Hidenori Maruta

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The purpose of this paper is to present a new digital control method for dc-dc converters by reference modification with the neural network predictor. In the proposed method, the reference in the proportional control term of the conventional PID control is modified using the neural network predictor during the transient interval. The neural network is(More)
In extensive facilities such as port facilities, chemical plants, and power stations, it is important to detect a fire early and certainly. The purpose of this paper is to present a new smoke detection method in open areas, as smoke is considered as a significant signal of the fire. It is assumed that the camera monitoring the scene of the open area is(More)
Early and certain fire detection is one of the important issues to keep safe infrastructures. Especially, it becomes an urgent problem in large facilities like port facilities, large factories and power plants, due to its large harmful effect to surrounding areas. In these places, to detect the fire or flame directly is have some difficulties because they(More)
The purpose of this paper is to present a new digital control method of a forward type multiple-output dc-dc converter with both a P-I-D feedback and a new feed forward control. In this converter, a new method with a neural network predictor is presented. The dynamic characteristics of digital control dc-dc converter are improved as compared with the(More)
Smoke is an important sign for early fire detection. Image based detection methods are more useful than other methods which use some special sensor devices. When treating image information of smoke, it is important to consider characteristics of smoke. In this study, we consider that the image information of smoke is a self-affine fractal. We focus on the(More)
This paper proposes a novel prediction based digital control dc-dc converter. In this method, a neural network control is adopted to improve the transient response in coordination with a conventional P-I-D control. The prediction based control term is consists of predicted data which are obtained from repetitive training of the neural network. This works to(More)
The research on perception of motion has important applications for surveillance and autonomous robot navigation in dynamic environments. The issue of estimation of motion in depth is the crucial point of the problem of recognition 3D motion. In this paper, we propose a fixed monocular camera with focus changed cyclically to recognize the absolute(More)
Image based smoke detection is a difficult problem especially in open areas since it is heavily affected from its environmental objects. This comes from the transparent property of smoke itself. Therefore, to realize robust smoke detection in such situation, it needs to take into account the effect of the degree of transparency, the change of background(More)
Generally, the training based control method for dc-dc converters has a problem due to the fact that there is a difference of behavior between a controlled system before the training and one after the training. Therefore, when it is adopted to improve the transient response of dc-dc converter, it is needed to consider the bad effect of the training since(More)
As energy saving becomes important for sustainable society, one of the important social problems is to decrease the power consumption of the power converters such as those in renewable energy systems and information systems. In these application fields, the superior digital control method of power converter is needed. This paper presents a novel prediction(More)