Computing-Predictor-Based MRACS for Nonlinear Time-Varying Power Plants Based on a New System Identification Method

Abstract This paper introduces an MRACS (Model Reference Adaptive Control System) developed by the authors, which can be applied to nonlinear time-varying plants. The feature of the proposed MRACS is that it uses a simulation model which has the same structure and parameters as the plant. Control signals, that makes the plant output follow specified reference outputs, are synthesized in a circuit called the “computing-predictor-network” in which prediction of state variables taken from the simulator is utilized. System identification and parameter estimation are also carried out by using a simulator with identical structure to the plant. The method used for system identification is the one developed to suit the proposed MRACS. In the paper, the concept of the proposed MRACS is introduced in the first place. Then the proposed system identification method is explained with an example of its application to the simulation model of the feedwater heater control system of a power plant. Finally, the control performance of the proposed MRACS is demonstrated with some results of simulation study, in which the steam temperature control system of a variable-pressure power plant is used.