Abstract
This work investigates a finite-time observer problem for a class of uncertain switched nonlinear systems in strict-feedback form, preceded by unknown hysteresis. By using a finite-time performance function, a finite-time switched state observer (FTSO) is derived using radial basis function neural networks (RBFNNs) to estimate the unmeasured states. An adaptive feedback neural network tracking control is derived based on the backstepping technique, which guarantees that all the signals of the closed-loop system are bounded, the output tracking error converges to zero, and the observer error converges to a prescribed arbitrarily small region within a finite-time interval. In addition, two simulation studies and an experiment test are provided to verify the feasibility and effectiveness of the theoretical finding in this study.
Highlights
In the past decades, great attentions and developments have been gained in nite-time adaptive control design, which developed a great number of typical design approaches in the literature
As stated in [33], they addressed the consensus tracking problem of a class of nonlinear multiagent system with hysteresis. They developed a distributed adaptive neural output feedback control scheme proposed by constructing a state observer and using the backstepping technique
(2) To the best of our knowledge, it is the first time that the finite-time convergence problem of observer error is taken into consideration in a class of uncertain switched nonlinear systems with unknown backlash-like hysteresis, by using a finite-time performance function to obtain a better tracking performance
Summary
Great attentions and developments have been gained in nite-time adaptive control design, which developed a great number of typical design approaches in the literature (see, e.g., [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15]). As stated in [33], they addressed the consensus tracking problem of a class of nonlinear multiagent system with hysteresis They developed a distributed adaptive neural output feedback control scheme proposed by constructing a state observer and using the backstepping technique. (2) To the best of our knowledge, it is the first time that the finite-time convergence problem of observer error is taken into consideration in a class of uncertain switched nonlinear systems with unknown backlash-like hysteresis, by using a finite-time performance function to obtain a better tracking performance. Is paper aims to derive an FTSO-based adaptive neural control signal v for nonlinear system (1) with unknown backlash-like hysteresis (2), so that the following objectives can be achieved:. For any inter i ≤ n, where φ(xi) [π1(xi), π2(xi), · · · , πN(xi)]T/ Nk 1πk(xi) and πk(xi) exp[− (xi − li)T(xi − li)/ 2c2i ]
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