Patrinos, Panagiotis and Bemporad, Alberto An accelerated dual gradient-projection algorithm for linear model predictive control. In: Proceedings of the IEEE 51st Annual Conference on Decision and Control (CDC), 2012. IEEE, 662 -667. ISBN 978-1-4673-2064-1 (2012)
Full text not available from this repository.Abstract
This paper proposes a dual fast gradient-projection method for solving quadratic programming problems that arise in linear model predictive control with general polyhedral constraints on inputs and states. The proposed algorithm is quite suitable for embedded control applications in that: (1) it is extremely simple and easy to code; (2) the number of iterations to reach a given accuracy in terms of optimality and feasibility of the primal solution can be estimated quite tightly; (3) the computational cost per iteration increases only linearly with the prediction horizon; and (4) the algorithm is also applicable to linear time-varying (LTV) model predictive control problems, with an extra on-line computational effort that is still linear with the prediction horizon.
| Item Type: | Book Section |
|---|---|
| Identification Number: | https://doi.org/10.1109/CDC.2012.6426458 |
| Additional Information: | 51st IEEE Conference on Decision and Control December 10-13, 2012. Maui, Hawaii, USA |
| Uncontrolled Keywords: | Acceleration; Convergence; Optimization; Prediction Algorithms; Predictive control; Tin; Vectors |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > TJ Mechanical engineering and machinery |
| Research Area: | Computer Science and Applications |
| Depositing User: | Ms T. Iannizzi |
| Date Deposited: | 12 Feb 2013 12:03 |
| Last Modified: | 12 Feb 2013 12:03 |
| URI: | http://eprints.imtlucca.it/id/eprint/1470 |
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