The stability and control of discrete processes
The stability and control of discrete processes
Optimal control: linear quadratic methods
Optimal control: linear quadratic methods
Training multilayer perceptrons with the extended Kalman algorithm
Advances in neural information processing systems 1
Robust nonlinear control design: state-space and Lyapunov techniques
Robust nonlinear control design: state-space and Lyapunov techniques
Stability margins of nonlinear receding-horizon control via inverse optimality
Systems & Control Letters
Kalman Filtering and Neural Networks
Kalman Filtering and Neural Networks
Stabilization of Nonlinear Uncertain Systems
Stabilization of Nonlinear Uncertain Systems
Dual extended Kalman filtering in recurrent neural networks
Neural Networks
Simple and conditioned adaptive behavior from Kalman filter trained recurrent networks
Neural Networks - 2003 Special issue: Advances in neural networks research — IJCNN'03
A learning algorithm for continually running fully recurrent neural networks
Neural Computation
Output tracking with constrained inputs via inverse optimal adaptive recurrent neural control
Engineering Applications of Artificial Intelligence
Discrete time sliding mode control with application to induction motors
Automatica (Journal of IFAC)
Identification of finite state automata with a class of recurrent neural networks
IEEE Transactions on Neural Networks
Nonlinear maximum likelihood estimation of electricity spot prices using recurrent neural networks
Neural Computing and Applications
Swarm Stability and Optimization
Swarm Stability and Optimization
Discrete-Time Nonlinear HJB Solution Using Approximate Dynamic Programming: Convergence Proof
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Brief paper: The return difference for discrete-time optimal feedback systems
Automatica (Journal of IFAC)
Identification and control of dynamical systems using neural networks
IEEE Transactions on Neural Networks
Convergence Study in Extended Kalman Filter-Based Training of Recurrent Neural Networks
IEEE Transactions on Neural Networks
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This paper presents a robust inverse optimal neural control approach for stabilization of discrete-time uncertain nonlinear systems, which simultaneously minimizes a meaningful cost functional. A neural identifier scheme is used to model the uncertain system, and based on this neural model and an appropriate control Lyapunov function, then the robust inverse optimal neural controller is synthesized. Applicability of the proposed scheme is illustrated via simulation results for a synchronous generator model.