Predictive Control Strategy of Hydraulic Turbine Turning System Based on BGNN Neural Network

Authors:
Yijian Liu;Yanjun Fang
Affiliations:
Department of Automation, Wuhan University, China 430072 and School of Electrical & Automation Engineering, Nanjing Normal University, Jiangsu, China 210042;Department of Automation, Wuhan University, China 430072
Venue:
ISICA '08 Proceedings of the 3rd International Symposium on Advances in Computation and Intelligence
Year:
2008

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Abstract

A model predictive control (MPC) strategy based on a novel Bayesian-Gaussian neural network (BGNN) model was proposed for the controller design of hydraulic turbine in this paper. The BGNN was used to learn the nonlinear dynamic model of controlled hydraulic turbine on-line as the predictive model for the design of MPC controller. Experiments show that the proposed nonlinear MPC strategy based on BGNN performs much better than the conventional PID controller.