Neural Computing and Applications, ( ISI ), Volume (23), No (2), Year (2013-12) , Pages (2093-2100)

Title : ( Optimal control problem via neural networks )

Authors: Sohrab Effati , Morteza Pakdaman ,

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This paper attempts to propose a new method based on capabilities of artificial neural networks, in function approximation, to attain the solution of optimal control problems. To do so, we try to approximate the solution of Hamiltonian conditions based on the Pontryagin minimum principle (PMP). For this purpose, we introduce an error function that contains all PMP conditions. In the proposed error function, we used trial solutions for the trajectory function, control function and the Lagrange multipliers. These trial solutions are constructed by using neurons. Then, we minimize the error function that contains just the weights of the trial solutions. Substituting the optimal values of the weights in the trial solutions, we obtain the optimal trajectory function, optimal control function and the optimal Lagrange multipliers.


Pontryagin minimum principle  Optimal control problem  Artificial neural networks
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author = {Effati, Sohrab and Pakdaman, Morteza},
title = {Optimal control problem via neural networks},
journal = {Neural Computing and Applications},
year = {2013},
volume = {23},
number = {2},
month = {December},
issn = {0941-0643},
pages = {2093--2100},
numpages = {7},
keywords = {Pontryagin minimum principle  Optimal control problem  Artificial neural networks},


%0 Journal Article
%T Optimal control problem via neural networks
%A Effati, Sohrab
%A Pakdaman, Morteza
%J Neural Computing and Applications
%@ 0941-0643
%D 2013