Statistical Identification and Optimal Control of Marine Engine

Abstract

The authors presented a preliminary study on the optimal control of a marine engine in the last symposium. In this paper, they discuss some new results which were obtained after it. The first part of this paper is devoted to statistical identification problem of governor-propeller system. The identification is carried out to the data which was observed on a small training ship, using an auto regressive model. A salient feature of this data is that it was gained under almost no feedback control condition of marine diesel engine. Namely, the engine was controlled by a weak digital PI control, plus a strong random noise. They fit a statistical auto regressive model to this data and calculate a frequency response function, an impulse response function and a transfer function. The second part of this paper is devoted to an optimal control of the main engine. The authors has carried out many actual experiments at sea using the theory which were proposed in the last symposium. In this part, they report some important results about the actual tests and propose an entirely new ship control system in which a marine engine control, ship’s motions and steering motion are integrated.