DocumentCode :
694573
Title :
BP neural network control of single inverted pendulum
Author :
Zhang Pengpeng ; Zhang Lei ; Huang Yanhai
Author_Institution :
Coll. of Phys. & Electron., Henan Univ., Kaifeng, China
fYear :
2013
fDate :
12-13 Oct. 2013
Firstpage :
1259
Lastpage :
1262
Abstract :
The BP neural network can combine with Levenberg-Marquardt algorithm, which effectively overcomes the disadvantages of traditional neural network such as slow convergence speed, always converging to local minimum point and poor stability. Neural network capture the data of inverted pendulum with LQR optimal control method, set up multilayer forward feedback neural network. We through matlab simulate the control system to get the each state variable and control response curve of Single inverted pendulum. Experimental results show that the improved BP neural network can successfully control the inverted pendulum and have faster speed of control response and good stability than LQR optimal control.
Keywords :
feedforward neural nets; linear quadratic control; neurocontrollers; nonlinear control systems; recurrent neural nets; stability; BP neural network control; LQR optimal control; Levenberg-Marquardt algorithm; convergence speed; multilayer forward feedback neural network; single inverted pendulum; stability; Approximation algorithms; Biological neural networks; Control systems; Neurons; Stability analysis; Training; BPneural network; Levenberg-Marquardt algorithm; Single inverted pendulum;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Network Technology (ICCSNT), 2013 3rd International Conference on
Conference_Location :
Dalian
Type :
conf
DOI :
10.1109/ICCSNT.2013.6967331
Filename :
6967331
Link To Document :
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