摘要：AbstractA recently proposed quadratic programming (QP) solver dedicated to bandstructured optimal control problems as they may arise in the field of model predictive control (MPC) is the dual Newton strategy, as implemented in the publicly available software qpDUNES. Such a structure-exploiting solver is often preferable over the use of condensing for problems with long horizons. In this paper, we propose an effcient and exible algorithm for real-time nonlinear MPC which tries to combine the advantages of the two approaches by means of a block condensing technique. Using a nontrivial benchmarking problem, we show that this approach can improve the performance of the dual Newton strategy by a factor of 10 in terms of total computation times while reducing the delay between state estimate and feedback even further. Additionally, an open-source implementation of the resulting scheme is provided as part of the ACADO code generation tool.
关键词：KeywordsNumerical methodspredictive controlquadratic programmingnonlinear systems
