PIDNN decoupling control of doubly fed hydro-generator system based on PSO method

The doubly fed hydro-generator system is a novel type of hydraulic generation system. Considering the performances of uncertain and nonlinear as well as parameters coupling and time-variation for three parts of water flux, hydro-turbine and generator, the doubly fed hydro-generator system is highly nonlinear, time-varying, large time delay and multi-variable strong coupling. To solve this problem, a multi-variable adaptive neural network decoupling controller with PID structure is introduced based on the principle of NN control and decoupling compensation. The decoupling and control capability of PIDNN decoupling controller are from the NN cross-tie structure and the nonlinear mapping properties. The weighs of the NN are learned and optimized by the particle swarm optimization (PSO) algorithm, which is known for its searching ability in the total parameter space concurrently and efficiently. These NN weights will not only eliminate the coupling relations between circuits, but also strengthen the PIDNN controller´s adaptability. By comparison with the conventional PID control, the results of simulation show that hydro-generator system is good robustness against system parameters uncertainly and load disturbance.