Adaptive critic anti-slip control of wheeled autonomous robot

被引：40

作者：

Lin, W.-S. ^{[1
]}

Chang, L.-H. ^{[1
]}

Yang, P.-C. ^{[1
]}

机构：

[1] Natl Taiwan Univ, Dept Elect Engn, Taipei, Taiwan

来源：

IET CONTROL THEORY AND APPLICATIONS | 2007年 / 1卷 / 01期

关键词：

Automation - Computer simulation - Fuzzy control - Heuristic programming - Neural networks - Optimization - Velocity control - Wheels;

D O I：

10.1049/iet-cta:20050341

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

When a wheeled autonomous robot drives with wheel slips, the velocity and posture control becomes difficult. An ideal automatic driving control system should be able to comply with changes in slip conditions so as to optimise the control performance. Using dual heuristic programming and multi-layer perceptron neural networks, an adaptive critic anti-slip control design is developed to achieve this goal. The critic structure enables neural network learning by satisfying the Bellman equation so that the inclination of the action performance can be assessed to improve the control parameters. A slip model of the robot vehicle is derived. The adaptive critic anti-slip control system is verified extensively by computer simulation. The result shows that the performance is significantly better than that of using traditional fuzzy control.

引用

页码：51 / 57

页数：7

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