Model-On-Demand

7.Rivera, D.E., H. Lee, H.D. Mittelmann, and M.W. Braun, “High purity distillation: using plant-friendly multisine signals to identify a strongly interactive process,” Special Section on Applications of System Identification, IEEE Control Systems Magazine, Vol. 28, No. 5, pgs. 72-89, October 2007.IEEE Xplore
6.Rivera, D.E., H. Lee, H.D. Mittelmann, G. Pendse, “Optimization-based design of plant-friendly input signals for data-centric estimation and control,” Annual AIChE Meeting, paper 242k, Cincinnati, OH, October 31-November 4, 2005.Preprint
5.Braun, M.W., R. Ortiz-Mojica, and D.E. Rivera, “Design of Minimum Crest Factor Multisinusoidal Signals for Plant-Friendly Identification of Nonlinear Process Systems,” Control Engineering Practice, Vol. 3, No. 3, pp. 301-313, March 2002.ScienceDirect
4.Braun, M.W., D.E. Rivera, and A. Stenman. “A Model-on-Demand Identification Methodology for Nonlinear Process Systems,” International Journal of Control, Vol.74, Issue.18, pp.1708-1717, December 2001.Taylor & Francis Online
3.Braun, M.W., Model-On-Demand Nonlinear Estimation And Model Predictive Control: Novel Methodologies For Process Control And Supply Chain Management, PhD Thesis, Control Systems Engineering Laboratory, Arizona State University, Dec. 2001.ASU Library
2. Braun, M.W., D.E. Rivera, and A. Stenman, “Model-on-Demand Model Predictive Control for Nonlinear Process Systems,” AIChE 2000 Annual Meeting, Los Angeles, CA, November 12-17, 2000, paper 256h.Presentation Record
1.Braun, M.W., B. McNamara, D.E. Rivera, and A. Stenman, “Model-on-Demand Identification for Control: An Experimental Study and Feasibility Analysis for MoD-based Predictive Control”, SYSID 2000, Santa Barbara, CA, June 21-23, 2000.Preprint