Title :
Adaptive control of multi-variables nonlinear system based on artificial neural network
Author :
Gong, Dunwei ; Zhou, Yong
Author_Institution :
Coll. of Inf. & Electr. Eng., China Univ. of Min. & Technol., Jiangsu, China
Abstract :
In this paper, the adaptive control of a multivariable nonlinear system based on artificial neural networks is put forth. A three-layer diagonal recurrent neural network is used to identify the system. The neural net´s structure is simple, the number of networks is small and it can also identify the system better. A three-layer feedforward neural network is applied to control the system. The method to train neural network is simple, so it improves response speed to desired inputs. The strategy is applied to the control of a nonlinear dynamic system. Simulation studies show its efficiency
Keywords :
adaptive control; control system analysis; control system synthesis; feedforward neural nets; learning (artificial intelligence); multivariable control systems; neurocontrollers; nonlinear control systems; recurrent neural nets; adaptive control; control design; control simulation; multivariable nonlinear system; nonlinear dynamic system; response speed; three-layer diagonal recurrent neural network; three-layer feedforward neural network; training; Adaptive control; Artificial neural networks; Control systems; Feedforward neural networks; Feedforward systems; Neural networks; Neurons; Nonlinear control systems; Nonlinear systems; Recurrent neural networks;
Conference_Titel :
Industrial Electronics, 2001. Proceedings. ISIE 2001. IEEE International Symposium on
Conference_Location :
Pusan
Print_ISBN :
0-7803-7090-2
DOI :
10.1109/ISIE.2001.931756