Design of Sliding Mode Controller with Particle Swarm Optimization using Optimised PID Sliding

Abstract

In this paper a path planning technique called particle swarm optimization and sliding mode control is described. Particle Swarm optimization (PSO) is a computational strategy that upgrades an issue by repeatedly attempting to improve an applicant solution with respect to a given proportion of value. Evaluation and detailed design of the Sliding Mode Control (SMC), utilizes a discontinuous controller is developed in two phases, i.e. reaching phase and sliding phase and it will be integrated with PID(proportional-integral-derivative). The sliding stage, represented by decreased order dynamics, provides some advantages in terms of parameters and disturbances such as invariance. PID controller is a mechanism in which uses feedback to evaluate the error and applies correction. Particle swarm optimization and sliding mode control are the unique technique that can be used to optimize the gain parameter. In addition, it has been noted that the reaching stage is vulnerable to unpredictability and disruption that may demean efficiency or even result in issues with stability in some delicate apps. Known for chattering eradication, the Smooth SMC (SSMC) does not match the sense of sliding methods. In this paper, the SSTA's novel Lyapunov function-based assessment is suggested and by virtue of cohesion new performance and robustness parameters are produced which include analytical phrases as selecting controller gains, setting time for the closed loop system, and stability boundaries for a class of unpredictability.