以CMAC類神經網路控制器實現機器人控制

Abstract

本論文的目的在研究CMAC類神經網路控制系統的控制行為並分析系統的穩定性，然後和PID控制器作比較。為了知道受控系統的輸出/輸入特性，在這裡使用Runge-Kutta法。我們企圖以CMAC控制系統來扮演機械臂的pd-plus-gravity控制效果。不過CMAC控制系統不需要關於機械臂的任何資訊，而且可以應付很大的負載變化。當輸入向量緩慢的移動的時候，CMAC控制器會產生龐大的積分動作。但是當輸入向量快速變化的時候，CMAC控制器也能有效的產生"遺忘"效應。論文中也證明CMAC控制系統能夠在目標位置收斂。然後描述回授訊號雜訊對輸出誤差的影響，並且說明控制器參數改變時雜訊影響的能力。此外我們也將CMAC控制系統應用在兩軸機械臂上，以兩個獨立的CMAC控制系統對各軸獨立控制。最後比較CMAC控制系統及PID控制器的控制效果。

The object of this paper is to study the behaviors of CMAC control system and to analyze the stability of the system, and then to compare with PID controller. To find out the characteristic between output and input, the Runge-Kutta method is used. The CMAC controller is proposed to emulate the pd-plus-gravity control for robotics. However, the CMAC requires no information about the robot, and can deal with large variations in load. The CMAC produces enormous integration action when the input vector moves slowly in the space, but it can also forget efficiently when the input vector moves fast in the space. It is shown that the CMAC control system can converge into the target position. The effect of feedback signal noise has been described, the effect of noise when controller parameters are changed is also illustrated. We also use CMAC control system for 2-link robot control. Each link of the robot has an independent CMAC controller. The controller performance between CMAC control system and PID controller has been compared. 英文摘要.....................................................ii 誌謝........................................................iii 目錄.........................................................iv 表目錄.......................................................vi 圖目錄......................................................vii 第一章 緒論..................................................1 1.1 研究動機、背景與目的.....................................1 1.2 論文內容介紹.............................................2 第二章 控制對象及PID控制結果.................................4 2.1 四階Runge-Kutta法求解常微分方程式........................4 2.2 單軸機械臂...............................................6 2.2.1 PID控制結果............................................8 2.3 二軸機械臂..............................................10 2.3.1 PID控制結果...........................................14 第三章 CMAC控制器...........................................18 3.1 CMAC控制系統............................................18 3.2 CMAC之計算架構..........................................19 3.3 CMAC工作原理............................................23 3.4 記憶體配置及存取........................................24 3.5 CMAC與Traditional Adaptive Control System之比較.........25 第四章 單軸機械臂控制.......................................29 4.1 CMAC控制結果分析........................................29 4.2 穩定性分析..............................................34 4.2.1 控制對象線性化模型....................................34 4.2.2 只使用CMAC控制器......................................37 4.2.3 只使用PD控制器........................................38 4.2.4 CMAC控制系統的穩定條件................................39 4.2.5 不同操作點的穩定情形..................................40 4.2.6 PD控制器控制參數D的影響...............................40 4.2.7 Sampling Rate的影響...................................42 4.3 Tracking控制結果........................................44 4.4 系統雜訊................................................46 4.4.1 雜訊靈敏度............................................46 4.4.2 PD控制器控制參數KP的影響..............................48 4.4.3 PD控制器控制參數KD的影響..............................49 4.4.4 取樣間隔(Sampling Interval)的影響.....................50 第五章 二軸機械臂控制.......................................52 5.1 控制系統架構............................................52 5.2 CMAC之計算架構..........................................52 5.3 CMAC控制結果............................................54 第六章 結論及未來展望.......................................57 參考文獻.....................................................58