Integration of Particle Swarm Optimization and Sliding Mode Control: A Comprehensive Review

Particle swarm optimization (PSO) is among the prominent computing approaches that rely on population-based optimization. It is coupled to a swarm intelligence cluster and is used in global optimization challenges. Sliding Mode Control (SMC) is a first-order control approach which has a broad range of mechanical device applications. But due to its disadvantages such as chattering effect, a higher order control mechanism is necessary. Super-Twisting SMC (ST-SMC) is a second order control mechanism, has advantages like reduced chattering effect, and achieves convergence in time. In this review article, first a comprehensive review on PSO and its applications is performed. Later, ST-SMC is reviewed in detail and then optimization of SMC parameters using PSO for autonomous vehicle is discussed.