Design of backstepping particle-swarm-optimisation control for maglev transportation system

This study focuses on the design of a backstepping particle-swarm-optimisation control (BSPSOC) for the on-line levitated balancing and propulsive positioning of a magnetic levitation (maglev) transportation system. The dynamic model of a maglev transportation system including levitated electromagnets and a propulsive linear induction motor (LIM) based on the concepts of mechanical geometry and motion dynamics is first constructed. The aim is to design an on-line particle-swarm-optimisation (PSO) control methodology to cope with the problem of the complicated control transformation and the chattering control effort in backstepping control (BSC) design, and to directly ensure the stability of the controlled system without the requirement of strict constraints, detailed system information and auxiliary compensated controllers despite the existence of uncertainties. In the proposed BSPSOC scheme, a PSO control is utilised to be the major control role, and adaptation laws derived from Lyapunov stability analyses are manipulated to adjust appropriate evolutionary coefficients. The effectiveness of the proposed control strategy for the maglev transportation system is verified by experimental results, and the superiority of the BSPSOC scheme is indicated in comparison with the total sliding-mode control (TSMC) and BSC strategies.