Stable adaptive systems
Nonlinear control systems: an introduction (2nd ed.)
Nonlinear control systems: an introduction (2nd ed.)
An extended direct scheme for robust adaptive nonlinear control
Automatica (Journal of IFAC)
Adaptive nonlinear control without overparametrization
Systems & Control Letters
Robust adaptive control
A robust adaptive nonlinear control design
Automatica (Journal of IFAC)
Nonlinear and Adaptive Control Design
Nonlinear and Adaptive Control Design
Adaptive Control
Automatica (Journal of IFAC)
Observer-based fuzzy adaptive control for strict-feedback nonlinear systems
Fuzzy Sets and Systems
IEEE Transactions on Neural Networks
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 Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on game theory
IEEE Transactions on Fuzzy Systems
Neural Computing and Applications - Special Issue on Theory and applications of swarm intelligence
Decentralized Output-Feedback Neural Control for Systems With Unknown Interconnections
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Stable adaptive control using fuzzy systems and neural networks
IEEE Transactions on Fuzzy Systems
Fuzzy adaptive sliding-mode control for MIMO nonlinear systems
IEEE Transactions on Fuzzy Systems
Adaptive neural network control for strict-feedback nonlinear systems using backstepping design
Automatica (Journal of IFAC)
Adaptive NN control of uncertain nonlinear pure-feedback systems
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)
Direct adaptive NN control of a class of nonlinear systems
IEEE Transactions on Neural Networks
Identification and control of dynamical systems using neural networks
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Robust Output Feedback Tracking Control for Time-Delay Nonlinear Systems Using Neural Network
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Adaptive Neural Control of Pure-Feedback Nonlinear Time-Delay Systems via Dynamic Surface Technique
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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This paper investigates the problem of global tracking control for a class of nonlinear systems in the strict-feedback form with unknown system functions. By using radial basis function neural networks (RBFNNs) to compensate for system uncertainties, a novel switching controller is developed by combining direct adaptive control approach and backstepping technique, which consists of a conventional adaptive neural controller dominating in the neural active region and an extra robust controller to pull back the transient outside the neural active region. The key features of the proposed algorithm are given as follows. First, a novel nth-order smoothly switching function is presented, and then an energy-efficient controller is obtained. Second, only a neural network (NN) is employed to compensate for all the unknown parts in each backstepping design procedure to reduce the number of adaptive parameters, so that a more simplified controller is proposed. Third, by exploiting a special property of the affine term, the developed strategy avoids the controller singularity problem completely without using projection algorithm. As a result of the above features, the developed control algorithm is convenient to implement in applications. Finally, the overall controller ensures that all the signals in the closed-loop system are globally uniformly ultimately bounded (GUUB) and the output of the system converges to a small neighborhood of the reference trajectory by properly choosing the design parameters. Three simulation examples are given to illustrate the effectiveness of the proposed control scheme.