کنفرانس بین المللی کنترل ، ابزار دقیق و اتوماسیون

صفحه اصلی / هشتمین کنفرانس بین المللی کنترل ، ابزار دقیق و اتوماسیون

Adaptive Optimal Control of Chaotic System Using Backstepping Neural Network Concept

نویسندگان :

Mohammad Sarbaz¹ MohammadReza Soltanian² Mohammad Manthouri³ Iman Zamani⁴

1- دانشگاه شاهد 2- دانشگاه شاهد 3- دانشگاه شاهد 4- دانشگاه شاهد

کلمات کلیدی :

Uncertain Chaotic System, Backstepping Concept, Neural Network, Variational Inequality

چکیده :

By the projection recurrent neural network-based adaptive backstepping control (PRNN-ABC), this paper stabilizes a class of uncertain chaotic system that includes unknown dynamics and disturbances. First, the backstepping control laws based on the nonlinear model is proposed. Second, the optimization problem studied by performance index and the control limitations. Third, the optimization problem is turned to a constrained quadratic programming (QP) in order to formulate recurrent neural network (RNN). later, the model of RNN is defined due to the Karush-Kuhn-Tucker (KKT) and the variational inequality concept. Finally, the stability of the closed-loop is investigated by Lyapunov function.