Title :
Constrained optimal control of bilinear systems using neural network based HJB solution
Author :
Adhyaru, Dipak M. ; Kar, I.N. ; Gopal, M.
Author_Institution :
Dept. of Electr. Eng., Indian Inst. of Technol., New Delhi
Abstract :
In this paper, a Hamilton-Jacobi-Bellman (HJB) equation based optimal control algorithm is proposed for a bilinear system. Utilizing the Lyapunov direct method, the controller is shown to be optimal with respect to a cost functional, which includes penalty on the control effort and the system states. In the proposed algorithm, Neural Network (NN) is used to find approximate solution of HJB equation using least squares method. Proposed algorithm has been applied on bilinear systems. Necessary theoretical and simulation results are presented to validate proposed algorithm.
Keywords :
Lyapunov methods; least squares approximations; neurocontrollers; nonlinear control systems; optimal control; Hamilton-Jacobi-Bellman equation; Lyapunov direct method; bilinear systems; constrained optimal control; least squares method; neural network; Control systems; Cost function; Equations; Feedback control; Least squares methods; Lyapunov method; Neural networks; Nonlinear systems; Optimal control; Stability;
Conference_Titel :
Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1820-6
Electronic_ISBN :
1098-7576
DOI :
10.1109/IJCNN.2008.4634394
