His primary areas of investigation include Process control, Process, Process simulation, Control theory and Process plant. His Process control research includes elements of Database, Real-time computing and Control theory. His Step response and Slack variable study, which is part of a larger body of work in Control theory, is frequently linked to Set, bridging the gap between disciplines.
Terrence L. Blevins interconnects Model predictive control, Data efficiency, Computer data storage, Control engineering and Data warehouse in the investigation of issues within Process. His Process simulation research is multidisciplinary, incorporating elements of Representation and Fault detection and isolation. The Control theory study combines topics in areas such as Control and Limit.
Terrence L. Blevins mainly investigates Process control, Process, Control theory, Control theory and Control. His work in the fields of Process control, such as Process control network, intersects with other areas such as Set. His work on Process variable and Process simulation as part of his general Process study is frequently connected to Process plant and Value, thereby bridging the divide between different branches of science.
His Control theory study incorporates themes from Control engineering, Process output and Control signal. His Control engineering research integrates issues from Process control block, Setpoint and Automatic control. His Control theory research focuses on subjects like Signal, which are linked to Transmission.
Terrence L. Blevins focuses on Process control, Process, Big data, Control theory and In process control. His studies deal with areas such as Control, Real-time computing and Analytics as well as Process control. Terrence L. Blevins usually deals with Control and limits it to topics linked to Control engineering and Setpoint, Reset and Response time.
The concepts of his Process study are interwoven with issues in Algorithm and Data mining. His research in Big data intersects with topics in Controller and Field, Database. In his research, Control signal is intimately related to Process variable, which falls under the overarching field of Control theory.
Terrence L. Blevins spends much of his time researching Big data, Process, Process control, Real-time computing and Control. He has included themes like Controller and Output device in his Big data study. His Process research is multidisciplinary, relying on both Wireless, Field, Data mining and Model predictive control.
His biological study spans a wide range of topics, including Identifier, Analytics and Data processing. His Real-time computing study combines topics from a wide range of disciplines, such as Pipeline transport, Filter, Fault detection and isolation, Unsupervised learning and Signal processing. His Control study combines topics in areas such as Key and Capital cost.
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Diagnostic expert in a process control system
Trevor D. Schleiss;Mark Nixon;Terrence Lynn Blevins;Todd B. Brase.
Diagnostics in a process control system
Terrence L Blevins;Trevor D Schleiss;Wilhelm K Wojsznis;ケー． ウオズニス ウィルヘルム.
Integrated model predictive control and optimization within a process control system
Wilhelm K Wojsznis;Terrence L Blevins;Mark J Nixon.
Integrated, advanced control blocks in process control systems
Terrence L. Blevins;Wilhelm K. Wojsznis;Vasiliki Tzovla;Dirk Thiele.
Process plant monitoring based on multivariate statistical analysis and on-line process simulation
Blevins Terrence L;Mcmillan Gregory K;Nixon Mark J.
Integration of graphic display elements, process modules and control modules in process plants
Terrence Blevins;Mark Nixon;Michael Lucas;Arthur Webb.
Diagnostics in a process control system which uses multi-variable control techniques
Terrence L. Blevins;Mark J. Nixon;Wilhelm K. Wojsznis.
Multi-objective predictive process optimization with concurrent process simulation
Terrence Lynn Blevins;Wilhelm K Wojsznis;Mark J Nixon;Peter Wojsznis.
Economic calculations in a process control system
Marion A. Keyes;Mark J. Nixon;Terrence Lynn Blevins.
Smart process objects used in a process plant modeling system
Terrence Blevins;Mark Nixon;Ken Beoughter;Michael Lucas.
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