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One Parameter Estimation-based Approximation-free Global Adaptive Control of Strict-feedback Nonlinear Systems

Ruizhen Gao, Haoqian Wang, Zongxiao Yue, and Mingyuan Yu*
International Journal of Control, Automation, and Systems, vol. 20, no. 6, pp.1943-1950, 2022

Abstract : In the existing works, as the number and the dimension of unknown system parameters increases, it normally requires more and more adaptive laws to estimate them, which may dramatically consume limitedly available computational resource and seriously increase large amount of computational time. In this paper, a novel approximation-free global adaptive backstepping control scheme is proposed for nonlinear systems. By estimating the maximum value of the norm (or absolute value) of those unknown parameters instead of unknown parameters themselves, the developed control shows that only one scalar parameter is needed to be updated online and therefore, the computational burden can be greatly reduced. Furthermore, the result is also extended to multi-input multi-output (MIMO) strict-feedback nonlinear systems. A simulation example is presented to demonstrate the efficacy of the proposed schemes.

Keyword : Global tracking, nonlinear systems, one parameter estimation, robust adaptive control.

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