Robust discrete-time sliding mode controller
Systems & Control Letters
Robust control of linear discrete-time systems
Systems & Control Letters
Adaptive Control Design and Analysis (Adaptive and Learning Systems for Signal Processing, Communications and Control Series)
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Brief Robust adaptive control of uncertain discrete-time systems
Automatica (Journal of IFAC)
Nonlinear adaptive control using neural networks and multiple models
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Adaptive NN control for a class of strict-feedback discrete-time nonlinear systems
Automatica (Journal of IFAC)
Adaptive sliding mode control for discrete-time multi-input multi-output systems
Automatica (Journal of IFAC)
Stable adaptive neurocontrol for nonlinear discrete-time systems
IEEE Transactions on Neural Networks
Output feedback control of a class of discrete MIMO nonlinear systems with triangular form inputs
IEEE Transactions on Neural Networks
Automatica (Journal of IFAC)
Hi-index | 0.00 |
In this paper, adaptive control is studied for a class of nonlinear discrete-time systems in parameter-strict-feedback form with both parametric and non-parametric uncertainties. The non-parametric uncertainty function is assumed to satisfy the Lipschitz condition. To achieve asymptotical tracking performance, estimation of both uncertainties is constructed. Future states are predicted to overcome the noncausal problem. Based on future states prediction and uncertainties estimation, a novel adaptive control is proposed. An augmented tracking error of equal growth order of the output tracking error is used in the parameter estimation law. The proposed adaptive control achieves asymptotical tracking performance and guarantees the boundedness of all closed-loop signals. The effectiveness of the proposed control law is demonstrated in the simulation.