Adaptive Neural Control of Uncertain MIMO Nonlinear Systems With State and Input Constraints

An adaptive neural control strategy for multiple input multiple output nonlinear systems with various constraints is presented in this paper. To deal with the nonsymmetric input nonlinearity and the constrained states, the proposed adaptive neural control is combined with the backstepping method, ra...

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Veröffentlicht in:	IEEE transaction on neural networks and learning systems 2017-06, Vol.28 (6), p.1318-1330
Hauptverfasser:	Ziting Chen, Zhijun Li, Chen, C. L. Philip
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptive control Barrier Lyapunov function (BLF) Basis functions Closed loop systems Computer simulation disturbance observer Disturbance observers Feedback control Liapunov functions MIMO MIMO (control systems) Neural networks neural networks (NNs) Nonlinear control Nonlinear systems Nonlinearity Observers Radial basis function Robot arms Robots state/input saturation constraints Uncertainty
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