Intelligent robust PI adaptive control strategy for speed control of EV(s)

Abstract

The intensive non-linear system and plants of modern industry highly motivating researcher to extend and evolve non-linear control systems. In this study, in order to control a class of non-linear uncertain power systems in the presence of large and fast disturbances, a new simple indirect adaptive proportional-integral is proposed. For handling dynamic uncertainties, the proposed controller utilises the advantages of least squares support vectors regression (LS-SVR) to approximate unknown non-linear actions and noisy data. The LS-SVR is used to approximate the non-linear uncertainties which must be bounded, whereas no requirement needs for bounds to be known. The globally asymptotic stability of the closed-loop system is mathematically proved by using Lyapunov synthesis. To show the merits of the proposed approach, a non-linear electric vehicle (EV) system is considered as a case study. The goal is to force the speed of EV to track a desired reference in the present of structured and unstructured uncertainties. The experimental data, new European driving cycle, is used in order to examine the performance of proposed controller. The simulation studies on a second-order EV with the presence of fast against slow and large against small disturbances demonstrate the effectiveness of the proposed control scheme.