A recursive delayed output-feedback control to stabilize chaotic systems using linear-in-parameter neural networks

作者：Yadmellat Peyman^*; Nikravesh S Kamaleddin Yadavar

来源：Communications in Nonlinear Science & Numerical Simulation, 2011, 16(1): 383-394.

DOI：10.1016/j.cnsns.2010.04.015

• Chaotic systems
• Delayed feedback control
• Intelligent control
• Neural networks

In this paper, a recursive delayed output-feedback control strategy is considered for stabilizing unstable periodic orbit of unknown nonlinear chaotic systems. An unknown nonlinearity is directly estimated by a linear-in-parameter neural network which is then used in an observer structure. An on-line modified back propagation algorithm with e-modification is used to update the weights of the network. The globally uniformly ultimately boundedness of overall closed-loop system response is analytically ensured using Razumikhin lemma. To verify the effectiveness of the proposed observer-based controller, a set of simulations is performed on a Rossler system in comparison with several previous methods.

• 出版日期2011-1