Adaptive control of unknown plants using dynamical neural networks
George A. Rovithakis, M.A. Christodoulou · IEEE Transactions on Systems Man and Cybernetics · 1994
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.>