Traffic Signal Timing with Neural Dynamic Optimization
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
On-Line Learning Control for Discrete Nonlinear Systems Via an Improved ADDHP Method
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
Reinforcement learning and adaptive dynamic programming for feedback control
IEEE Circuits and Systems Magazine
FRBF neural network and new Smith predictor for wireless networked control systems
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Adaptive neural controller design for synchronous generator based on heuristic dynamic programming
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Two coupled neural-networks-based solution of the Hamilton-Jacobi-Bellman equation
Applied Soft Computing
Application of dual heuristic programming in excitation system of synchronous generators
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part III
Book reviews: Neural networks for modeling and control of dynamic systems: a practitioner's handbook
Automatica (Journal of IFAC)
Book review: Stochastic controls-Hamiltonian systems and HJB equations
Automatica (Journal of IFAC)
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The paper presents neural dynamic optimization (NDO) as a method of optimal feedback control for nonlinear multi-input-multi-output (MIMO) systems. The main feature of NDO is that it enables neural networks to approximate the optimal feedback solution whose existence dynamic programming (DP) justifies, thereby reducing the complexities of computation and storage problems of the classical methods such as DP. This paper mainly describes the background and motivations for the development of NDO, while the two other subsequent papers of this topic present the theory of NDO and demonstrate the method with several applications including control of autonomous vehicles and of a robot arm, respectively