Information Sciences—Informatics and Computer Science: An International Journal - Special issue: Informatics and computer science intelligent systems applications
Automatica (Journal of IFAC)
Barrier Lyapunov Functions for the control of output-constrained nonlinear systems
Automatica (Journal of IFAC)
A correlation-test-based validation procedure for identified neural networks
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Automatica (Journal of IFAC)
Brief Paper: Design and performance analysis of a direct adaptive controller for nonlinear 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)
Robust adaptive control of nonlinear systems with unknown time delays
Automatica (Journal of IFAC)
Multilayer neural-net robot controller with guaranteed tracking performance
IEEE Transactions on Neural Networks
Direct adaptive NN control of a class of nonlinear systems
IEEE Transactions on Neural Networks
Nonlinear discrete time neural network observer
Neurocomputing
Sliding mode output-feedback stabilization of uncertain nonlinear nonaffine systems
Automatica (Journal of IFAC)
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This study presents a generalized procedure for designing recurrent neural network enhanced control of time-varying-delayed nonlinear dynamic systems with non-affine triangle structure and pure-feedback prototype. Under the framework, recurrent neural network is developed to accommodate the on-line approximation, which the weights of the neural network are iteratively and adaptively updated through system state vector. Based on the neural network online approximation model, an indirect adaptive neural network controller is designed, by means of dynamic compensation, to deal with some of the challenging issues encountered in such complex nonlinear control systems. Taking consideration of the correctness, rigorousness, and generality of the new development, the Lyapunov stability theory is referred to prove that the closed-loop control system is uniformly ultimately bounded stable and the output of the system is converged to a small neighborhood of the desired trajectory. Two bench mark tests are simulated to demonstrate the effectiveness and efficiency of the procedure. In addition these could be the show cases for potential readers/users to digest and/or apply the procedure to their ad hoc problems.