His main research concerns Control theory, Fuzzy control system, Adaptive control, Control system and Control engineering. His Control theory study frequently intersects with other fields, such as Stability. Fuzzy control system is a subfield of Fuzzy logic that Kevin M. Passino tackles.
His Adaptive control research incorporates elements of Artificial neural network, Foraging and Biomimetics. His study on Control system is mostly dedicated to connecting different topics, such as Intelligent control. His work in Control engineering tackles topics such as Mobile robot which are related to areas like Human–computer interaction.
Kevin M. Passino mainly investigates Control theory, Control engineering, Adaptive control, Fuzzy control system and Control theory. His study in Nonlinear system, Control system, Stability, Nonlinear control and Discrete time and continuous time is done as part of Control theory. Kevin M. Passino interconnects Expert system, Mobile robot, Fault tolerance, Control and Intelligent control in the investigation of issues within Control engineering.
His research integrates issues of Intelligent decision support system and Real-time Control System in his study of Intelligent control. His research in Adaptive control intersects with topics in Artificial neural network, Genetic algorithm, Exponential stability and Automatic control. His Fuzzy control system study necessitates a more in-depth grasp of Fuzzy logic.
Kevin M. Passino mainly focuses on Control theory, Swarm behaviour, Mathematical optimization, Artificial intelligence and Swarm intelligence. His Control theory study integrates concerns from other disciplines, such as Maximum power point tracking, Grid-connected photovoltaic power system and Control. Kevin M. Passino has researched Swarm behaviour in several fields, including Swarming, Discrete time and continuous time, Control engineering, Asynchronous communication and Double integrator.
His work focuses on many connections between Artificial intelligence and other disciplines, such as Cognitive science, that overlap with his field of interest in Artificial life and Ethology. His work in Observer addresses issues such as Kalman filter, which are connected to fields such as Control system. His Testbed research focuses on Intelligent control and how it relates to Simulation.
His primary scientific interests are in Mathematical optimization, Artificial intelligence, Swarm behaviour, Network topology and Equilibrium point. His Mathematical optimization research includes themes of Algorithm design, Game theory and Group. His work deals with themes such as Function minimization and Optimal foraging theory, Foraging, which intersect with Artificial intelligence.
His biological study spans a wide range of topics, including Swarming, Direct search, Relevance and Social foraging. The concepts of his Network topology study are interwoven with issues in Group cohesiveness, Cohesion, Nash equilibrium, Group dynamic and Monte Carlo method. His Equilibrium point research is multidisciplinary, incorporating perspectives in Node, Replicator equation and Optimization problem.
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Kevin M. Passino;Stephen Yurkovich.
Biomimicry of bacterial foraging for distributed optimization and control
IEEE Control Systems Magazine (2002)
Stability analysis of swarms
V. Gazi;K.M. Passino.
IEEE Transactions on Automatic Control (2003)
Stability analysis of social foraging swarms
V. Gazi;K.M. Passino.
systems man and cybernetics (2004)
Stable adaptive control using fuzzy systems and neural networks
J.T. Spooner;K.M. Passino.
IEEE Transactions on Fuzzy Systems (1996)
Stable Adaptive Control and Estimation for Nonlinear Systems: Neural and Fuzzy Approximator Techniques
Jeffrey T. Spooner;R. Ordonez;Manfredi Maggiore;Kevin M. Passino.
Stable Adaptive Control and Estimation for Nonlinear Systems
Jeffrey T. Spooner;Manfredi Maggiore;Raúl Ordóñez;Kevin M. Passino.
Biomimicry for Optimization, Control, and Automation
Kevin M. Passino.
A class of attractions/repulsion functions for stable swarm aggregations
Veysel Gazi;Kevin M. Passino.
International Journal of Control (2004)
Biomimicry of social foraging bacteria for distributed optimization: Models, principles, and emergent behaviors
Y. Liu;K.M. Passino.
Journal of Optimization Theory and Applications (2002)
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