Finite-time dynamic surface control for induction motors with input saturation in electric vehicle drive systems

摘要

This paper proposes a neural networks-based finite-time dynamic surface position tracking control method for induction motors with input saturation in electric vehicle drive systems. Firstly, the neural networks are utilized to approximate the unknown nonlinear functions and the dynamic surface control is used to solve the problem of "explosion of complexity" in traditional backstepping technology. Then, the finite-time control technology is adopted to accelerate the response speed of the system and reduce the tracking error, and the iron losses and input saturation are considered to improve control accuracy. At last, the results of simulation contrast experiments show that the proposed control method realizes ideal tracking effect considering iron losses and input saturation of the induction motors. (C) 2019 Elsevier B.V. All rights reserved.