Title :
Adaptive Inverse Control of Nonlinear Systems using PID Dynamic Neural Networks
Author :
Li, Ming ; Yang, Chengwu
Author_Institution :
Coll. of Power Eng., Nanjing Univ. of Sci. & Techonology
Abstract :
A new adaptive inverse control (AIC) system based on PID dynamic neural networks is presented in this paper. The system consists of two PID dynamic neural networks: one is applied to identifying the plant; the other approximates inverse model of the plant. A BPTM online learning algorithm for this system was described in detail. Simulation results show PID dynamic neural networks-based identifier and controller work well and the given BPTM online learning algorithm is efficient in the application of adaptive inverse control (AIC)
Keywords :
adaptive control; neurocontrollers; nonlinear control systems; three-term control; PID dynamic neural network; adaptive inverse control; nonlinear systems; online learning; Adaptive control; Adaptive systems; Control systems; Inverse problems; Neural networks; Nonlinear control systems; Nonlinear dynamical systems; Nonlinear systems; Programmable control; Three-term control; PID dynamic neural network; adaptive inverse control; nonlinear systems;
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
DOI :
10.1109/WCICA.2006.1712705
