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Validation of Convex Optimization Algorithms and Credible Implementation for Model Predictive Control

Feron, Eric and Cohen, Raphaël P. and Davy, Guillaume and Garoche, Pierre-Loic Validation of Convex Optimization Algorithms and Credible Implementation for Model Predictive Control. (2017) In: AIAA SciTech Forum 2017, 9 January 2017 - 13 January 2017 (Gravepine, United States).

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Official URL: https://doi.org/10.2514/6.2017-0562

Abstract

Advanced real-time embedded algorithms are growing in complexity and length, related to the growth in autonomy, which allows vehicles to plan paths of their own. However, this promise cannot happen without proper attention to the considerably stronger operational constraints that real time, safety-critical applications must meet. This paper discusses the formal verification for optimization algorithms with a particular emphasis on receding-horizon controllers. Following a brief historical overview, a prototype autocoder for embedded convex optimization algorithms is discussed. Options for encoding code properties and proofs, and their applicability and limitations is detailed as well.

Item Type:Conference or Workshop Item (Paper)
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:French research institutions > Office National d'Etudes et Recherches Aérospatiales - ONERA (FRANCE)
Other partners > Georgia Institute of Technology (USA)
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Deposited On:18 Mar 2019 16:22

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