Title :
Maximum entropy adaptive control of chaotic systems
Author :
Lin, Jiann-Horng ; Isik, Can
Author_Institution :
Dept. of Electr. & Comput. Eng., Syracuse Univ., NY, USA
Abstract :
We present an adaptive control strategy for controlling chaos in nonlinear dynamical systems. The proposed method is a neuro-fuzzy model as a globally coupled map based on entropy optimization, which combines an identified system fuzzy model and a control input update rule. The stability analysis of the resulting control scheme is shown by a property of contraction mappings. Numerical examples are given to illustrate the transition between chaotic states and stable equilibrium states
Keywords :
adaptive control; chaos; fuzzy control; intelligent control; maximum entropy methods; neurocontrollers; nonlinear dynamical systems; optimisation; stability; chaos control; chaotic states; chaotic systems; contraction mappings; control input update rule; entropy optimization; fuzzy model; globally coupled map; maximum entropy adaptive control; neuro-fuzzy model; stability analysis; stable equilibrium states; Adaptive control; Chaos; Control systems; Entropy; Fuzzy control; Fuzzy systems; Nonlinear control systems; Nonlinear dynamical systems; Optimization methods; Stability analysis;
Conference_Titel :
Intelligent Control (ISIC), 1998. Held jointly with IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA), Intelligent Systems and Semiotics (ISAS), Proceedings
Conference_Location :
Gaithersburg, MD
Print_ISBN :
0-7803-4423-5
DOI :
10.1109/ISIC.1998.713668
