Finite-time adaptive control based on output feedback and auxiliary variables for time-varying parameters and disturbances

Abstract

This paper presents a finite-time adaptive control scheme tailored for a diverse range of unknown discrete-time systems, with a specific emphasis on BLDC motor position control. The approach leverages an auxiliary variable within an output feedback framework, adeptly circumventing the causality problem without necessitating the use of state or disturbance observers. Through the application of finite-time convergence techniques, the control law demonstrates robust performance even in the presence of time-varying parameters and compact disturbances. Additionally, the proposed time-varying estimator, based on multi-input fuzzy emulated network (MiFREN), offers a practical solution for handling unknown dynamics and disturbances, making it well-suited for real-world applications where accurate mathematical models may be unavailable. Extensive experimental validation is conducted to evaluate the efficacy of the proposed scheme, including comparisons with existing controllers. The results highlight the superiority of the approach, particularly in terms of tracking accuracy and robustness against disturbances.