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Adaptive Tracking Control of a Class of Nonlinear Systems with Input Delay and Dynamic Uncertainties Using Multi-dimensional Taylor Network

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  • Intelligent Control and Applications
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Abstract

This paper concerns on the control problem of a class of nonlinear systems with input delay and dynamic uncertainties using multi-dimensional Taylor Network (MTN) control method. Firstly, a new variable is introduced to eliminate the effect of input delay by combining Padé approximation with Laplace transformation. Secondly, a MTN-backstepping-based control strategy is constructively designed by introducing a new coordinate transformation, and the proposed controller has the advantages of simple structure and good real-time performance. Finally, the effectiveness of the proposed MTN-based control approach is demonstrated by three examples.

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Authors and Affiliations

  1. School of Mathematics and Physics, Qingdao University of Science and Technology, Qingdao, 266061, China

    Yu-Qun Han, Wen-Jing He, Na Li & Shan-Liang Zhu

  2. The Research Institute for Mathematics and Interdisciplinary Sciences, Qingdao University of Science and Technology, Qingdao, 266061, China

    Yu-Qun Han, Wen-Jing He, Na Li & Shan-Liang Zhu

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Correspondence to Shan-Liang Zhu.

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This work was supported by the Shandong Provincial Natural Science Foundation, China (No. ZR2020QF055), and the Open Fund of the Key Laboratory of Ocean Circulation and Waves, Chinese Academy of Sciences (No. KLOCW2003).

Yu-Qun Han received his B.S. degree in mathematics and applied mathematics and an M.S. degree in applied mathematics from Qingdao University of Science and Technology, Qingdao, China, in 2010 and 2013, respectively, and a Ph.D. degree in control theory and control engineering form Southeast University, Nanjing, China, in 2018. He has been with the School of Mathematics and Physics, Qingdao University of Science and Technology, Qingdao, China, since December 2018. His current research interests include nonlinear system control, stochastic nonlinear system control, adaptive control and neural networks.

Wen-Jing He received her B.S. degree in applied statistics from Qingdao University of Science and Technology, Qingdao, China, in 2020. She is currently pursuing an M.S. degree in Qingdao University of Science and Technology. Her current research interests include adaptive control, neural networks and nonlinear systems.

Na Li received her B.S degree in applied statistics from Dezhou University, Dezhou, China, in 2019. She is currently pursuing an M.S. degree in Qingdao University of Science and Technology. Her current research interests include adaptive control, neural networks and nonlinear systems.

Shan-Liang Zhu received his Ph.D. degree in college of electromechanical engineering form Qingdao Science and Technology University in 2020 and an M.S. degree in the School of Mathematical Sciences from the Ocean University of China in 2004. He is currently an Associate Professor with Qingdao Science and Technology University. His research interests include differential dynamic system, data driven control, machine learning, and their applications.

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Han, YQ., He, WJ., Li, N. et al. Adaptive Tracking Control of a Class of Nonlinear Systems with Input Delay and Dynamic Uncertainties Using Multi-dimensional Taylor Network. Int. J. Control Autom. Syst. 19, 4078–4089 (2021). https://doi.org/10.1007/s12555-020-0708-y

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