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Robust Control Co-Design with Receding-Horizon MPC
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Control co-design (CCD) is a technique for improving the closed-loop performance of systems through the coordinated design of both plant parameters and an optimal control policy. While model predictive control (MPC) is an attractive control strategy for many systems, embedding it within a CCD algorithm presents challenges because obtaining a closed-form solution for this receding-horizon optimization strategy is often not feasible. This paper meets that challenge by including a robust MPC formulation within the inner loop of a CCD algorithm. As exemplified by application to an aircraft thermal management system, the proposed algorithm closely matches the plant design of an open-loop benchmark. However, unlike the open-loop approach, the proposed algorithm can leverage MPC control variables designed a priori to achieve robust online operation under disturbance profiles that differ from those used for design.
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$\texttt{codesign-mcdp}$: A Python Library for Monotone Co-Design Problems
codesign-mcdp is a from-scratch Python implementation of monotone co-design problems — series/parallel/feedback composition, Kleene fixed-point solving, uncertainty and online learning — plus new, unproved temporal an...
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