Nonlinear Predictive Control Design Of The Generator

It is very important for the national economics to improve and enhance the stability of the power system, so the stability research of the power system has been being focused for a long time. Researchers have done much works and got many accomplishments, but there are still many questions to be done. This paper applies the predictive control theory into the nonlinear control design of the generator, and proposes the new nonlinear predictive control law. The main works and the results are followsThe paper summarizes the research productions of the excitation control, the integrated control and the predictive control theory, and finds out the questions in the control design of the generator up to now. Aiming at the questions, in the initial stages, the paper applies the control design principium of Model Algorithmic Control (MAC) in the predictive theory to design the excitation control of the generator, and proposes the nonlinear predictive excitation control law based on MAC. In order to verify the valid of the control law, the paper compares it with the integral linear optimal excitation control law. In the further research, defining the offsets between the state variables and the reference tracks as the Target State Equation (TSE), the paper proposes the nonlinear predictive excitation control law of the generator based on TSE, and compares the law with the differential geometry control to verify its valid. Because the second control design method has better effects than the first one does, the paper applies it into the nonlinear integrated control design of the generator, and proposes the nonlinear predictive integrated control law. To verify its valid, the paper compares it with the differential geometry control.Altogether, the proposed control law not only can solve the coordinatedcontrol questions of the dynamic and the static performances of the system, and enhance the system stability, but also can improve the output characteristics of the generator.