Adaptive nonlinear control without overparametrization
Systems & Control Letters
Feedback linearization using neural networks
Automatica (Journal of IFAC)
Adaptive robust control of SISO nonlinear systems in a semi-strict feedback form
Automatica (Journal of IFAC)
Nonlinear and Adaptive Control Design
Nonlinear and Adaptive Control Design
Robust adaptive fuzzy control and its application to ship roll stabilization
Information Sciences—Informatics and Computer Science: An International Journal - Special issue: Intelligent information systems and applications
Adaptive fuzzy control for strict-feedback canonical nonlinear systems with H∞ tracking performance
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Adaptive fuzzy robust tracking controller design via small gain approach and its application
IEEE Transactions on Fuzzy Systems
Robust adaptive neural control for a class of perturbed strict feedback nonlinear systems
IEEE Transactions on Neural Networks
International Journal of Systems, Control and Communications
A novel adaptive NN control for a class of strict-feedback nonlinear systems
ACC'09 Proceedings of the 2009 conference on American Control Conference
A simple adaptive fuzzy control for a class of strict-feedback SISO systems
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
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
Adaptive neural networks control on ship's linear-path following
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part V
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
DSC approach to robust adaptive NN tracking control for a class of SISO systems
ISNN'13 Proceedings of the 10th international conference on Advances in Neural Networks - Volume Part II
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A novel robust adaptive neural network control (RANNC) is proposed for a class of strict-feedback nonlinear systems with both unknown system nonlinearities and unknown virtual control gain nonlinearities. The synthesis of RANNC is developed by use of the input-to-state stability (ISS), the backstepping technique, and generalized small gain approach. The key feature of RANNC is that the order of its dynamic compensator is only identical to the order n of controlled system, such that it can reduce the computation load and makes particularly suitable for parallel processing. In addition, the possible controller singularity problem can be removed elegantly. Finally, simulation results are presented to validate the effectiveness of the RANNC algorithm.