Neural Network Application To Optimal Control Of Nonlinear Systems
Author(s)
J. Kasac & B. Novakovic
Abstract
Neural network application to optimal control
of nonlinear systems
i 'j
J. Kasac & B. Novakovic
^Institute for Defense Studies, Research and Development, Croatia
^Faculty of Mechanical Engineering and Naval Architecture, University
of Zagreb, Croatia
Abstract
This paper presents the derivation of the numerical algorithm for optimal
control of nonlinear multivariable systems with control and state vectors
constraints. The algorithm derivation is based on the backpropagation-
through-time (BPTT) algorithm which is used as a learning algorithm for
recurrent neural networks. This approach is not based on Lagrange mul-
tiplier techniques and the calculus of variations. The derived algorithm is
used for the control of the cooperative work of two robots with two degrees
of freedom. The main problem is the determination of the control vectors
of robots for the transfer of rigid load from the initial state to the final one
in a fixed time while maintaining constant
Keywords
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