Fractional order chaotic system tracking design based on adaptive hybrid intelligent control

Abstract

In this paper, an adaptive hybrid fuzzy neural network (FNN) controller is proposed to achieve prescribed tracking performance of fractional order chaotic systems. Based on the trade-off between plant knowledge and control knowledge, a weighting factor can be adjusted by combining the indirect adaptive FNN control effort and the direct FNN adaptive control effort. Nonlinear fractional order chaotic response system is fully illustrated to track the trajectory generated from fractional order chaotic drive system. The numerical results show that tracking error and control effort can be made smaller and the proposed hybrid intelligent control scheme is more flexible during the design process.