文档介绍：第 4 章 Adaptive Fuzzy Control
教学内容
本章将现代控制理论的自适应控制理论应用于模糊控制技术中,以期提高模糊控制系统的动态、静态
性能,增强模糊控制系统对于模型的参数、结构变化的鲁棒性以及控制系统不同相应阶段对控制其性能的
不同要求,提高控制系统的综合品质。主要内容:
1. 直接自适应控制和间接自适应控制的基本概念;
2. 模糊模型参考学习控制(FMRLC)的原理、结构;
3. FMRLC 的设计和实现。
教学重点
模糊模型参考学习控制(FMRLC)的原理和结构。
教学难点
对 FMRLC 中学习机制的准确把握和理解,关键是模糊逆模型的设计。
教学要求
本章的学习需要预先掌握一定的自适应控制、自校正调节器的基础知识、概念。要求掌握模糊模型参
考学习控制(FMRLC)的原理和结构。
Overview
The design process for fuzzy controllers that is based on the use of heuristic information from human experts has
found ess in many industrial applications. Moreover, the approach to constructing fuzzy controllers via numerical
input-output data is increasingly finding use.
Regardless of which approach is used, however, there are certain problems that are encountered for practical control
problems, including the following: (1) The design of fuzzy controllers is performed in an ad hoc manner so it is often
difficult to choose at least some of the controller parameters. For example, it is sometimes difficult to know how to pick
the membership functions and rule-base to meet a specific desired level of performance. (2) The fuzzy controller
constructed for the nominal plant may later perform inadequately if significant and unpredictable plant parameter
variations occur, or if there is noise or some type of disturbance or some other environmental effect. Hence, it may be
difficult to perform the initial synthesis of the fuzzy controller, and if the plant changes while the closed-loop system is
operating we may not be able to maintain adequate performance levels.
As an example, we showed how our heuristic knowledge can be used to design a fuzzy controller for the rotational
inverted pendulum. However, we also showed that if a bottle half-filled with water is attached to the endpoint, the
performance of the fuzzy controller degraded. While we certainly could have tuned the controller for this new situation,
it would not then perform as well without a b