FPGA-based adaptive backstepping control system using RBFN for linear induction motor drive

Abstract

A field-programmable gate array (FPGA)-based adaptive backstepping control system with radial basis function network (RBFN) observer is proposed to control the mover position of a linear induction motor (LIM). First, the indirect field-oriented mechanism is adopted for controlling the LIM. Next, a backstepping control law is designed step by step for the tracking control of periodic reference trajectories, in which the uncertainties are lumped by a conservative constant. However, the lumped uncertainty is unknown and difficult to obtain in advance in practical applications. Therefore an RBFN is derived to observe the lumped uncertainty in real-time, and an adaptive backstepping control system with RBFN observer is resulted. Then, an FPGA chip is adopted to implement the indirect field-oriented mechanism and the developed control algorithms for possible low-cost, high-performance industrial applications. The effectiveness of the proposed control scheme is verified by some simulated and experimental results. By using the adaptive backstepping control system with RBFN observer, the FPGA-based LIM drive possesses the advantages of good transient control performance and robustness to uncertainties in the tracking of periodic reference trajectories.