Real-Time Sequential Convex Programming for Optimal Control Applications
HPSC(2011)
摘要
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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关键词
Model Predictive Control, Sequential Quadratic Programming, Interior Point Method, Nonlinear Model Predictive Control, Model Predictive Control Algorithm
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