Cognitive non-linear controller design for magnetic levitation system

Abstract

This paper proposes a new development of a position-tracking control algorithm for a non-linear magnetic ball levitation system by utilizing the back-stepping technique based on the cognitive online auto-tune algorithm. The aim of the proposed cognitive robust non-linear controller is to find the optimal voltage or current control action for the real magnetic ball levitation model during the tracking of pre-defined position of the steel ball precisely and quickly. The cognitive methodology guided by the Lyapunov stability criterion is implemented as a stable and robust online auto-tune algorithm to find optimal parameters for the proposed controller. Matlab simulation results and laboratory work confirm the validity and the robustness of the proposed controller algorithm in terms of overcoming the noise signal and disturbances, minimizing the tracking error, and obtaining an optimal and smooth control signal, with the minimum number of fitness evaluations.