2018 - Fellow of the American Association for the Advancement of Science (AAAS)
2007 - IEEE Fellow For contributions to discrete event system modeling, control, diagnosis and applications
Supervisory control, Event, Theoretical computer science, Controllability and Control theory are his primary areas of study. Ratnesh Kumar brings together Supervisory control and Supervisor to produce work in his papers. His Theoretical computer science research is multidisciplinary, relying on both Discrete event dynamic system, Bounded function and Formal language.
Ratnesh Kumar has included themes like Nondeterministic algorithm and Algebra in his Controllability study. His Control theory research incorporates themes from Finite-state machine, Voltage droop and Automata theory. His work carried out in the field of Observability brings together such families of science as Event and Decentralised system.
His primary scientific interests are in Supervisory control, Control theory, Theoretical computer science, Event and Supervisor. The various areas that Ratnesh Kumar examines in his Supervisory control study include Discrete mathematics, Nondeterministic algorithm, Control system, Controllability and Event. His Controllability research includes elements of Dynamical systems theory and Observability.
His Control theory and Discrete event dynamic system study in the realm of Control theory interacts with subjects such as Event. He combines subjects such as Algorithm, Inference, Secrecy and Distributed computing with his study of Theoretical computer science. Ratnesh Kumar works mostly in the field of Algorithm, limiting it down to topics relating to Temporal logic and, in certain cases, Linear temporal logic.
The scientist’s investigation covers issues in Graphene, Optoelectronics, Algorithm, Set and Agricultural engineering. His research in Algorithm intersects with topics in Maximization, Leverage, Data-driven, Property and Relation. The Set study combines topics in areas such as Software architecture description, Generator, Cyber-physical system and Identification.
His work focuses on many connections between Software architecture description and other disciplines, such as Visualization, that overlap with his field of interest in Theoretical computer science. Ratnesh Kumar is involved in the study of Theoretical computer science that focuses on Automaton in particular. His Identification study combines topics from a wide range of disciplines, such as Tree, Industrial control system and Supervisory control.
His primary scientific interests are in Graphene, Vibration, Nanotechnology, Biosensor and Cantilever. His Graphene study incorporates themes from Microfluidics, Dispersion and Working electrode, Electrochemistry, Electrochemical gas sensor. His studies deal with areas such as Optoelectronics, Plasmon and Lithography as well as Microfluidics.
His Electrochemical gas sensor study integrates concerns from other disciplines, such as Electrochemical detection and Chromatography. His Vibration research is multidisciplinary, incorporating elements of Nanogenerator, Electronic circuit, Rectifier, Inductor and Impedance matching. His Nanotechnology research integrates issues from Optical fiber and Analyte.
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A polynomial algorithm for testing diagnosability of discrete-event systems
Shengbing Jiang;Zhongdong Huang;V. Chandra;R. Kumar.
IEEE Transactions on Automatic Control (2001)
Modeling and Control of Logical Discrete Event Systems
Ratnesh Kumar;Vijay K. Garg.
Decentralized failure diagnosis of discrete event systems
Wenbin Qiu;R. Kumar.
systems man and cybernetics (2006)
Formulas for calculating supremal controllable and normal sublanguages
R. D. Brandt;V. Garg;R. Kumar;F. Lin.
Systems & Control Letters (1990)
Failure diagnosis of discrete-event systems with linear-time temporal logic specifications
Shengbing Jiang;R. Kumar.
IEEE Transactions on Automatic Control (2004)
On controllability and normality of discrete event dynamical systems
Ratnesh Kumar;Vijay Garg;Steven I. Marcus.
Systems & Control Letters (1991)
Predicates and predicate transformers for supervisory control of discrete event dynamical systems
R. Kumar;V. Garg;S.I. Marcus.
IEEE Transactions on Automatic Control (1993)
Optimal sensor selection for discrete-event systems with partial observation
Shengbing Jiang;R. Kumar;H.E. Garcia.
IEEE Transactions on Automatic Control (2003)
Model Predictive Control-Based Real-Time Power System Protection Schemes
Licheng Jin;Ratnesh Kumar;Nicola Elia.
IEEE Transactions on Power Systems (2010)
Optimal Supervisory Control of Discrete Event DynamicalSystems
Ratnesh Kumar;Vijay K. Garg.
Siam Journal on Control and Optimization (1995)
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