His primary areas of study are Control theory, Electric power system, Control engineering, Mathematical optimization and Electronic engineering. His Control theory course of study focuses on Voltage and Dead time. The study incorporates disciplines such as Electric power industry, Power station, Marine engineering, Automotive engineering and Heuristics in addition to Electric power system.
Katsumi Uezato works mostly in the field of Control engineering, limiting it down to concerns involving Ultrasonic motor and, occasionally, Electric motor, Motor control, Servomotor and Electronic speed control. His Mathematical optimization study incorporates themes from Electric power, Power system simulation, Fuzzy logic and Nonlinear system. His Electronic engineering research includes elements of Boost converter, Buck converter, Maximum power point tracking and Photovoltaic system, Maximum power principle.
Katsumi Uezato focuses on Control theory, Control engineering, Electric power system, Ultrasonic motor and Synchronous motor. His study looks at the relationship between Control theory and fields such as Control, as well as how they intersect with chemical problems. His research investigates the link between Control engineering and topics such as Artificial neural network that cross with problems in Electric power.
The Electric power system study combines topics in areas such as Stability, Genetic algorithm, Mathematical optimization, Fuzzy logic and Transient. His research investigates the connection between Ultrasonic motor and topics such as Dead zone that intersect with issues in Compensation. His study in Synchronous motor is interdisciplinary in nature, drawing from both Permanent magnet synchronous generator, Voltage, Lyapunov function, Stator and Permanent magnet synchronous motor.
The scientist’s investigation covers issues in Control theory, Wind power, AC power, Renewable energy and Electrical engineering. The concepts of his Control theory study are interwoven with issues in Control engineering, Wind speed and Voltage. His work in Control engineering tackles topics such as Electric power system which are related to areas like Reduction and Weighting.
Many of his research projects under AC power are closely connected to Superconducting magnetic energy storage with Superconducting magnetic energy storage, tying the diverse disciplines of science together. His Renewable energy research is multidisciplinary, incorporating elements of Power station, Power control and Energy storage. His Energy storage research incorporates elements of Photovoltaic system and Heuristics.
His primary areas of investigation include Control theory, Renewable energy, AC power, Artificial neural network and Euclidean distance. The Synchronous motor and Torque research Katsumi Uezato does as part of his general Control theory study is frequently linked to other disciplines of science, such as Magnetic flux and Series, therefore creating a link between diverse domains of science. His Renewable energy research is multidisciplinary, relying on both Wind power, Induction generator and Power control, Power-flow study.
His Wind power research is multidisciplinary, incorporating perspectives in Electric power system, Hybrid power, Power station, Marine engineering and Automotive engineering. The various areas that Katsumi Uezato examines in his AC power study include Dead time and Inverter. His studies in Artificial neural network integrate themes in fields like Load forecasting, Microeconomics, Electricity and Econometrics.
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Neural-network-based maximum-power-point tracking of coupled-inductor interleaved-boost-converter-supplied PV system using fuzzy controller
M. Veerachary;T. Senjyu;K. Uezato.
IEEE Transactions on Industrial Electronics (2003)
A fast technique for unit commitment problem by extended priority list
T. Senjyu;K. Shimabukuro;K. Uezato;T. Funabashi.
IEEE Transactions on Power Systems (2003)
One-Hour-Ahead Load Forecasting Using Neural Networks
T. Senjyu;H. Takara;K. Uezato;T. Funabashi.
IEEE Transactions on Power Systems (2002)
A hybrid power system using alternative energy facilities in isolated island
T. Senjyu;T. Nakaji;K. Uezato;T. Funabashi.
IEEE Transactions on Energy Conversion (2005)
Voltage-based maximum power point tracking control of PV system
M. Veerachary;T. Senjyu;K. Uezato.
IEEE Transactions on Aerospace and Electronic Systems (2002)
An adaptive dead-time compensation strategy for voltage source inverter fed motor drives
N. Urasaki;T. Senjyu;K. Uezato;T. Funabashi.
IEEE Transactions on Power Electronics (2005)
A unit commitment problem by using genetic algorithm based on unit characteristic classification
T. Senjyu;H. Yamashiro;K. Uezato;T. Funabashi.
2002 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.02CH37309) (2002)
Feedforward maximum power point tracking of PV systems using fuzzy controller
M. Veerachary;T. Senjyu;K. Uezato.
IEEE Transactions on Aerospace and Electronic Systems (2002)
Adaptive Dead-Time Compensation Strategy for Permanent Magnet Synchronous Motor Drive
N. Urasaki;T. Senjyu;K. Uezato;T. Funabashi.
IEEE Transactions on Energy Conversion (2007)
Maximum power point tracking control of IDB converter supplied PV system
M. Veerachary;T. Senjyu;K. Uezato.
IEE Proceedings - Electric Power Applications (2001)
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