A Design of Adaptive Fuzzy Cerebellar Model Articulation Controller Via Particle Swarm Optimization

碩士 === 銘傳大學 === 電子工程學系碩士班 === 97 === In the thesis, a Proportional-Derivative Fuzzy Cerebellar Model Arithmetic Controller (PDFCMAC) is considered to solve tracking problem of a class of nonlinear systems. The linguistic rule of Fuzzy theory is implemented to PDFCMAC, which if-part is membership fun...

Full description

Bibliographic Details
Main Authors: Li-Chi Cheng, 鄭立奇
Other Authors: You-Shen Lo
Format: Others
Language:zh-TW
Published: 2009
Online Access:http://ndltd.ncl.edu.tw/handle/30281862414042013386
id ndltd-TW-097MCU05428003
record_format oai_dc
spelling ndltd-TW-097MCU054280032017-05-14T04:31:27Z http://ndltd.ncl.edu.tw/handle/30281862414042013386 A Design of Adaptive Fuzzy Cerebellar Model Articulation Controller Via Particle Swarm Optimization 輔以粒子群最佳化於適應性模糊小腦控制器設計 Li-Chi Cheng 鄭立奇 碩士 銘傳大學 電子工程學系碩士班 97 In the thesis, a Proportional-Derivative Fuzzy Cerebellar Model Arithmetic Controller (PDFCMAC) is considered to solve tracking problem of a class of nonlinear systems. The linguistic rule of Fuzzy theory is implemented to PDFCMAC, which if-part is membership function and then-part is CMAC. First, adaptation laws of the PDFCMAC are used to approximate an ideal controller, and then a compensated controller is employed to assure the system stability. Second, redesign adaptation laws for the proposed controller and the estimated error bound are concerned to attenuate the chattering control signal and promote the robustness of adaptation laws. The robustness of adaptive laws and compensated controller are respectively derived from the Lyapunov stability analysis, so that the system tracking ability and the error convergence can be guaranteed in the closed-loop system. Under the requirements of PDFCMAC stability and defined performance index, the Particle Swarm Optimization and fitness function are used to search a set of parameters of PDFCMAC, which is applied on electronic driver system, van der pol system and invereted pemdulum system. From the simulations, controller parameters searched by PSO has performance as well as redesign adaptive laws, and has smaller compensated control signal than redesign adaptive laws. You-Shen Lo Jen-Yang Chen 駱有聲 陳珍源 2009 學位論文 ; thesis 79 zh-TW
collection NDLTD
language zh-TW
format Others
sources NDLTD
description 碩士 === 銘傳大學 === 電子工程學系碩士班 === 97 === In the thesis, a Proportional-Derivative Fuzzy Cerebellar Model Arithmetic Controller (PDFCMAC) is considered to solve tracking problem of a class of nonlinear systems. The linguistic rule of Fuzzy theory is implemented to PDFCMAC, which if-part is membership function and then-part is CMAC. First, adaptation laws of the PDFCMAC are used to approximate an ideal controller, and then a compensated controller is employed to assure the system stability. Second, redesign adaptation laws for the proposed controller and the estimated error bound are concerned to attenuate the chattering control signal and promote the robustness of adaptation laws. The robustness of adaptive laws and compensated controller are respectively derived from the Lyapunov stability analysis, so that the system tracking ability and the error convergence can be guaranteed in the closed-loop system. Under the requirements of PDFCMAC stability and defined performance index, the Particle Swarm Optimization and fitness function are used to search a set of parameters of PDFCMAC, which is applied on electronic driver system, van der pol system and invereted pemdulum system. From the simulations, controller parameters searched by PSO has performance as well as redesign adaptive laws, and has smaller compensated control signal than redesign adaptive laws.
author2 You-Shen Lo
author_facet You-Shen Lo
Li-Chi Cheng
鄭立奇
author Li-Chi Cheng
鄭立奇
spellingShingle Li-Chi Cheng
鄭立奇
A Design of Adaptive Fuzzy Cerebellar Model Articulation Controller Via Particle Swarm Optimization
author_sort Li-Chi Cheng
title A Design of Adaptive Fuzzy Cerebellar Model Articulation Controller Via Particle Swarm Optimization
title_short A Design of Adaptive Fuzzy Cerebellar Model Articulation Controller Via Particle Swarm Optimization
title_full A Design of Adaptive Fuzzy Cerebellar Model Articulation Controller Via Particle Swarm Optimization
title_fullStr A Design of Adaptive Fuzzy Cerebellar Model Articulation Controller Via Particle Swarm Optimization
title_full_unstemmed A Design of Adaptive Fuzzy Cerebellar Model Articulation Controller Via Particle Swarm Optimization
title_sort design of adaptive fuzzy cerebellar model articulation controller via particle swarm optimization
publishDate 2009
url http://ndltd.ncl.edu.tw/handle/30281862414042013386
work_keys_str_mv AT lichicheng adesignofadaptivefuzzycerebellarmodelarticulationcontrollerviaparticleswarmoptimization
AT zhènglìqí adesignofadaptivefuzzycerebellarmodelarticulationcontrollerviaparticleswarmoptimization
AT lichicheng fǔyǐlìziqúnzuìjiāhuàyúshìyīngxìngmóhúxiǎonǎokòngzhìqìshèjì
AT zhènglìqí fǔyǐlìziqúnzuìjiāhuàyúshìyīngxìngmóhúxiǎonǎokòngzhìqìshèjì
AT lichicheng designofadaptivefuzzycerebellarmodelarticulationcontrollerviaparticleswarmoptimization
AT zhènglìqí designofadaptivefuzzycerebellarmodelarticulationcontrollerviaparticleswarmoptimization
_version_ 1718448361916334080