Prediction governors: Optimal solutions and application to electric power balancing control

This paper focuses on control systems with unknown reference signals, and considers a shaping problem of predicted reference signals under the situation that past actual reference signals are available. We first propose a signal shaping mechanism called prediction governor, and formulate an optimal design problem of prediction governors. The design problem finds a prediction governor such that the system composed of a given plant and the governor is an optimal approximation of a given ideal plant in the sense of input-output relation. Then, we analytically derive an optimal prediction governor which is characterized by plant parameters. Finally, the optimal prediction governor is applied to electric power demand prediction problem for power balancing control, and its usefulness is illustrated by a numerical example.