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Erschienen in:
2007 | OriginalPaper | Buchkapitel
Hard Constraints for Prioritized Objective Nonlinear MPC
verfasst von : Christopher E. Long, Edward P. Gatzke
Erschienen in: Assessment and Future Directions of Nonlinear Model Predictive Control
Verlag: Springer Berlin Heidelberg
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This paper presents a Nonlinear Model Predictive Control (NMPC) algorithm that uses hard variable constraints to allow for control objective prioritization. Traditional prioritized objective approaches can require the solution of a complex mixed-integer program. The formulation presented in this work relies on the feasibility and solution of a relatively small logical sequence of purely continuous nonlinear programs (NLP). The proposed solution method for accomodation of discrete control objectives is equivalent to solution of the overall mixed-integer nonlinear programming problem. The performance of the algorithm is demonstrated on a simulated multivariable network of air pressure tanks.