Fuzzy Controller Design Based On Particle Swarm Optimization Algorithm for Two-Wheeled Balance Robot

Document Type : Original Article

Authors

20.1001.1.27174409.1399.3.2.1.8/DOR

Abstract

Controlling balance robots is one of the most challenging issues in control science. The two-wheeled balance robot with a physical structure similar to an inverted pendulum is widely used in the fields of transportation, military and recreation. This paper deals with the design of a controller for a two-wheeled balance robot with the aim of maintaining balance and tracking different paths. Here, the dynamic equations of a two-wheeled equilibrium robot are divided into two distinct subsystems, one involving the equilibrium state variables and linear velocity, and the other involving the angular velocity mode variable. The slider mode controller is designed to control the first subsystem and the fuzzy controller is designed to control the second subsystem. The fuzzy controller is not based on the dynamic model of the system and has a good performance against system uncertainties. The particle swarm optimization (PSO) algorithm is used to determine the optimal values ​​of the fuzzy controller parameters. The simulation results show a significant improvement in the performance of the PSO-based fuzzy controller compared to the fuzzy controller in pursuing the speed of different angles in terms of mean squares and maximum size of the tracking error. The slider mode controller also performs well and reduces tracking time by maintaining an equilibrium angle and controlling the linear velocity.

Keywords

References

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History

  • Receive Date: 29 August 2020
  • Revise Date: 02 December 2020
  • Accept Date: 26 April 2021

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