【作者】 张友刚；

【导师】 肖建；

【作者基本信息】 西南交通大学 ， 电力电子与电力传动， 2003， 博士

【摘要】 传统控制理论难以解决复杂非线性系统分析、建模与控制问题，而模糊控制技术由于能够方便地利用专家经验及语言信息，甚至无需建立系统数学模型即可对系统进行控制，目前已逐渐成为复杂非线性系统分析与设计所采用的主要方法之一。但是由于模糊控制系统自身的非线性特性，使得其稳定性分析与性能设计缺乏有效的解析方法，很多设计过程是通过尝试的方法来完成的。因此，如何将传统控制理论中的解析设计方法与模糊系统理论相结合，产生一套完整的系统化的模糊控制理论，已成为模糊控制理论研究人员的一项迫切任务。 此外随着现代科技的迅速发展，实际控制系统变得越来越复杂，越来越大型化，所以近年来关于大系统分散控制理论的研究引起了学术界和工程界的广泛兴趣。本论文的主要目的是将模糊控制技术与大系统分散控制理论相结合，建立一套系统化的非线性关联模糊大系统稳定性分析与性能设计的有效方法。 首先，本文对关联模糊大系统的分散镇定问题进行了研究。稳定性与相应的镇定问题是模糊控制系统分析与设计的基本问题。本文所研究的关联模糊大系统由一系列T-S模糊子系统构成。本文采用分散化并行分布补偿(DPDC)模糊控制器实现非线性关联模糊大系统的控制，即对每个子T-S模糊系统均采用一个PDC控制器进行控制。基于李雅普诺夫稳定性理论及大系统分散控制理论，采用LMI方法导出了该类模糊大系统在采用DPDC模糊控制器时闭环渐近稳定的充分条件，并利用隶属函数的信息对该稳定性条件进行了改进，得出了保守性更小的稳定性条件。此外，考虑到实际系统的状态通常不能完全量测，本文研究了其分散状态观测器的设计方法。所设计的分散状态观测器与DPDC模糊控制器类似，本身也是一系列T-S模糊子系统，本论文给出了这些分散化状态观测器能渐近估计出原系统状态的LMI形式的充分条件。并证明了对于关联模糊大系统而言，线性系统中著名的控制器及观测器设计的分离原理也是成立的，这对于非线性关联模糊大系统控制器与观测器的分析与设计问题具有重要的意义。 其次，本论文研究了一类具有参数不确定性的连续时间及离散时间关联模糊大系统的分散鲁棒镇定问题。所考虑的参数不确定性以范数有界的形式出现在各个子模糊系统的系统矩阵、输入矩阵及输出矩阵中，本论文讨论了该类不确定性关联大系统DPDC控制器的设计问题。采用LMI方法给出了该类不确定性关联模糊大系统可分散鲁棒镇定的条件。同时通过利用隶属度函数的信息对该鲁棒镇定条件进行了改进，得到了保守性更小的LMI形式的鲁棒镇定条件。第11页西南交通大学博士研究生学位论文 此外，本文考虑了具有时滞关联项的模糊大系统的分散镇定问题。众所周知，由于系统中信息传输和测量的不灵敏性，其关联项常常存在时滞现象，而时滞常常是导致系统不稳定的因素。基于李雅普诺夫稳定性理论及大系统分散控制理论，通过定义增广的状态变量，本文给出了LMI形式的连续及离散时滞模糊大系统的时滞无关分散能镇定条件。 最后，本文采用LMI技术，研究了一类具有参数不确定性的连续时间及离散时间关联模糊大系统的保性能控制问题，给出了其分散状态反馈保成本控制器的设计方案，所设计的控制器不但能使系统闭环稳定，而且闭环系统的性能也得到了一定的保证。 本文的研究结果提供了一套非线性关联模糊大系统控制器、观测器及性能分析与设计的有效方法，为实际的复杂工业大系统的模糊控制提供一套现实可行的方案，LMI方法的数值有效性保证了本文方法的切实可行性。更多还原

【Abstract】 By utilizing expert experience and language information, analyzing, modeling and control of many industrial complex plants can be handled effectively by fuzzy control technology, which otherwise will be very hard by approaches of traditional control theory, if not impossible. In addition, these complex plants can be controlled easily even without exact mathematical models, so fuzzy control has become a popular topic for analysis and design of complex nonlinear systems. However, the nonlinear nature of fuzzy control technology sets an obstacle to development of analytic method for stability analysis and systematic performance design of fuzzy control systems, and many design procedures are performed by trial-and-error. So, how to combine the advantages of analytic methods of traditional control theory and fuzzy systems theory and develop an integrated and systematic fuzzy control theory has increasingly becoming an urgent task for researchers of fuzzy control theory.On the other hand, with the rapid development of modern science and technology, the practical control system has become very huge and complex, so decentralized control theory of large-scale systems has attracted great attentions in both academic research and industrial applications. The main aim of this dissertation is to fuse the fuzzy logic control technology and decentralized control theory of large-scale system to develop a systematic design methodology that guaranteeing some basic requirements, such as stability and acceptable performance, for nonlinear interconnected fuzzy large-scale systems.Firstly, decentralized stabilization problems for interconnected fuzzy large-scale systems are considered. Stability and stabilization are the most basic problems in analysis and design of fuzzy control systems. The interconnected fuzzy large-scale systems considered in this dissertation consists of some interconnected T-S fuzzy subsystems, Decentralized Parallel Distributed Compensation (DPDC) fuzzy controllers are designed for this fuzzy large-scale systems, namely each T-S fuzzy subsystems will be controlled only by one PDC fuzzy controllers. Based on Lyapunov stability theory and decentralized control theory of large-scale systems, sufficient conditions for asymptotic stability of the closed-loop fuzzy large-scale systems are derived via LMI technology, and by using information of membership functions these LMI-basedsufficient conditions are relaxed and less conservative stabilization conditions are obtained. Considering that not all of the states variables of the system can be detected, decentralized states observers are also designed to estimate the system states. Similar to DPDC fuzzy controllers, these decentralized states observer are T-S fuzzy systems themselves. And LMI-based sufficient conditions for these states observers to estimate the true states of the fuzzy large-scale system asymptotically are developed. Furthermore, the well-known separation principle for designs of controllers and observers in linear system theory are proved to be hold for fuzzy large-scale systems considered in this dissertation, which is important for analysis and design problems of controllers and observers of interconnected fuzzy large-scale systems.Next, robust decentralized stabilization problems for a class of interconnected fuzzy large-scale systems with parametric uncertainties are considered in this dissertation, both for continuous-time and discrete-time case. The norm-bounded parametric uncertainties entered into system matrices, input matrices and interconnections in all of the T-S fuzzy subsystems. DPDC controllers are designed for the uncertain interconnected fuzzy large-scale systems and LMI-based decentralized robust stabilizable conditions for uncertain interconnected fuzzy large-scale systems are developed. By utilizing information of membership functions these robust stabilizable conditions are also relaxed and less conservative LMI-based conditions are obtained.In addition, decentralized stabilization problems for fuzzy large-scale更多还原