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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/53985

Title: 基於動態模型之控制系統實現
Control System Implementation Based on Dynamic Models
Authors: Chang, Chia-Wei
張嘉崴
Contributors: NTOU:Department of Communications Navigation and Control Engineering
國立臺灣海洋大學:通訊與導航工程學系
Keywords: 電動平衡載具;動態模型;模糊控制器;小腦模型控制器;類神經網路
Vehicle system;Model based;Fuzzy controller;CMAC;neural network
Date: 2019
Issue Date: 2020-07-09T02:52:31Z
Abstract: 本論文將基於各個系統模型,並實現於電動獨輪車、電動雙輪載具以及改良型電動獨輪車系統中。其三種載具系統藉由直流馬達的動力使載具平台維持於平衡點,並依照騎乘者之重心移動,使車身移動,達到車體移動的目的。而系統中皆是利用牛頓運動定律使系統保持平衡。這樣的平衡載具系統實現能達到成為代步工具之目標,並利用電池做為能源,降低交通工具所造成之空氣汙染。 為了完成平衡載具的平衡控制,針對各個系統使用不同的平衡控制器,以載具平台之傾斜之角度以及角速度做為控制變數,經過控制器運算後,傳送命令至直流馬達,並在馬達出力旋轉後達到載具維持平衡不倒之目標。本論文中各個系統有各自推導出的動態模型,並使用不同的控制器。在此先使用MSC.ADAMS與MATLAB/SIMLINK的聯合模擬對動態模型進行驗證,再設計出根據動態模型的各個控制器。 對於電動獨輪車,使用強健適應性輸出遞迴仿第二型模糊控制器做為平衡控制器;在電動雙輪載具方面,使用了強健適應性輸出遞迴仿第二型小腦膜性控制器做為平衡控制器;最後在改良型電動獨輪車中,使用了強健適應型輸出遞迴粒子群優派翠Elman類神經網路控制器做為平衡控制器。以上三種控制器皆使用高斯函數做為歸屬函數,其中輸出遞迴改善了控制器為靜態的缺點,而強健控制器包含了所推導控制系統的動態模型,使得控制系統在面對外擾以及不確定因素時能夠有更佳的反應。再者,藉由李亞普諾夫穩定性(Lyapunov Stability)分析推導以達到誤差收斂之目的。最後,透過模擬以及實驗結果,證明了基於動態模型之控制器能夠實現於各系統中,並在平衡控制上有不錯的表現。
The purpose of this thesis is to implement the control system based on each dynamic models. The co-simulation of MSC.ADAMS and MATLAB/SIMULINK is used here to verify the derived dynamic model. Then design each controller to each control system based on the dynamic models. In this study, a robust adaptive output recurrent imitate type-2 fuzzy controller is proposed for the electric unicycle, robust adaptive output recurrent imitate type-2 cerebellar model articulation controller is applied to electric two-wheel vehicle, and robust adaptive output recurrent particle swarm optimization (PSO) Petri Elman neural network controller is proposed for modified electric unicycle vehicle. The output recurrent technique make the static controller to dynamic. The robust controller contains the derived dynamic model of each control system, which make the control system has better performance when facing the external disturbance and uncertainties. When a person riding on the vehicle system, the control strategy is proposed for real-world moving control. The main object of this thesis is to implement a self-dynamic balancing control system. Owing to the nonlinear and time varying characteristic of the vehicle system, an adaptive control method based on the dynamic models of control system is designed. The Lynapunov stability analysis is applied here to guarantee the convergence of tracking error. In the end, the results of simulation and experiment verify the performance of the balance controller to each vehicle system.
URI: http://ethesys.lib.ntou.edu.tw/cgi-bin/gs32/gsweb.cgi?o=dstdcdr&s=G0010567019.id
http://ntour.ntou.edu.tw:8080/ir/handle/987654321/53985
Appears in Collections:[通訊與導航工程學系] 博碩士論文

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