Hybrid PD-fuzzy position controller for linear switched reluctance motor with online fuzzy logic gain scheduling of PD

Abstract

This paper presents the design of an adaptive hybrid controller for linear switched reluctance motor (LSRM) to be used in pick and place industrial applications. The hybrid controller consists of two main controllers, the proportional-derivative controller (PDC) and the fuzzy logic controller (FLC). In this paper, the proposed Adaptive hybrid PD-fuzzy logic controller (AHPDFLC) uses, at the beginning, the adaptive PDC (APDC) for coarse position error while for fine position error the position control process is achieved using conventional FLC. This hybrid controller exploits the advantages of both controllers, APDC which can vary its gains online to avoid the overshoot problems and FLC which can decrease the steady-state error to roughly zero value to get an acceptable position tracking response of the underlying LSRM. The adaptivity of the hybrid controller refers to the variation of PDC's proportional and derivative gains to adapt a wide range of loading conditions i.e. a specific reference position signal, load force, mover mass, friction constant, applied dc voltage and phase resistance. PDC gain scheduling is achieved online based on fuzzy rules and reasoning. The results of AHPDFLC are compared with the results of non-adaptive position controllers. This comparison between different position controllers' response verifies the simplicity and the effectiveness of the proposed adaptive hybrid position controller for a wide range of variable loading conditions. Finite Element Method Magnetics (FEMM) and MATLAB/Simulink simulation programs are used throughout the paper to model the different modules of LSRM to prove the validity of this position controller approach on simulation environment.