Adaptive Matching Pursuit based Online Identification and Control Scheme for Nonlinear Systems

TL;DR

This paper introduces an adaptive matching pursuit algorithm with wavelet bases for real-time identification and control of nonlinear systems with changing parameters, aiming for low computational complexity and robust performance.

Contribution

It presents a novel online identification and control scheme using adaptive matching pursuit with wavelet bases tailored for nonlinear time-varying systems.

Findings

Effective in identifying nonlinear systems with time-varying parameters

Achieves good control performance in benchmark tests

Demonstrates robustness under parameter variations

Abstract

The complexity of adaptive control of nonlinear time-varying systems requires the use of novel methods that have lower computational complexity as well as ensuring good performance under time-varying parameter changes. In this study, we use adaptive matching pursuit algorithm with wavelet bases for an online identification and control of the nonlinear system with time-varying parameters. We apply the proposed online identification and control scheme to two different benchmark examples of nonlinear system identification and control. Simulation results show that the proposed algorithm, using adaptive matching pursuit with wavelet bases, can effectively identify and control the nonlinear system even in presence of time-varying parameters.