Optimization approaches to nonlinear model predictive control

Technical Report · Tue Jan 01 00:00:00 EST 1991

OSTI ID:5935850

Biegler, L T ^[1]; Rawlings, J B ^[2]

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1. Carnegie-Mellon Univ., Pittsburgh, PA (USA). Dept. of Chemical Engineering
2. Texas Univ., Austin, TX (USA). Dept. of Chemical Engineering

With the development of sophisticated methods for nonlinear programming and powerful computer hardware, it now becomes useful and efficient to formulate and solve nonlinear process control problems through on-line optimization methods. This paper explores and reviews control techniques based on repeated solution of nonlinear programming (NLP) problems. Here several advantages present themselves. These include minimization of readily quantifiable objectives, coordinated and accurate handling of process nonlinearities and interactions, and systematic ways of dealing with process constraints. We motivate this NLP-based approach with small nonlinear examples and present a basic algorithm for optimization-based process control. As can be seen this approach is a straightforward extension of popular model-predictive controllers (MPCs) that are used for linear systems. The statement of the basic algorithm raises a number of questions regarding stability and robustness of the method, efficiency of the control calculations, incorporation of feedback into the controller and reliable ways of handling process constraints. Each of these will be treated through analysis and/or modification of the basic algorithm. To highlight and support this discussion, several examples are presented and key results are examined and further developed. 74 refs., 11 figs.

• Research Organization: Argonne National Lab., IL (USA)
• Sponsoring Organization: USDOE; USDOE, Washington, DC (USA)
• DOE Contract Number: W-31109-ENG-38
• OSTI ID: 5935850
• Report Number(s): ANL/CP-72735; ON: DE91011178
• Country of Publication: United States
• Language: English

Related Subjects

42 ENGINEERING
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
PROCESS CONTROL
NONLINEAR PROGRAMMING
ALGORITHMS
CONTROL SYSTEMS
DIFFERENTIAL EQUATIONS
OPTIMIZATION
CONTROL
EQUATIONS
MATHEMATICAL LOGIC
PROGRAMMING
420200* - Engineering- Facilities
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& Techniques
990200 - Mathematics & Computers