Proportioning with second-order information for model predictive control
Optimization Methods and Software(2017)
摘要
We propose an algorithm for the effective solution of quadratic programming QP problems arising from model predictive control MPC. MPC is a modern multivariable control method which gives the solution for a QP problem at each sample instant. Our algorithm combines the active-set strategy with the proportioning test to decide when to leave the actual active set. For the minimization in the face, we use a direct solver implemented by the Cholesky factors updates. The performance of the algorithm is illustrated by numerical experiments, and the results are compared with the state-of-the-art solvers on benchmarks from MPC.
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关键词
quadratic programming,model predictive control,active-set strategy
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