Introduction to non-linear optimization
Introduction to non-linear optimization
Optimization theory with applications
Optimization theory with applications
Neural networks for control systems: a survey
Automatica (Journal of IFAC)
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Applied Optimal Control and Estimation
Applied Optimal Control and Estimation
Applied Numerical Methods with Software
Applied Numerical Methods with Software
Numerical Methods for Engineers: With Programming and Software Applications
Numerical Methods for Engineers: With Programming and Software Applications
Training trajectories by continuous recurrent multilayer networks
IEEE Transactions on Neural Networks
High-order neural network structures for identification of dynamical systems
IEEE Transactions on Neural Networks
Modeling and prediction with a class of time delay dynamic neural networks
Applied Soft Computing
A real-time neuro-adaptive controller with guaranteed stability
Applied Soft Computing
A symbol-based intelligent control system with self-exploration process
Engineering Applications of Artificial Intelligence
Epileptic seizure detection using dynamic wavelet network
Expert Systems with Applications: An International Journal
Adaptive self-scaling non-monotone BFGS training algorithm for recurrent neural networks
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
Adaptive controller based on wavelets neural network for a class of nonlinear systems
ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
Adaptive load frequency control with dynamic fuzzy networks in power systems
IWANN'05 Proceedings of the 8th international conference on Artificial Neural Networks: computational Intelligence and Bioinspired Systems
Time delay dynamic fuzzy networks for time series prediction
ICCS'05 Proceedings of the 5th international conference on Computational Science - Volume Part I
Classification of EMG signals using combined features and soft computing techniques
Applied Soft Computing
The modified self-organizing fuzzy neural network model for adaptability evaluation
LSMS'07 Proceedings of the 2007 international conference on Life System Modeling and Simulation
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The application of neural networks technology to dynamic system control has been constrained by the non-dynamic nature of popular network architectures. Many of difficulties are-large network sizes (i.e. curse of dimensionality), long training times, etc. These problems can be overcome with dynamic neural networks (DNN).In this study, intelligent optimal control problem is considered as a nonlinear optimization with dynamic equality constraints, and DNN as a control trajectory priming system. The resulting algorithm operates as an auto-trainer for DNN (a self-learning structure) and generates optimal feed-forward control trajectories in a significantly smaller number of iterations. In this way, optimal control trajectories are encapsulated and generalized by DNN. The time varying optimal feedback gains are also generated along the trajectory as byproducts. Speeding up trajectory calculations opens up avenues for real-time intelligent optimal control with virtual global feedback.We used direct-descent-curvature algorithm with some modifications (we called modified-descend-controller-MDC algorithm) for the optimal control computations. The algorithm has generated numerically very robust solutions with respect to conjugate points. The adjoint theory has been used in the training of DNN which is considered as a quasi-linear dynamic system. The updating of weights (identification of parameters) are based on Broyden-Fletcher-Goldfarb-Shanno BFGS method. Simulation results are given for an intelligent optimal control system controlling a difficult nonlinear second-order system using fully connected three-neuron DNN.