Báo Cáo Non-linear dynamical systems control using neural networks

ABSTRACT
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Non-linear dynamical systems are difficult to control due to the model uncertainties and external
disturbances that may occur in these systems. This paper addresses the problem of modeling and online
direct inverse controlling method using neural networks for a given class of nonlinear systems.
The design procedure involves the integration of identification and neural control for an imprecisely
known plant. A new recurrent neural network approach for on-line adaptive control is presented. A
dynamic learning algorithm for the recurrent neutral network has been developed with faster
convergence and improved steady-state performance for two neural networks structure. On-line
simulation studies for selected process with the proposed control are presented and discussed using
two-link robot arm to demonstrate the performance of the proposed strategy.