Cogeneration systems (CGSs) consist of power generators and thermally activated machines used to recover the thermal energy from the generators. The CGS optimal design problem is an optimal location problem of facilities that produce energy through two stages. Electric power and thermal energy are produced in the first stage and thermal energy is converted to effective energy in the second stage. An allocation of facilities is evaluated as the sum of the initial cost associated with the equipping of facilities and the minimum running cost entailed in satisfying the energy demand. Therefore, the CGS optimal design problem is a difficult problem that is composed of an optimal location problem and an optimal scheduling problem. In this paper, we present a mixed integer programming (MIP) formulation of the CGS optimal design problem. The proposed formulation enables us to use a general purpose MIP solver that is readily available. We show that realistic CGS optimal design problems arising in a hospital, a hotel and an office can be solved with reasonable computational costs.

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This paper considers synchronization of multiple plants over networks. The effect of time-varying transmission delay is compensated by a switching observer which uses the time-stamp information. To calculate the instantaneous value of transmission delay length via the time-stamp, the clocks of sending and receiving computers must be synchronized. It is shown that the correction of the difference of the quartz frequencies of the computers and the clock adjustment via NTP (Network Time Protocol) can provide the time synchronization within a required accuracy for moderate sampling periods. Proposed method is demonstrated by an experiment of synchronization of DC-motors over a real network.

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We propose a method of shape classification in rotating manipulation by a multi-fingered robot hand. A multi-fingered robot hand understands position and posture of a object and can realize suitable manipulations by classifying a shape of contact surface in rotating manipulation. Our method uses pressure distributed sensors equipped in fingers and consists of the following three processes. First, periodic pressure distributions are measured by a pressure distributed sensor in rotating manipulation. A kurtosis is calculated from each pressure distribution and can quantify a shape of contact surface in the moment. Secondly, a kurtosis pattern is cut out from a periodic kurtosis. Finally, a degree of similarity calculates between a kurtosis pattern and a reference pattern by DP matching method and classifies the shape of contact surface using thresholds. We confirm that our method classifies three objects with a high degree of accuracy and can keep the classification rate even in changing rotation velocity through laboratory experiments.

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This paper proposes a novel method to easily and effectively teach a mobile robot its path and to navigate it along the instructed path. First, an operator takes pictures at some significant points such as a start point, turning left/right points and a goal point at the teaching stage. At the same time, locations of these significant points are also obtained with a GPS receiver. Then, the operator teaches the robot its path by some simple instructions based on the pictures referred as reference images. Finally, at the autonomous navigation stage, the robot travels along the path with two navigation modes. One of them is landmark-based navigation, that is, the robot recognizes its headings and the significant points by detecting the landmarks indicated in the reference images when the robot is traveling near the significant points. Another mode is GPS-based navigation. The robot is navigated to near the significant points by GPS information when the robot is far from the significant points. Experiment conducted along a 620 meters long path indicates the effectiveness of the proposed method.

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