Add to ORKGCaption title.Includes bibliographical references (leaf 23).Supported by an NSF graduate fellowship. Supported in part by the NSF. ECS-9216531 Supported in part by EPRI. RP8030-10Wesley McDermott and Michael Athans
Optimal control problems naturally arise in many scientific applications where one wishes to steer a...
The application of neural networks technology to dynamic system control has been constrained by the ...
4noNeural Approximations for Optimal Control and Decisionprovides a comprehensive methodology for t...
The purpose of this paper is to assess the capability of an artificial neural network (ANN) to imple...
This paper presents a method for developing control laws for nonlinear systems based on an optimal c...
Optimal control methods for linear systems have reached a substantial level of maturity, both in ter...
Recent research shows that supervised learning can be an effective tool for designing near-optimal f...
Dynamic programming is an exact method of determining optimal control for a discretized system. Unfo...
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2009.Ca...
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer S...
Recent research reveals that deep learning is an effective way of solving high dimensional Hamilton-...
The design of a feedback controller, so as to minimize a given performance criterion, for a general ...
In this thesis, the optimal control of a hypersonic vehicle in ascent through the atmosphere is deve...
Designing optimal feedback controllers for nonlinear dynamical systems requires solving Hamilton-Jac...
An optimal guidance law for a missile flight is one which determines appropriate controls to produce...
Optimal control problems naturally arise in many scientific applications where one wishes to steer a...
The application of neural networks technology to dynamic system control has been constrained by the ...
4noNeural Approximations for Optimal Control and Decisionprovides a comprehensive methodology for t...
The purpose of this paper is to assess the capability of an artificial neural network (ANN) to imple...
This paper presents a method for developing control laws for nonlinear systems based on an optimal c...
Optimal control methods for linear systems have reached a substantial level of maturity, both in ter...
Recent research shows that supervised learning can be an effective tool for designing near-optimal f...
Dynamic programming is an exact method of determining optimal control for a discretized system. Unfo...
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2009.Ca...
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer S...
Recent research reveals that deep learning is an effective way of solving high dimensional Hamilton-...
The design of a feedback controller, so as to minimize a given performance criterion, for a general ...
In this thesis, the optimal control of a hypersonic vehicle in ascent through the atmosphere is deve...
Designing optimal feedback controllers for nonlinear dynamical systems requires solving Hamilton-Jac...
An optimal guidance law for a missile flight is one which determines appropriate controls to produce...
Optimal control problems naturally arise in many scientific applications where one wishes to steer a...
The application of neural networks technology to dynamic system control has been constrained by the ...
4noNeural Approximations for Optimal Control and Decisionprovides a comprehensive methodology for t...