H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Electronics and Electrical Engineering D-index 31 Citations 5,991 161 World Ranking 3477 National Ranking 157

Overview

What is he best known for?

The fields of study he is best known for:

  • Control theory
  • Electrical engineering
  • Voltage

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.

His most cited work include:

  • Neural-network-based maximum-power-point tracking of coupled-inductor interleaved-boost-converter-supplied PV system using fuzzy controller (417 citations)
  • A fast technique for unit commitment problem by extended priority list (370 citations)
  • One-Hour-Ahead Load Forecasting Using Neural Networks (306 citations)

What are the main themes of his work throughout his whole career to date?

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.

He most often published in these fields:

  • Control theory (79.49%)
  • Control engineering (33.76%)
  • Electric power system (19.66%)

What were the highlights of his more recent work (between 2003-2008)?

  • Control theory (79.49%)
  • Wind power (7.26%)
  • AC power (5.13%)

In recent papers he was focusing on the following fields of study:

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.

Between 2003 and 2008, his most popular works were:

  • A hybrid power system using alternative energy facilities in isolated island (303 citations)
  • An adaptive dead-time compensation strategy for voltage source inverter fed motor drives (127 citations)
  • Next day load curve forecasting using hybrid correction method (119 citations)

In his most recent research, the most cited papers focused on:

  • Electrical engineering
  • Control theory
  • Voltage

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.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

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)

583 Citations

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)

558 Citations

One-Hour-Ahead Load Forecasting Using Neural Networks

T. Senjyu;H. Takara;K. Uezato;T. Funabashi.
IEEE Transactions on Power Systems (2002)

510 Citations

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)

420 Citations

Voltage-based maximum power point tracking control of PV system

M. Veerachary;T. Senjyu;K. Uezato.
IEEE Transactions on Aerospace and Electronic Systems (2002)

278 Citations

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)

203 Citations

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)

195 Citations

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)

186 Citations

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)

185 Citations

Maximum power point tracking control of IDB converter supplied PV system

M. Veerachary;T. Senjyu;K. Uezato.
IEE Proceedings - Electric Power Applications (2001)

180 Citations

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