Research on operation optimization of building energy systems based on machine learning

北九州市立大学博士(工学)本研究では、建築エネルギーシステムの運用を最適化するために機械学習を応用し、建築エネルギーシステムの運用コストを削減し、再生可能エネルギーの自給率を向上させることを重点的に扱っています。これらの一連の研究成果は、この分野に新たな知見をもたらし、建築エネルギーシステムの経済的効率を向上させるのに役立っています。In this study, we focus on applying machine learning to optimize the operation of building energy systems, with a primary emphasis on reducing the operational costs of these systems and enhancing the self-sufficiency of renewable energy. This series of research outcomes has brought new insights to the field and contributes to improving the economic efficiency of building energy systems.doctoral thesi

Precision Control of a Sensorless Brushless Direct Current Motor System

Sensorless control strategies were first suggested well over a decade ago with the aim of reducing the size, weight and unit cost of electrically actuated servo systems. The resulting algorithms have been successfully applied to the induction and synchronous motor families in applications where control of armature speeds above approximately one hundred revolutions per minute is desired. However, sensorless position control remains problematic. This thesis provides an in depth investigation into sensorless motor control strategies for high precision motion control applications. Specifically, methods of achieving control of position and very low speed thresholds are investigated. The developed grey box identification techniques are shown to perform better than their traditional white or black box counterparts. Further, fuzzy model based sliding mode control is implemented and results demonstrate its improved robustness to certain classes of disturbance. Attempts to reject uncertainty within the developed models using the sliding mode are discussed. Novel controllers, which enhance the performance of the sliding mode are presented. Finally, algorithms that achieve control without a primary feedback sensor are successfully demonstrated. Sensorless position control is achieved with resolutions equivalent to those of existing stepper motor technology. The successful control of armature speeds below sixty revolutions per minute is achieved and problems typically associated with motor starting are circumvented.Research Instruments Ltd

University catalog, 2018-19

Welcome to the University of Missouri 2018-2019 catalog! We are pleased to provide an interactive and searchable catalog online. The catalog is a comprehensive reference for your academic studies. It includes a list of all degree programs offered at MU, including bachelors, masters, specialists, doctorates, minors, certificates, and emphasis areas. It details the university wide requirements, the curricular requirements for each program, and in some cases provides a sample plan of study. The catalog includes a complete listing and description of approved courses. It also provides information on academic policies, contact information for supporting offices, and a complete listing of faculty members. Information in the catalog is current as of May 2018.--Page 17