A desiccant system is effective in reducing an energy consumption. However, the energy saving effect of the system in winter period is unexplained. Additionally, the complexity of desiccant system makes optimal control difficult. And so, the automatic control system is expected to solve this problem. In this study, we developed an automatic control system for Air-conditioner that makes Predict Mean Vote (PMV) thermal neutral and measured an electricity consumption of Air-conditioner and indoor environmental factors using the developed system. As a result, AC control by the developed system, PMV indicated within a range of ±0.3 that is same value in case of AC control with fixed preset temperature 24℃. Moreover, the energy consumption of the AC control by developed system was lower than AC control with fixed preset temperature 24℃. From the above, the developed system affected reducing heat load. Furthermore, an energy consumption of the desiccant system was calculated. As a result, the desiccant system was effective in case of more than three rooms controlling Air-conditioner.
In this paper, we propose a day-ahead scheduling method under uncertain renewable energy generation based on a machine learning approach. An aggregator, which has renewable energy generation devices, needs to schedule the energy production and consumption (prosumption) in a situation where the renewable power generation amount is not exactly predicted in day-ahead scheduling. If imbalance, defined as the difference between a day-ahead schedule and an actual prosumption profile, occurs, the aggregator is required to pay imbalance penalty costs. As a scheduling method to avoid paying imbalance penalty costs, we propose a scheduling model by machine learning based on the results of past transactions. In particular, we show that the problem of finding the parameters of the scheduling model is reduced to a convex program by introducing a parametric black-box scheduling model which is linear with respect to the parameters. Furthermore, we also show that the problem of finding the parameters is reduced to a linear program if the cost functions are convex and piecewise affine. In addition, it is also shown that the problem of finding the parameters is reduced to a quadratic program if the L2 regularization term is introduced. Finally, we show the efficiency of the proposed method through a numerical example.
In this paper, we propose a speed control method for automobiles based on the landing motion of seagulls. We assume that seagulls have flexible speed control capability because they can accurately land at the target position with smoothly decelerating. Therefore, if we can reproduce the landing motion of seagulls within the framework of general control method in the following steps, it can be expected to realize excellent speed control method for automobiles. In this study, we construct the control method based on the empirical data from the viewpoint of the inverse problem of optimal control. Then, we show the effectiveness of the proposed method as a control method of automobile decelerating and stopping compared with the existing method.
In human services that provide human-interpersonal services, it is known that experience at the service encounter affects customer's survival and that customers have loyalties to a service provider rather than to a shop. For this reason, it appears that management would be seriously damaged if the service providers leave their jobs or transfer to another shop. Therefore, it is helpful for managers to estimate turnover risks and transfer effects at a human service company. In this paper, we propose a methodology for simulation analysis of the influence of service-provider turnover and transfer in the human services business. Our methodology provides a modeling framework to build an operational simulation model for analyzing the risk of staff turnover and transfer in the human-services business, from the viewpoint of organizational cybernetics and computational organization theory. Our methodology also identifies the tasks required in the modeling process and provides guidelines for model validation and scenario analysis. We applied the proposed methodology to simulation analysis of the turnover and transfer impact of service providers in a hair salon company with several shops.
In this paper, we investigate energy-efficient control of data center air conditioning systems with outside air intakes. Taking account of the slow time constants inherent in the air conditioning systems, the present algorithm determines the current control actions, temperature set-points and intakes of the outside air, based on the predicted future values of physical quantities. To this end, we present an online modeling algorithm based on so-called just-in-time (JIT) modeling techniques with novel key variable selections based on both physical knowledge and data-based method, stepwise method. It is then shown that the future quantities are successfully estimated with an accuracy of correlation coefficient 0.97 or more. We then implement the present algorithm on a large-scale real data center and demonstrate that it successfully reduces the power consumption while meeting several operational constraints. Comparing the data over 2 months, the power consumption is shown to be reduced by 28.9% relative to a conventional method.
Auto flap gate is a water gate which realizes the automatic operation of cutoff and drainage by its buoyancy corresponding to the changes of water levels. The operation states of auto flap gate have been verified by visual obeservation of operator. However, it is difficult for operator to visually observe the operation states and manually operate the gate when it rains very heavily. Therefore, in this paper, a method to systematically judge the operation states of auto flap gate by using observation data of water levels and gate angle is newly proposed. First, a novel classification of eleven operation states is given. Secondly, an algorithm to judge the operation states is proposed, where theoretical gate angle to be utilized in the judgement is calculated based on the moments acting on the gate. In order to evaluate the effectiveness of the proposed method, an experiment by using an actual experimental equipment was performed. By comparing the judgement results based on the proposed method with visual observation, it was verified that the proposed method could successfully achieve the valid evaluation of the operation states.
Tracking performance of non-minimum phase systems under the continuous deadbeat condition is handled in this paper. It is well known that tracking performance is constrained and is difficult to achieve good transient response for the plant with unstable zeros. It seems that the deadbeat time and minimum undershoot by controller has some relation. In this paper, we derive analytical solution of a minimum undershoot for plants with one unstable zero when we want to achieve tracking control for the step reference. The effectiveness is illustrated using numerical simulations.
The Mendelsohn maneuver is one of dysphagia rehabilitation methods and is a swallowing maneuver which voluntarily prolongs laryngeal elevation. In general, the recognition of the laryngeal elevation is difficult for patients. They often need a long-time training to obtain the maneuver. However, showing onset and offset times of laryngeal elevation can promote effective rehabilitation. We propose a measurement device of the laryngeal elevation based on the change of the circumference of the neck. In this study, we develop a neckband-shaped device composed of stretchable strain sensors. The laryngeal elevation changes the neck circumference. The device partially measures the neck circumference. Two methods detect the onset and offset times of the laryngeal elevation. One determines the times from the difference of the time-series circumference of the neck. The other method determines the times from both the difference and a pattern matching. In experiments, 21 healthy subjects conducted 4-second laryngeal elevation in the Mendelsohn maneuver. Simultaneously, a speech-language-hearing therapist determined the times of the laryngeal elevation by palpating the subjects. The method of only the difference correctly detected the onset times. However, the offset times had over 1-second errors in some cases. The other method detected both the onset and offset times with short-time errors. We confirmed that the proposed device and the method with the difference and pattern matching have a potential for a biofeedback rehabilitation device.