Abstract
This paper proposes real-time sequential convex programming (RTSCP), a method for solving a sequence of nonlinear optimization problems depending on an online parameter. We provide a contraction estimate for the proposed method and, as a byproduct, a new proof of the local convergence of sequential convex programming. The approach is illustrated by an example where RTSCP is applied to nonlinear model predictive control.
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© 2012 Springer-Verlag Berlin Heidelberg
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Quoc, T.D., Savorgnan, C., Diehl, M. (2012). Real-Time Sequential Convex Programming for Optimal Control Applications. In: Bock, H., Hoang, X., Rannacher, R., Schlöder, J. (eds) Modeling, Simulation and Optimization of Complex Processes. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25707-0_8
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DOI: https://doi.org/10.1007/978-3-642-25707-0_8
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