| This session focuses on results in the area of process systems monitoring and identification. Topics of interest include, but are not limited to: data-driven and theoretical models applied monitoring, statistical methods for monitoring, design of input signals for these applications, information quality under conditions of inadequate and/or incomplete data, and monitoring nonlinear systems. Applications in nontraditional processes and systems are of particular interest. |
A Convex Programming Approach to Plant Friendly Input Design for System Identification
Sridharakumar Narasimhan, Chemical Engineering, Norwegian Univeristy of Science and Technology, Sem Sælands vei 4, Trondheim, 7491, Norway and Raghunathan Rengaswamy, Chemical Engg. Dept., Clarkson University, 8 Clarkson Avenue, Potsdam, NY 13699 |
Nonlinear System-Identification Using Subspace Algorithms For The Control Of Multiscale Process
Sivakumar Pitchaiah and Antonios Armaou, Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16801 |
Two-Stage Subspace Identification for High Performance Softsensor Design
Manabu Kano, Seunghyun Lee and Shinji Hasebe, Chemical Engineering, Kyoto University, Kyoto, 615-8510, Japan |
Further Evaluation On A Valve Stiction Detection Method – Its Capabilities And Limitations
Qinghua (Peter) He, Department of Chemical Engineering, Tuskegee University, Tuskegee, AL 36088 and Jin Wang, Department of Chemical Engineering, Auburn University, Auburn, AL 36849 |
Model Based Identification And Compensation For Hysteresis, Stiction And Varying Valve Dynamics Due To Process Disturbances
Srinivas Karra and M. Nazmul Karim, Chemical Engineering Department, Texas Tech University, Lubbock, TX 79409-3121 |
Improving Model Predictive Control Performance Using Disturbance Estimation And Systematic Kalman Filter Tuning
Bernt M. Åkesson, CAPEC, Department of Chemical Engineering, Technical University of Denmark, Søltofts Plads, Building 229, Kgs. Lyngby, DK-2800, Denmark, John Bagterp Jørgensen, Informatics and Mathematical modelling, Technical University of Denmark, Richard Petersens Plads, Bldg. 305, Kgs. Lyngby, DK-2800, Denmark, Niels Kjølstad Poulsen, Imformatics and Mathmatical Modelling, Technical University of Denmark, Building 321, Lyngby, 2800, Denmark and Sten Bay Jørgensen, Department of Chemical Engineering, Technical University of Denmark, CAPEC, Søltofts Plads, Kgs. Lyngby, DK 2800, Denmark |
Optimal Instrumentation Networks for Maximum Economic Value of Plant Operations
Duyquang Nguyen, University of Oklahoma, 100 E. Boyd St., T-335, Norman, OK 73019 and Miguel J. Bagajewicz, Chemical, Biological and Materials Engineering, University of Oklahoma, 100 E. Boyd St., T-335, Norman, OK 73019 |
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