Title :
The Application of Wavelet Neural Network in Adaptive Inverse Control of Hydro-turbine Governing System
Author_Institution :
Coll. of Mech. & Electr. Eng., China Jiliang Univ., Hangzhou, China
Abstract :
Considering of the nonlinear, time-variable and non-minimum phase character and the easy variance of hydro-turbine governing system´s structure and parameters, a new adaptive inverse control method of hydro-turbine governing system based on the learning characteristic of neural network and the function approximation ability of the wavelet analysis is presented. It approximates the model and its inversion of plant by wavelet neural networks, and then through constructing an aim function of broad sense, a wavelet neural networks adaptive inverse law is put forward which is effective to the nonlinear non-minimum phase system. Theory and simulation to hydro-turbine governing system demonstrate that the control strategy can more effective improve the dynamic and stationary performance than those based on neural networks. It is showed the scheme is valid.
Keywords :
adaptive control; function approximation; hydroelectric generators; learning systems; machine control; neurocontrollers; turbines; wavelet transforms; adaptive inverse control method; function approximation; hydro-turbine governing system; learning characteristic; nonlinear nonminimum phase system; wavelet analysis; wavelet neural networks adaptive inverse law; Adaptive control; Adaptive systems; Analysis of variance; Control systems; Function approximation; Neural networks; Nonlinear control systems; Nonlinear dynamical systems; Programmable control; Wavelet analysis; adaptive inverse contro; hydro-turbine governing system; intelligent computation and control technique; wavelet neural networks;
Conference_Titel :
Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3835-8
Electronic_ISBN :
978-0-7695-3816-7
DOI :
10.1109/AICI.2009.178
