Stochastic model predictive control of nonlinear continuous-time systems using the unscented transformation
Völz A, Graichen K (2015)
Publication Language: English
Publication Status: Published
Publication Type: Conference contribution, Conference Contribution
Publication year: 2015
Publisher: Institute of Electrical and Electronics Engineers Inc.
Pages Range: 3365-3370
Article Number: 7331054
Conference Proceedings Title: 2015 European Control Conference (ECC)
Event location: Linz
ISBN: 9783952426937
Abstract
The paper presents a stochastic model predictive control (MPC) scheme for nonlinear continuous-time stochastic systems with chance constraints. The approach uses the unscented transformation to predict the mean and covariance of the nonlinear continuous-time dynamics. Special emphasis is put on integrating the resulting unscented MPC formulation within a real-time gradient algorithm by exploiting the structure of the optimality conditions. The effectiveness of the approach is demonstrated for an automotive emergency braking scenario with collision avoidance.
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Germany (DE)How to cite
APA:
Völz, A., & Graichen, K. (2015). Stochastic model predictive control of nonlinear continuous-time systems using the unscented transformation. In 2015 European Control Conference (ECC) (pp. 3365-3370). Linz, AT: Institute of Electrical and Electronics Engineers Inc..
MLA:
Völz, Andreas, and Knut Graichen. "Stochastic model predictive control of nonlinear continuous-time systems using the unscented transformation." Proceedings of the European Control Conference, ECC 2015, Linz Institute of Electrical and Electronics Engineers Inc., 2015. 3365-3370.
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