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Tracking control of multi-input affine nonlinear dynamical systems with unknown nonlinearities using dynamical neural networks

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

The purpose of this paper is to design and rigorously analyze a tracking controller, based on a dynamic neural network model for unknown but affine in the control, multi input nonlinear dynamical systems, Lyapunov stability theory is used to guarantee a uniform ultimate boundedness property for the tracking error, as well as of all other signals in the closed loop. The controller derived is smooth. No a priori knowledge of an upper bound on the “optimal” weights and modeling errors is required. Simulation studies are used, to illustrate and clarify the theoretical results

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Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on  (Volume:29 ,  Issue: 2 )