Title :
Design and application of decoupled controller based on the BP neural network
Author :
Baoxia, Cui ; Deyuan, Sun
Author_Institution :
Sch. of Inf. Sci. & Eng., Shenyang Univ. of Technol., Shenyang, China
Abstract :
Composed by the neural network and traditional PID controller, a new BP neural network PID parameter self-adjustment decoupled controller is designed to realize the control of multi-input and multi-output systems in this paper, as well as to solve the problem such that the traditional PID controller can not achieve satisfied control effectiveness in multi-input and multi-output strong coupled control systems. The BP neural network PID controller is not only owning non-linear mapping capability, but also owning the PID capability of dealing with dynamical information. Because of the simple structure and algorithm, the BP neural network PID control method is more suitable for industry application.
Keywords :
MIMO systems; backpropagation; control system synthesis; neurocontrollers; self-adjusting systems; three-term control; BP neural network PID control method; BP neural network PID controller; BP neural network PID parameter self-adjustment decoupled controller; PID capability; dynamical information; industry application; multiinput and multioutput strong coupled control systems; multiinput and multioutput systems control; nonlinear mapping capability; Artificial neural networks; Couplings; Heuristic algorithms; Neurons; Process control; Temperature control; BP Neural Network; Decouple Control; MIMO System; PID Control;
Conference_Titel :
Control and Decision Conference (CCDC), 2011 Chinese
Conference_Location :
Mianyang
Print_ISBN :
978-1-4244-8737-0
DOI :
10.1109/CCDC.2011.5968779