Adaptive controller with fuzzy rules emulated structure and its applications
Adaptive controller with fuzzy rules emulated structure and its applications
复制标题
DOI：
10.1016/j.engappai.2004.12.006
复制
发表时间：
2005-08-01
影响因子：
8
通讯作者：
Uatrongjit, S
中科院分区：
文献类型：
--
作者：
Treesatayapun, C;Uatrongjit, S
本文提出了一种受神经模糊控制器启发的自适应控制器。它的结构，称为模糊规则仿真网络（FREN），推导出基于模糊IF-THEN规则。这种结构不仅仿真了模糊控制规则，而且可以直观地选择控制器参数的初始值。这些参数在系统操作期间使用类似于最速下降技术的方法进一步调整。基于李雅普诺夫稳定性条件给出了学习率的选择准则。FREN控制器被应用于控制各种非线性系统，例如，单级倒立摆系统、水浴温度控制、高压直流输电系统和机器人系统。计算机仿真结果表明，所提出的控制器能够令人满意地控制目标系统。(c)2005爱思唯尔有限公司保留所有权利。
In this paper, the adaptive controller inspired by the neuro-fuzzy controller is proposed. Its structure, called fuzzy rules emulated network (FREN), is derived based on the fuzzy IF-THEN rules. This structure not only emulates the fuzzy control rules but also allows the initial value of controller's parameters to be intuitively chosen. These parameters are further adjusted during system operation using a method similar to the steepest descent technique. The learning rate selection criteria based on Lyapunov's stability condition is also presented. FREN controller is applied to control various nonlinear systems, for examples, the single invert pendulum plant, the water bath temperature control, the high voltage direct current transmission system and the robotic system. Computer simulations results indicate that the proposed controller is able to control the target systems satisfactory. (c) 2005 Elsevier Ltd. All rights reserved.