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Missouri University of Science and Technology

2010

Optimal Control

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Full-Text Articles in Engineering

Decentralized State Feedback And Near Optimal Adaptive Neural Network Control Of Interconnected Nonlinear Discrete-Time Systems, Shahab Mehraeen, Jagannathan Sarangapani, Mariesa Crow Dec 2010

Decentralized State Feedback And Near Optimal Adaptive Neural Network Control Of Interconnected Nonlinear Discrete-Time Systems, Shahab Mehraeen, Jagannathan Sarangapani, Mariesa Crow

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, first a novel decentralized state feedback stabilization controller is introduced for a class of nonlinear interconnected discrete-time systems in affine form with unknown subsystem dynamics, control gain matrix, and interconnection dynamics by employing neural networks (NNs). Subsequently, the optimal control problem of decentralized nonlinear discrete-time system is considered with unknown internal subsystem and interconnection dynamics while assuming that the control gain matrix is known. For the near optimal controller development, the direct neural dynamic programming technique is utilized to solve the Hamilton-Jacobi-Bellman (HJB) equation forward-in-time. The decentralized optimal controller design for each subsystem utilizes the critic-actor structure …


Decentralized Nearly Optimal Control Of A Class Of Interconnected Nonlinear Discrete-Time Systems By Using Online Hamilton-Bellman-Jacobi Formulation, S. Mehraeen, Sarangapani Jagannathan Jan 2010

Decentralized Nearly Optimal Control Of A Class Of Interconnected Nonlinear Discrete-Time Systems By Using Online Hamilton-Bellman-Jacobi Formulation, S. Mehraeen, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, the direct neural dynamic programming technique is utilized to solve the Hamilton Jacobi-Bellman (HJB) equation online and forward-in-time for the decentralized nearly optimal control of nonlinear interconnected discrete-time systems in affine form with unknown internal subsystem and interconnection dynamics. Only the state vector of the local subsystem is considered measurable. the decentralized optimal controller design for each subsystem consists of an action neural network (NN) that is aimed to provide a nearly optimal control signal, and a critic NN which approximates the cost function. the NN weights are tuned online for both the NNs. It is shown …