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Fast implementations and rigorous models: Can both be accommodated in NMPC?
2008
International Journal of Robust and Nonlinear Control
In less than two decades, Nonlinear Model Predictive Control (NMPC) has evolved from a conceptual framework to an attractive, general approach for the control of constrained nonlinear processes. These advances were realized both through better understanding of stability and robustness properties as well as improved algorithms for dynamic optimization. This study focuses on recent advances in optimization formulations and algorithms, particularly for the simultaneous collocation-based approach.
doi:10.1002/rnc.1250
fatcat:vl52vgx6kjg25j5iaorawr7x7a