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Adaptive control of unknown plants using dynamical neural networks

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2 Author(s)
G. A. Rovithakis ; Dept. of Electron. & Comput. Eng., Tech. Univ. of Crete, Chania, Greece ; M. A. Christodoulou

In this paper, we are dealing with the problem of controlling an unknown nonlinear dynamical system. The algorithm is divided into two phases. First a dynamical neural network identifier is employed to perform “black box” identification and then a dynamic state feedback is developed to appropriately control the unknown system. We apply the algorithm to control the speed of a nonlinearized DC motor, giving in this way an application insight. In the algorithm, not all the plant states are assumed to be available for measurement

Published in:

IEEE Transactions on Systems, Man, and Cybernetics  (Volume:24 ,  Issue: 3 )