Adaptive Neural Dynamic Surface Control of Pure-Feedback Nonlinear Systems With Full State Constraints and Dynamic Uncertainties
| Autor: | Meizhen Xia, Yang Yi, Tianping Zhang, Qikun Shen |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
0209 industrial biotechnology
Adaptive control Artificial neural network 02 engineering and technology State (functional analysis) Upper and lower bounds Computer Science Applications Human-Computer Interaction Nonlinear system 020901 industrial engineering & automation Control and Systems Engineering Control theory Backstepping Bounded function 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Electrical and Electronic Engineering Software Mean value theorem Mathematics |
| Zdroj: | IEEE Transactions on Systems, Man, and Cybernetics: Systems. 47:2378-2387 |
| ISSN: | 2168-2232 2168-2216 |
| DOI: | 10.1109/tsmc.2017.2675540 |
| Popis: | In this paper, adaptive neural dynamic surface control (DSC) is developed using radial basis function neural networks (NNs) for a class of pure-feedback nonlinear systems with full state constraints and dynamic uncertainties. Based on a one-to-one nonlinear mapping, the pure-feedback system with full state constraints is transformed into a novel pure-feedback system without state constraints. The dynamic uncertainties are dealt with using a dynamic signal. Using modified DSC and mean value theorem as well as Nussbaum function, two adaptive NN control schemes are proposed based on the transformed system. The designed control strategy removes the conditions that the upper bound of the control gain is known, and the lower bounds and upper bounds of the virtual control coefficients are known. It is shown that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded, and the full state constraints are not violated. Two numerical examples are provided to illustrate the effectiveness of the proposed approach. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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