Abstract

This paper presents a new design of an adaptive fuzzy logic control by implementing the leader-follower approach. The principle is to modify the feedback control of non-holonomic Wheeled Mobile Robot (WMR) to be adaptive according to a fuzzy controller in the control loop, in order to adjust the feedback control gains according to the distance error between the reference path and the real position. The trajectory tracking control for a single WMR is extended to the formation control for two WMRs in which the first one is the leader and the second is the follower. Simulation results are presented to demonstrate the effectiveness of the proposed controller.

Highlights

  • Wheeled mobile robots are very useful devices that perform a wide range of tasks [1,2,3]

  • In the virtual structure approach [7, 9], the entire formation is considered as a single rigid body, which means that all robots work as a single complex robot

  • The leader moves along a predefined trajectory while the followers are controlled to maintain a desired distance and bearing angle [16]. This is the most used technic, which allows the formation control to be transformed into two simple problems, a trajectory tracking by the leader and a control to keep the formation by the followers

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Summary

INTRODUCTION

Wheeled mobile robots are very useful devices that perform a wide range of tasks [1,2,3]. In the virtual structure approach [7, 9], the entire formation is considered as a single rigid body, which means that all robots work as a single complex robot This method can control the motion of the whole robot formation, but cannot change the formation when the environment is changed, which limits the scope of its application. In the group shaped by multi-mobile robots, one robot is designed as the leader while the others are the followers In this approach, the leader moves along a predefined trajectory while the followers are controlled to maintain a desired distance and bearing angle [16]. The obtained simulation results for tracking and formation control are discussed and a comparison with conventional methods is made

MULTI MOBILE ROBOT MODELING AND CONTROL
Control Strategy
Fuzzy Systems and Fuzzy Control
Adaptive Controller Parameter Calculation
RESULTS AND DISCUSSION
CONCLUSION
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