Hydraulic Turbine Power Set Control Base On ANN And ADRC

Through the unknown perturbation and uncertain estimation of the system, and feedback the estimation to the control system, the active disturbance rejection controller thus realizes the dynamic feedback linearization of those dynamic systems. The ADRC theory is unique, and the method is simple, it suited to the non-linear an uncertain hydroelectric power sets.Have analyzing the tracking-differentiator(TD) I/O characteristic, to get a improving TD which output uninfluenced by the input. For the non-minimum phase characteristic of hydraulic turbine power set, this paper proposes and analyses the tracking-differentiator (TD) with invariable tracking time based on the idea of arranging the transient process. The rational transient process is set by the improving TD based on the classical PID controller, which effectively reduces undershoot of non-minimum phase system. The simulation result shows that it is efficacious when applied to the hydraulic turbine power set real power control.Have analyzing the characteristic of ADRC and ESO and compensate some changes of target by artificial neural networks to lighten the burden of ESO, thus get an stronger controller which base on ANN and ADRC. For the nonlinear and uncertain characteristic of hydraulic turbine power set, this paper combines the artificial neural networks (ANN) with ADRC theory and adjusts the structure of the controller according to the characteristic of the subject. The simulation result shows that the ADRC, which base on ANN are efficacious when applied to a hydraulic turbine power set which change largely and quickly.