Title :
Fractional order chaotic system tracking design based on adaptive hybrid intelligent control
Author :
Lin, Tsung-Chih ; Kuo, Chia-Hao ; Balas, Valentina Emilia
Author_Institution :
Dept. of Electron. Eng., Feng-Chia Univ., Taichung, Taiwan
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.
Keywords :
adaptive control; chaos; drives; fuzzy neural nets; neurocontrollers; nonlinear control systems; tracking; adaptive hybrid fuzzy neural network controller; adaptive hybrid intelligent control; direct fuzzy neural network adaptive control effort; fractional order chaotic drive system; fractional order chaotic system tracking design; hybrid intelligent control scheme; indirect adaptive fuzzy neural network control effort; nonlinear fractional order chaotic response system; tracking performance; weighting factor; Adaptive systems; Approximation methods; Chaos; Fuzzy control; Fuzzy logic; Fuzzy neural networks; Trajectory; Fractional order chaotic systems; adaptive hybrid control; fuzzy neural network (FNN);
Conference_Titel :
Fuzzy Systems (FUZZ), 2011 IEEE International Conference on
Conference_Location :
Taipei
Print_ISBN :
978-1-4244-7315-1
Electronic_ISBN :
1098-7584
DOI :
10.1109/FUZZY.2011.6007356