Feedback linearization using neural networks
Automatica (Journal of IFAC)
Nonlinear and Adaptive Control Design
Nonlinear and Adaptive Control Design
Approximation-based control of nonlinear MIMO time-delay systems
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Brief paper: Novel adaptive neural control design for nonlinear MIMO time-delay systems
Automatica (Journal of IFAC)
Fuzzy adaptive observer backstepping control for MIMO nonlinear systems
Fuzzy Sets and Systems
A combined backstepping and small-gain approach to robust adaptive fuzzy output feedback control
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Adaptive neural network tracking control for a class of non-linear systems
International Journal of Systems Science
A DSC approach to robust adaptive NN tracking control for strict-feedback nonlinear systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on game theory
IEEE Transactions on Neural Networks
IEEE Transactions on Fuzzy Systems
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
Robust backstepping control of nonlinear systems using neural networks
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Online adaptive fuzzy neural identification and control of a class of MIMO nonlinear systems
IEEE Transactions on Fuzzy Systems
Time-delay systems: an overview of some recent advances and open problems
Automatica (Journal of IFAC)
Adaptive robust control of MIMO nonlinear systems in semi-strict feedback forms
Automatica (Journal of IFAC)
Stable neural controller design for unknown nonlinear systems using backstepping
IEEE Transactions on Neural Networks
Adaptive neural control of uncertain MIMO nonlinear systems
IEEE Transactions on Neural Networks
A Recurrent Neural Network for Hierarchical Control of Interconnected Dynamic Systems
IEEE Transactions on Neural Networks
NN based adaptive dynamic surface control for fully actuated AUV
ISNN'13 Proceedings of the 10th international conference on Advances in Neural Networks - Volume Part II
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In this paper, a novel adaptive NN control scheme is proposed for a class of uncertain multi-input and multi-output (MIMO) nonlinear time-delay systems. RBF NNs are used to tackle unknown nonlinear functions, then the adaptive NN tracking controller is constructed by combining Lyapunov-Krasovskii functionals and the dynamic surface control (DSC) technique along with the minimal-learning-parameters (MLP) algorithm. The proposed controller guarantees uniform ultimate boundedness (UUB) of all the signals in the closed-loop system, while the tracking error converges to a small neighborhood of the origin. An advantage of the proposed control scheme lies in that the number of adaptive parameters for each subsystem is reduced to one, triple problems of ''explosion of complexity'', ''curse of dimension'' and ''controller singularity'' are solved, respectively. Finally, a numerical simulation is presented to demonstrate the effectiveness and performance of the proposed scheme.