Multilayer feedforward networks are universal approximators
Neural Networks
Neural networks for control systems: a survey
Automatica (Journal of IFAC)
Adaptive Control
Nonlinear and Optimal Control Systems
Nonlinear and Optimal Control Systems
Nonlinear adaptive control using neural networks and multiple models
Automatica (Journal of IFAC)
Brief Nonlinear model-state feedback control for nonminimum-phase processes
Automatica (Journal of IFAC)
A direct adaptive neural-network control for unknown nonlinear systems and its application
IEEE Transactions on Neural Networks
A new method for the control of discrete nonlinear dynamic systems using neural networks
IEEE Transactions on Neural Networks
Adaptive inverse control of linear and nonlinear systems using dynamic neural networks
IEEE Transactions on Neural Networks
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Most self-tuning control algorithms for nonlinear systems become invalid when the controlled systems have nonminimum phase property. In this article, a direct neural network-based self-tuning control strategy is developed to deal with this problem under the certainty equivalence principle. Based on an equivalent linearized model from the local linearization, the controller structure is designed using a modified Clarke index with the guaranteed closed-loop stability and without the traditional requirement of the globally boundedness. For the system with unknown parameters, the controller is self-tuned by an on line RBF neural network identifier. Satisfactory simulations illustrate the effectiveness and adaptability of the proposed strategy even under system parameter variations.