Adaptive complementary fuzzy self-recurrent wavelet neural network controller for the electric load simulator system

Abstract

Due to the complexities existing in the electric load simulator, this article develops a high-performance nonlinear adaptive controller to improve the torque tracking performance of the electric load simulator, which mainly consists of an adaptive fuzzy self-recurrent wavelet neural network controller with variable structure (VSFSWC) and a complementary controller. The VSFSWC is clearly and easily used for real-time systems and greatly improves the convergence rate and control precision. The complementary controller is designed to eliminate the effect of the approximation error between the proposed neural network controller and the ideal feedback controller without chattering phenomena. Moreover, adaptive learning laws are derived to guarantee the system stability in the sense of the Lyapunov theory. Finally, the hardware-in-the-loop simulations are carried out to verify the feasibility and effectiveness of the proposed algorithms in different working styles.

A wavelet neural control scheme for a quadrotor unmanned aerial vehicle

“…WNN-based control systems have been adopted widely for control of complex dynamical systems owing to their fast learning properties and good generalization capability. Moreover, recurrent wavelet neural networks (RWNNs), which combine properties such as dynamic response of recurrent neural networks and the fast convergence of WNNs, have been proposed to identify and control nonlinear systems [19][20][21][22][23][24][25][26]. An intelligent control system using a recurrent wavelet-based Elman neural network for position control of a permanent magnet synchronous motor servo drive was proposed in [27].…”

Dynamics and Stability of Permanent‐Magnet Synchronous Motor

“…It has both the advantages of reliable operation of AC motor and the advantages of excellent speed control performance of DC motor which is very suitable for engineering application [1][2][3][4]. PMSM is a multivariable, strongly nonlinear, and strongly coupled electromechanical system [5,6]. When PMSM is used in engineering, the parameters are not fixed but fluctuate within a range according to the changes of working environment, and the torque and speed may irregularly oscillate in some parameter regions which is not allowed for ensuring the stability and security.…”