Regular Papers

International Journal of Control, Automation, and Systems 2024; 22(11): 3509-3524

https://doi.org/10.1007/s12555-024-0430-2

© The International Journal of Control, Automation, and Systems

Parameter Estimation and Model-free Multi-innovation Adaptive Control Algorithms

Xin Liu* and Pinle Qin

North University of China

Abstract

Parameter estimation is the basis of adaptive control for dynamic systems. This paper surveys and reviews some parameter estimation methods, including the projection algorithms, stochastic gradient (SG) algorithms and multi-innovation stochastic gradient (MISG) algorithms etc. Further, this paper discusses some adaptive control laws and adaptive control algorithms, including the SG self-tuning control algorithms and MISG weighted self-tuning control algorithms etc. Moreover, this paper presents some model-free adaptive control algorithms, including the compact form model-free adaptive control algorithm, SG partial form adaptive control algorithm and MISG partial form adaptive control algorithm etc. The proposed MISG adaptive control algorithm has better tracking performance than the projection and SG adaptive control algorithms because of using the multi-innovation identification theory.

Keywords Adaptive control, gradient search, least squares, multi-innovation identification, parameter estimation, stochastic system.

Article

Regular Papers

International Journal of Control, Automation, and Systems 2024; 22(11): 3509-3524

Published online November 1, 2024 https://doi.org/10.1007/s12555-024-0430-2

Copyright © The International Journal of Control, Automation, and Systems.

Parameter Estimation and Model-free Multi-innovation Adaptive Control Algorithms

Xin Liu* and Pinle Qin

North University of China

Abstract

Parameter estimation is the basis of adaptive control for dynamic systems. This paper surveys and reviews some parameter estimation methods, including the projection algorithms, stochastic gradient (SG) algorithms and multi-innovation stochastic gradient (MISG) algorithms etc. Further, this paper discusses some adaptive control laws and adaptive control algorithms, including the SG self-tuning control algorithms and MISG weighted self-tuning control algorithms etc. Moreover, this paper presents some model-free adaptive control algorithms, including the compact form model-free adaptive control algorithm, SG partial form adaptive control algorithm and MISG partial form adaptive control algorithm etc. The proposed MISG adaptive control algorithm has better tracking performance than the projection and SG adaptive control algorithms because of using the multi-innovation identification theory.

Keywords: Adaptive control, gradient search, least squares, multi-innovation identification, parameter estimation, stochastic system.

IJCAS
December 2024

Vol. 22, No. 12, pp. 3545~3811

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