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Optimal Design of Super Twisting Control with PSO Algorithm for Robotic Manipulator

, and . International Journal of Intelligent Systems and Applications in Robotics (IJRA), 9 (1): 1 - 15 (December 2018)

Abstract

Robotic manipulators are nonlinear and coupling systems exposing to external disturbance. They are used in wide industrial applications; the suitable selection of a nonlinear robust controller is required. Sliding Mode Controller (SMC) was designed to achieve these requirements, but unfortunately the chattering phenomenon was the main drawback of the conventional SMC. It leads to destructive of some components of a real system and subsequent loss in its accuracy. Hence, the design of Super-Twisting Controller (STC) is suggested for chattering elimination. In previous literatures, the accomplishment of the manual adjustment for the parameters of STC was a large burden and time consuming process. Therefore, a new combination of Particle Swarm Optimization (PSO) algorithm with STC is proposed for optimal tuning of STC parameters. The simulation results demonstrate the superiority of the super twisting technique for chattering mitigation comparing to the conventional SMC. Also, STC tuned via PSO proves its effectiveness and robustness to different types of external disturbances without the needs for the knowledge of their upper boundary values. Besides, the performance of the controlled system is faster and more accurate in the criteria of overshoot, settling time and rise time compared to the manual adjusting of super twisting controllers.

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