A. A. Pervozvanski
Russia, 195251, St.-Petersburg, Polytechnicheskaja st. 29,
St.-Petersburg
State Technical University,
Department of Mechanic and control proceses,
T. V. Varjadchenko
Russia, 195251, St.-Petersburg, Polytechnicheskaja st. 29,
St.-Petersburg
State Technical University,
Department of Mechanic and control proceses,
For a compensation of nonlinear interactions between subsystems in a complex control system, a neuroalgorithm is suggested. This algorithm is based on the local approximation method for a control function of phase variables. We consider the case of unknown dynamics where the values of "observations" used in the local estimates cannot be calculated a priori. A simple algorithm of the coefficient adjustment is suggested. As a basic example, control problems for simple robots are considered. Numerical experiments demonstrate that the performance index characterizing a difference between the "ideal control" and the ANN control can be diminished in many times for not too large number of elements.