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Nonlinear Horizon-One Model Predictive Control for Resource-Limited Applications | IEEE Conference Publication | IEEE Xplore

Nonlinear Horizon-One Model Predictive Control for Resource-Limited Applications


Abstract:

To reduce the computational footprint of model predictive control during online computation, a horizon-one scheme based on pre-computed inner-approximations of reach-able...Show More

Abstract:

To reduce the computational footprint of model predictive control during online computation, a horizon-one scheme based on pre-computed inner-approximations of reach-able sets is proposed. The inner-approximated reachable set allows to virtually predict the future system behavior over the full-horizon instead of repeatedly solving potentially large-scale optimal control problems. We provide theoretical proofs for recursive feasibility and asymptotic stability under mild assumptions. Furthermore, we illustrate how methods for sum-of-squares reachability analysis can be extended to meet these assumptions. The presented approach is demonstrated in simulation for functional verification and compared to other real-time methods from the literature.
Date of Conference: 10-12 July 2024
Date Added to IEEE Xplore: 05 September 2024
ISBN Information:

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Conference Location: Toronto, ON, Canada

References

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