Total sliding-model-based particle swarm optimization control design for linear induction motor

In this study, a total sliding-mode-based particle swarm optimization control (TSPSOC) scheme is designed for the periodic motion control of an indirect field-oriented linear induction motor (LIM) drive. First, an indirect field-oriented mechanism for a LIM drive is introduced to preserve the decoupling control characteristic. Then, the concept of toal sliding-mode control (TSC) is incorporated into particle swarm optimization (PSO) to form an on-line TSPSOC framework for preserving the robust control characteristics and reducing the chattering control phenomena of TSC. Moreover, an adaptive inertial weight is devised to accelerate the searching speed effectively. In this control scheme, a PSO control system is utilized to be the major controller, and the stability can be indirectly ensured by the concept of TSC without strict constraint and detailed system knowledge. Numerical simulations are given to verify the effectiveness of the proposed control scheme for the tracking of periodic reference trajectories. In addition, the superiority of the proposed TSPSOC scheme is indicated in comparison with the TSC, Petri fuzzy-neural-network control (PENNC), and traditional fuzzy-neural-network control (TFNNC) systems.