Robot high precision trajectory tracking variable domain fuzzy control

被引：0

作者：

Wan M. ^{[1
]}

An L.-Z. ^{[1
]}

Hu D.-Z. ^{[2
]}

Chen H.-F. ^{[1
]}

机构：

[1] School of Mechatronic Engineering, Southwest Petroleum University, Chengdu

[2] Department of Aviation Manufacturing Engineering, Chengdu Aeronautic Polytechnic, Chengdu

来源：

Wan, Min (18940103@qq.com) | 1600年 / Computer Society of the Republic of China卷 / 28期

关键词：

Fuzzy control; Genetic algorithm; Robot; Trajectory tracking; Variable universe;

D O I：

10.3966/199115992017122806007

中图分类号：

学科分类号：

摘要：

In order to achieve the desired path of the robot, trajectory tracking of robot system is to follow a given trajectory change with each joint's controller output drive torque control of each joint position, velocity and other variables. However, the traditional design method of the controller was usually based on the controlled object model, but the various uncertain factors in the actual engineering will lead to the precise mathematical model of the robot can not be gained, therefore the traditional control method will be difficult to achieve the purpose of high precision control. The fuzzy controller does not need to know the exact mathematical, but the control precision of the fuzzy control is not high. In this paper, based on the fuzzy control of the robot, the paper introduces the variable universe theory, introduces the domain expansion factor in the input variables, and uses the genetic algorithm to optimize the expansion factor to achieve the purpose of the variable universe. The simulation results show that the variable universe fuzzy control method has good adaptability, robustness and anti-interference ability, and the control precision is very high, and it can solve the control difficulty caused by the coupling effect of each link, and has high application value for the uncertain robot system.

引用

页码：79 / 87

页数：8

共 14 条

[1]

Liu J., Robot Control System and MATLAB Simulation, (2013)

[2]

Liu H.B., Wang J., Yan-He W.U., Study and Simulation of Fuzzy Adaptive PID Control of Brushless DC Motor, (2014)

[3]

Wen S., Zhao G., Cai K., A fuzzy-control adaptive algorithm with variable domain, Control Theory & Applications, 26, 3, pp. 265-268, (2009)

[4]

Tan B., Li C., Comparative study of the selection method of variable universe contraction-expansion, Science Technology and Engineering, 13, 4, pp. 908-911, (2013)

[5]

Fu G., Kinematics and Dynamics Analysis of A Manipulator, (2015)

[6]

Sun M., Zhu G., Xie J., Parameter method of constructing rational interpolating function, Computer Engineering and Applications, 50, 19, pp. 47-52, (2014)

[7]

Li Z., Zhang Y., Design of fuzzy controller based on calculation model of fuzzy reasoning algorithm, Computer Engineering and Applications, 50, 14, pp. 259-264, (2014)

[8]

Guo H., Li H., Hu K., A novel variable universe adaptive fuzzy controller, Fuzzy Systems and Mathematics, 25, 6, pp. 32-42, (2011)

[9]

Pan Y.P., Huang D.P., Zong-Hai A.S., Adaptive fuzzy control with high accuracy for uncertain nonlinear systems, Journal of The University of Electronic Science & Technology of China, 2012, pp. 54-59, (2012)

[10]

Chen F.G., Deng G.N., Tan Y.H., The design of improved variable universe fuzzy controller of triple inverted pendulum, Control Theory & Applications, 27, 2, pp. 233-237, (2010)

← 1 2 →