Modeling for process control. Final report, February 15, 1991--February 14, 1997
Explosive developments have taken place in the control field during the last decade. In the content of this work, the authors mention three of these milestones: first, the industrial development and application of model predictive control (MPC), a technique especially suitable for multivariable highly interactive processes involving constraints on manipulated as well as controlled variables. Second, on the theory side, robust control emerged as the eminent paradigm. Robust control aims at analyzing the effects of model uncertainty on closed loop performance and to incorporate insensitivity to model uncertainty into the control system design procedure in a systematic fashion. And third, substantial advances have been made in the mathematical theory of the dynamics of nonlinear systems. Various nonlinear control techniques have grown out of this work which have excellent potential to address some difficult and long-standing process control problems. Specifically, the authors have been pursuing (1) the development of linear regression techniques for problems with collinear data and (2) the development of tools for robust model predictive control system design for constrained and nonlinear systems; in particular, they are trying to establish what model uncertainty descriptions are suitable for design.
- Research Organization:
- California Inst. of Tech., Control and Dynamical Systems, Pasadena, CA (United States)
- Sponsoring Organization:
- USDOE Office of Energy Research, Washington, DC (United States)
- DOE Contract Number:
- FG03-91ER14170
- OSTI ID:
- 666149
- Report Number(s):
- DOE/ER/14170--T1; ON: DE99000064
- Country of Publication:
- United States
- Language:
- English
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