Title :
Stability Control of Inverted Pendulum Using Fuzzy Logic and Genetic Neural Networks
Author :
Yun Zhang ; Ming shuang Bi ; Xuemei Chen ; Wanqiang Qi
Author_Institution :
Sch. of Electr. & Inf. Eng., Changchun Inst. of Technol., Changchun, China
Abstract :
In this study, fuzzy logic is first proposed for nonlinear inverted-pendulum mechanism real time stability control. This kind of control can be observed as a coarse control action as fuzzy logic is rather easily applied. However, choosing the correct set of rules and scale factors is not an easy task in order to fine-tune the fuzzy controller for optimum performance. in this case, genetic algorithm and neural networks are used for fine improvement of the two controllers to overcome nonlinearity and unknown dynamics in the system.. Finally, the simulation experiments results show the superiority of the optimal controller.
Keywords :
control nonlinearities; fuzzy logic; genetic algorithms; neurocontrollers; nonlinear control systems; optimal control; pendulums; stability; coarse control action; fuzzy logic; genetic algorithm; genetic neural networks; nonlinear inverted pendulum mechanism real time stability control; nonlinearity; optimal controller; optimum performance; scale factors; unknown dynamics; Control systems; Educational institutions; Fuzzy logic; Genetics; Heuristic algorithms; Neural networks; Stability analysis; Fuzzy logic; Genetic algorithm; Inverted-pendulums mechanism; Neural networks; Stability Control;
Conference_Titel :
Computer Science & Service System (CSSS), 2012 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4673-0721-5
DOI :
10.1109/CSSS.2012.375
