D-Index & Metrics Best Publications

Heikki N. Koivo

Aalto University
Finland

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name Citations Publications World Ranking National Ranking

Engineering and Technology D-index 30 Citations 5,478 262 World Ranking 7762 National Ranking 47

Overview

What is he best known for?

The fields of study he is best known for:

Artificial intelligence
Electrical engineering
Control theory

His main research concerns Microgrid, Diesel generator, Optimization problem, Load management and Control theory. The Microgrid study combines topics in areas such as Turbine and Automotive engineering. His Turbine research focuses on Photovoltaic system and how it relates to Function and Simulation.

His work in Load management tackles topics such as Multi-objective optimization which are related to areas like Constrained optimization. His research in Control theory intersects with topics in Control engineering and Kinematics. Heikki N. Koivo has included themes like Process control, PID controller and Adaptive control in his Multivariable calculus study.

His most cited work include:

Paper: A multivariable self-tuning controller (279 citations)
Neural networks in process fault diagnosis (255 citations)
System modelling and online optimal management of MicroGrid using Mesh Adaptive Direct Search (236 citations)

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

His scientific interests lie mostly in Control theory, Control engineering, Control theory, Multivariable calculus and PID controller. The study incorporates disciplines such as Process and Power control in addition to Control theory. The various areas that Heikki N. Koivo examines in his Control engineering study include Automation, Process control, Expert system and Automatic control.

His Control theory research focuses on Self-tuning in particular. His Multivariable calculus study incorporates themes from Control and Structure. His Nonlinear system research focuses on subjects like Artificial neural network, which are linked to Fault and Data mining.

He most often published in these fields:

Control theory (33.70%)
Control engineering (27.90%)
Control theory (13.04%)

What were the highlights of his more recent work (between 2006-2018)?

Control engineering (27.90%)
Microgrid (6.16%)
Control theory (33.70%)

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

His primary areas of investigation include Control engineering, Microgrid, Control theory, Diesel generator and Simulation. In the subject of general Control engineering, his work in Adaptive control is often linked to Perspective, thereby combining diverse domains of study. Control theory, Nonlinear system, Networked control system, Control system and PID controller are subfields of Control theory in which his conducts study.

His Diesel generator study combines topics in areas such as Wind power, Turbine, Automotive engineering, Load management and Optimization problem. His research investigates the connection with Turbine and areas like Photovoltaic system which intersect with concerns in Function. His Automotive engineering research is multidisciplinary, incorporating elements of System model and Constrained optimization.

Between 2006 and 2018, his most popular works were:

System modelling and online optimal management of MicroGrid using Mesh Adaptive Direct Search (236 citations)
Online Management of MicroGrid with Battery Storage Using Multiobjective Optimization (111 citations)
Online management genetic algorithms of microgrid for residential application (86 citations)

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 networks in process fault diagnosis

T. Sorsa;H.N. Koivo;H. Koivisto.
systems man and cybernetics (1991)

481 Citations

Paper: A multivariable self-tuning controller

H. N. Koivo.
Automatica (1980)

418 Citations

System modelling and online optimal management of MicroGrid using Mesh Adaptive Direct Search

Faisal A. Mohamed;Heikki N. Koivo.
International Journal of Electrical Power & Energy Systems (2010)

395 Citations

Application of artificial networks in process fault diagnosis

Timo Sorsa;Heikki N. Koivo.
Automatica (1993)

240 Citations

Analysis of input-output clustering for determining centers of RBFN

Z. Uykan;C. Guzelis;M.E. Celebi;H.N. Koivo.
IEEE Transactions on Neural Networks (2000)

216 Citations

Online Management of MicroGrid with Battery Storage Using Multiobjective Optimization

Faisal A. Mohamed;Heikki N. Koivo.
international conference on power engineering, energy and electrical drives (2007)

195 Citations

APPLICATION OF ARTIFICIAL NEURAL NETWORKS IN PROCESS FAULT DIAGNOSIS

T. Sorsa;H.N. Koivo.
Fault Detection, Supervision and Safety for Technical Processes 1991#R##N#Selected Papers from the IFAC/IMACS Symposium, Baden-Baden, Germany, 10–13 September 1991 (1992)

194 Citations

Brief paper: Multivariable tuning regulators for unknown systems

J. Penttinen;H. N. Koivo.
Automatica (1980)

178 Citations

An observer theory for time delay systems

K. Bhat;H. Koivo.
IEEE Transactions on Automatic Control (1976)

171 Citations

Modal characterizations of controllability and observability in time delay systems

K. Bhat;H. Koivo.
IEEE Transactions on Automatic Control (1976)

154 Citations

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