B-Spline Wavelet Neural Network-Based Adaptive Control for Linear Motor-Driven Systems Via a Novel Gradient Descent Algorithm

This paper proposes a gradient descent (GD) algorithm-based B-Spline wavelet neural network (GDBSWNN) learning adaptive controller for linear motor (LM) systems under system uncertainties and actuator saturation constraints. A recursive least squares (RLS) algorithm-based indirect adaptive strategy...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on industrial electronics (1982) 2024-02, Vol.71 (2), p.1-10
Main Authors: Liu, Zhitai, Gao, Huijun, Yu, Xinghu, Lin, Weiyang, Qiu, Jianbin, Rodriguez-Andina, Juan J., Qu, Dongsheng
Format: Article
Language:English
Subjects:
Actuator saturation
Actuators
Adaptation models
Adaptive algorithms
Adaptive control
Artificial neural networks
b-spline wavelet neural network
Closed loops
Compensators
Electric motors
Feedback control
Friction
gradient descent
indirect adaptation
linear motor
Neural networks
Splines (mathematics)
Stability analysis
Uncertainty
Windings
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper proposes a gradient descent (GD) algorithm-based B-Spline wavelet neural network (GDBSWNN) learning adaptive controller for linear motor (LM) systems under system uncertainties and actuator saturation constraints. A recursive least squares (RLS) algorithm-based indirect adaptive strategy is used to effectively estimate model parameters, which can guarantee they converge to true values. A novel GDBSWNN compensator is proposed to estimate the remaining complex uncertainties, where weights are updated by online GD training. An auxiliary system is integrated into the control scheme to address the saturation problem, which guarantees stability and satisfactory control performance when saturation occurs. In addition, a stability analysis is presented to prove that all signals of the closed-loop system are bounded using the Lyapunov theory. Experiments have been conducted on an LM-driven motion platform, where different controllers have been tested, demonstrating the effectiveness and advantages of the proposed approach.
ISSN:0278-0046
1557-9948
DOI:10.1109/TIE.2023.3260318