Kinematics/Fuzzy Logic Combined Controller for Formation Control of Mobile Robots

Zhi-Jiang Du¹, Li-Min Ren^1,2, Wei-Dong Wang¹, Wei Dong¹

(1. State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150080, China; 2. College of Mechanical Engineering, Beihua University, Jilin 132021, China)



Abstract:

A kinematics and fuzzy logic combined formation controller was proposed for leader-follower based formation control using backstepping method in order to accommodate the dynamics of the robot. The kinematics controller generates desired linear and angular velocities for follower robots, which make the configuration of follower robots coverage to the desired. The fuzzy logic controller takes dynamics of the leader and followers into consideration, which is built upon Mamdani fuzzy model. The force and torque acting on robots are described as linguistic variables and also 25 if-then rules are designed. In addition, the fuzzy logic controller adopts the Centroid of Area method as defuzzification strategy and makes robots¡¯ actual velocities converge to the expected which is generated by the kinematics controller. The innovation of the kinematics and fuzzy logic combined formation controller presented in the paper is that the perfect velocity tracking assumption is removed and real-time performance of the system is improved. Compared with traditional torque-computed controller, the velocity error convergence time in case of the proposed method is shorter than traditional torque-computed controller. The simulation results validate that the proposed controller can drive robot members to form the desired formation and formation tracking errors which can coverage to a neighborhood of the origin. Additionally, the simulations also show that the proposed method has better velocity convergence performance than traditional torque-computed method.

Key words:  kinematics/fuzzy logic combined  formation controller  mobile robot  backstepping

DOI£º10.11916/j.issn.1005-9113.2013.04.019

Clc Number:TP242.6

Fund: