyapunov functions, nonquadratic Lyapunov functions and homogenously polynomially parameterized Lyapunov functions. For the control laws, this paper considers parallelly distributed compensation, non-parallel distributed compensation laws and homogenously polynomially parameterized control laws. By extensively applying the Pólya’s theorem and the techniques for homogenous polynomials, the stability conditions are gradually developed towards necessary and sufficient. It is very important to recognize and master this development in order to further study fuzzy control and the related control theories.     

T-S模糊系统的脉冲稳定性

针对模糊控制系统提出了一种新的稳定性设计方法.该方法在传统T-S模型的局部子系统中引入脉冲控制项,构造了具有脉冲影响的模糊控制系统.然后,通过去模糊化技术,把具有脉冲影响的模糊系统转化为脉冲微分系统.这样,借助脉冲微分方程的比较原理和线性矩阵不等式技术,给出了模糊系统的脉冲稳定的充分条件.从而建立了模糊系统的简单脉冲控制策略.     

布尔代数的直觉T-S模糊子代数及理想

在布尔代数中引入了的直觉T-S模糊子代数和直觉T-S模糊理想的概念,给出了布尔代数的直觉T-S模糊子代数的两个等价定义,进一步讨论了它们的性质.证明了布尔代数的两个直觉T-S模糊子代数(理想)的模交与直积也是直觉T-S模糊子代数(理想).