多重智慧控制器應用於機械手臂定位
Abstract
本論文的主要目的是設計一個六軸機械手臂，並且實現高精密且高穩定之六軸機械手臂。並且在硬體架構、機械手臂之空間三維座標、機械手臂各關節轉動角度與定位追跡的控制作介紹。在空間座標轉換中，本研究使用了D-H 座標系統來運算，並且求得機械手臂中各軸關節之轉換矩陣，再藉由順向運動學與逆向運動學的理論求得機械手臂之空間三維座標與機械手臂各關節轉動角度之轉換關係，並且再藉由設計控制器完成定位控制與追跡控制。
在控制器設計方面，本論文也設計一個多重人工智慧控制器去控制此六軸機械手臂。在控制的過程中，系統會有外界的干擾與不穩定因素，因此本研究所使用之適應性模糊類神經網路控制器會藉由理想輸出位置與機械手臂實際位置之誤差的回授來調整控制器的內部參數，藉由控制器自行調整其內部參數，則可達到高精密與高穩定度的控制法則。最後也提出李阿普諾函式(Lyapunov function)來證明此控制機械手臂系統之穩定性。
The purpose of this paper is to design a six axis robot manipulator, and achieve a high-precision and high-stable six axis robot manipulator. We introduce four part, about hardware architecture, the coordinate of three axis of the robot manipulator, all the rotate degree of the joint of robot manipulator,and the positioning control. In the paper, we use D-H coordinate method to transform the coordinate of three axis and all the rotate degree of the joint of robot manipulator. Finally, we design the controller to achieve positioning and tracing the robot command. In the controlling of robot manipulator, we design a hybrid artificial intelligence controller to control the six axis robot manipulator. In the control process, there are lots of disturbance and uncertainty, so we use adaptive fuzzy neural network controller to control the robot manipulator. This controller will update its parameter by the error between the command position and real position of the end of robot manipulator, so we can let the robot manipulator to achieve high-precise and high-stable. Finally, we use Lyapunov function to prove the stability of the robot manipulator system.
The purpose of this paper is to design a six axis robot manipulator, and achieve a high-precision and high-stable six axis robot manipulator. We introduce four part, about hardware architecture, the coordinate of three axis of the robot manipulator, all the rotate degree of the joint of robot manipulator,and the positioning control. In the paper, we use D-H coordinate method to transform the coordinate of three axis and all the rotate degree of the joint of robot manipulator. Finally, we design the controller to achieve positioning and tracing the robot command. In the controlling of robot manipulator, we design a hybrid artificial intelligence controller to control the six axis robot manipulator. In the control process, there are lots of disturbance and uncertainty, so we use adaptive fuzzy neural network controller to control the robot manipulator. This controller will update its parameter by the error between the command position and real position of the end of robot manipulator, so we can let the robot manipulator to achieve high-precise and high-stable. Finally, we use Lyapunov function to prove the stability of the robot manipulator system.
Description
Keywords
機械手臂, 適應控制, 模糊類神經網路, Lyapunov function, Robot manipulator, adaptive control, fuzzy neural network, Lyapunov function