不确定非线性时滞系统的非脆弱保成本控制

研究了一类具有状态时滞的不确定非线性系统的非脆弱保成本控制问题。通过利用Lyapunov稳定性理论和线性矩阵不等式方法,设计非脆弱保成本控制律,使得闭环系统渐近稳定,并且系统的性能指标不超过某个确定的上界。通过求解一个具有线性矩阵不等式约束的凸优化问题来设计最优非脆弱保成本控制器,以使得闭环不确定系统的性能指标最小化。仿真结果验证了该控制算法的有效性。     

非线性不确定系统的直接自适应输出反馈模糊控制

针对一类单输入单输出非线性不确定系统，基于状态观测器并结合自适应模糊系统和滑模控制，提出一种稳定的直接自适应模糊输出反馈控制算法。该算法不需要系统状态可测的条件，并能保证闭环系统稳定。仿真结果表明了该方法的有效性。     

结构不确定广义系统的鲁棒动态补偿器

对给定的不确定模式，得出了为保证广义闭环系统Ｈ稳定（或Ｄ稳定）动态补偿器所能容许的不确定上界。     

多变量非线性系统的间接模糊输出反馈自适应控制

针对一类多输入多输出非线性不确定系统，提出一种基于观测器的模糊间接自适应控制方法，并基于李亚普诺夫函数方法，导出了输出反馈控制律以及参数的自适应律，证明了整个控制方案不但能保证闭环系统稳定，而且取得了良好的跟踪控制性能。     

非线性系统的直接自适应输出反馈监督模糊控制

针对一类单输入单输出非线性不确定系统，提出一种稳定的直接自适应模糊输出反馈监督控制算法，该算法不需要系统的状态完全可测的假设条件，监督控制不仅迫使系统的状态在指定的集合内，而且当模糊自适应控制处于良好的工作状态时，监督控制可以关闭，证明了整个模糊自适应输出反馈控制算法可以保证闭环系统稳定。     

不确定离散时滞系统具有H ∞干扰抑制的保成本控制

针对一类用矩阵凸多面体形式的不确定线性离散时滞系统，提出一种通过无记忆状态反馈实现的具有H∞干扰抑制的保成本控制。当对象存在不确定性以及外部干扰统计特性未知时，该控制器能保证闭环系统稳定和一定的线性二次型性能指标上界，同时具有H∞范数下的干扰抑制作用。基于Lyapunov稳定性理论，控制器设计可转化为线性矩阵不等式的可解性问题。数值仿真表明，该控制器实际是对最优保成本上界和干扰抑制能力的一种折衷。     

一类非线性系统的自适应模型控制

对一类非线性不确定连续系统，提出了一种新的自适应控制方法。此方法用Ｔ－Ｓ模糊系统对未知函数进行逼近，引入Ｈ＾∞控制减弱外部干扰及逼近误差对输出跟踪误差的影响，证明了该方法可保证闭环系统稳定。仿真结果验证了此算法的有效性。     

广义不确定系统稳定鲁棒控制

利用李雅普诺夫稳定理论和矩阵范数性质研究了广义不确定系统的稳定鲁棒控 制问题.在不同情况下,分别给出了保证闭环不确定系统渐进稳定的两类稳定鲁棒控制:状态 反馈、正常动态补偿器的设计方法,得到了鲁棒稳定控制的不确定量的范数界,而且提出了在 多个稳定鲁棒控制器中寻找具有最大的不确定量范数界的控制器的方案.     

线性不确定奇异摄动系统的稳定控制鲁棒界

对于具有不确定量的奇异摄动系统，利用Lyapunov稳定性理论研究其稳定鲁棒控制问题。在一定条件下得到了任一理想奇异摄动系统的稳定鲁棒控制，也是不确定奇异摄动系统具有一定鲁棒界的稳定控制。给出了闭环奇异摄动系统渐近稳定的条件，讨论了鲁棒界及其变化范围。     

污水处理系统的鲁棒保成本控制

针对采用活性污泥法的污水处理系统,研究其鲁棒保成本控制问题。根据活性污泥法污水处理过程的特点,建立范数有界的不确定系统模型;利用Lyapunov稳定性理论和线性矩阵不等式方法,设计鲁棒保成本状态反馈控制律,使得闭环系统鲁棒渐近稳定,并且系统的性能指标不超过某个确定的上界。以某污水处理厂的污水处理系统为例,应用所设计的控制器进行仿真研究,结果表明:所设计控制算法是有效的。     

Robust guaranteed cost control of uncertain fuzzy systems under time-varying sampling

In practice, the system is often modeled as a continuous-time fuzzy system, while the control input is applied only at discrete instants. This system is called a sampled-data control system. In this paper, robust guaranteed cost control for uncertain sampled-data fuzzy systems is discussed. A guaranteed cost control where a quadratic cost function is bounded by a certain scalar, not only stabilizes a system but also considers a control performance. A typical sampled-data control is the zero-order input, which can be represented as a piecewise-continuous delay. Here we take a delay system approach to the sampled-data guaranteed cost control problem. The closed-loop system with a sampled-data state feedback controller becomes a system with time-varying delay. First, guaranteed cost control performance conditions for the closed-loop system are given in terms of linear matrix inequalities (LMIs). Such conditions are derived by using Leibniz–Newton formula and free weighting matrix method for fuzzy systems under the assumption that sampling time is not greater than some prescribed scalar. Then, a design method of robust guaranteed cost state feedback controller for uncertain sampled-data fuzzy systems is proposed. Examples are given to illustrate our robust sampled-data guaranteed cost control design.     

Fuzzy guaranteed cost control for nonlinear systems with time-varying delay

This paper focuses on the problem of guaranteed cost control for Takagi-Sugeno (T-S) fuzzy systems with time-varying delayed state. A linear quadratic cost function is considered as a performance index of the closed-loop fuzzy system. Then, the guaranteed cost control of the closed-loop fuzzy system is discussed, and the sufficient conditions are provided for the construction of a guaranteed cost controller via state feedback and observer-based output feedback. When these conditions, which are given in terms of the feasibility of linear matrix inequalities (LMIs), are satisfied, the designed state feedback controller and observer-based controller gain matrices can be obtained via a convex optimization problem. Two illustrative examples are provided to demonstrate the effectiveness of the approaches proposed in this paper.     

参数不确定T-S模糊交联系统的分散保成本控制

研究了参数不确定T-S模糊交联系统的分散保成本控制问题.对于给定系统所容许的所有不确定参数,设计了分散状态反馈保成本控制器,使得闭环系统不仅渐近稳定而且具有适当的性能指标上界.基于线性矩阵不等式(LM I)处理方法,给出了分散控制器存在的充分条件.仿真算例表明了所给方法的简易、有效.     

Optimal guaranteed cost control for an uncertain discrete T-S fuzzy system with time-delay

This paper considers the guaranteed cost control problem for a class of uncertain discrete T-S fuzzy systems with time delay and a given quadratic cost function. Sufficient conditions for the existence of such controllers are derived based on the linear matrix inequalities （LMI） approach by constructing a specific nonquadratic Lyapunov-Krasovskii functional and a nonlinear PDC-like control law. A convex optimization problem is also formulated to select the optimal guaranteed cost controller that minimizes the upper bound of the closed-loop cost function. Finally, numerical examples are presented to demonstrate the effectiveness of the proposed approaches.     

基于T-S模型的非线性时滞系统非脆弱保性能模糊控制

针对一类用T-S模糊模型描述的非线性时滞系统,采用状态反馈的并行分布补偿方法,研究其保守性较小的非脆弱保性能模糊控制问题,使闭环系统在控制器存在加性摄动的情况下,其闭环性能指标值低于确定的上界.利用线性矩阵不等式处理方法,导出了非脆弱保性能模糊控制律的存在条件,通过建立和求解一个线性矩阵不等式问题,给出了非脆弱保性能模糊控制律的设计方法.仿真结果表明了所提出方法的有效性.     

不确定非线性系统的鲁棒耗散性与保性能控制

考虑了不确定仿射非线性系统的鲁棒耗散性与保性能控制问题,不确定性范数有界,不满足匹配条件.基于HJI不等式,设计了状态反馈控制器.当扰动存在时,控制器能使系统达到耗散,当扰动为零时,所设计的控制器使系统对于给定的性能函数具有上界,最后研究了不确定线性系统的保性能与耗散性控制情形.     

Reliable LQ fuzzy control for nonlinear discrete-time systems via LMIs.

This paper studies reliable linear quadratic (LQ) fuzzy regulator problem for nonlinear discrete-time systems with actuator faults. The Takagi and Sugeno fuzzy model is employed to represent a nonlinear system. A sufficient condition expressed in linear matrix inequality (LMI) terms for the existence of reliable guaranteed cost (GC) fuzzy controllers is obtained. The fuzzy controller directly obtained from the LMI solutions can guarantee the stability of the closed-loop overall fuzzy system, while provide a guaranteed cost on the quadratic cost function of the system in the normal and actuator fault cases. Furthermore, an optimal reliable GC fuzzy controller in the sense of minimizing a bound on the worst or nominal case guaranteed cost is also given by means of an LMI optimization procedure. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed method.     

Intelligent digital redesign for nonlinear systems using a guaranteed cost control method

In this paper, a novel intelligent digital redesign (IDR) technique using the guaranteed cost control method is proposed for nonlinear systems which can be represented by a Takagi-Sugeno (T-S) fuzzy model. The IDR technique, which is one of the sampled-data fuzzy controller design methods, guarantees not only the stability condition of the sampled-data closed-loop system with the sampleddata fuzzy controller and the state-matching error is presented. By using the concept of the guaranteed cost control method, sufficient conditions are obtained for both minimization of the state-matching error and stabilization of the sampled-data closed-loop system and derived in terms of linear matrix inequalities (LMIs). Finally, a numerical example is provided to verify the effectiveness of the proposed technique.