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This work presents an application of tube-based model predictive control to aNonlinearMultirotor aircraftMultirotorAircraftFrameworkMultirotor aircraft  OptimizationmultirotorMultirotor aircraftAircraft subject to disturbances and model mismatch. The objective of this study is to design a robustRobust control strategy that ensures both stabilityStability and high-performancePerformance operation during trajectoryTrajectory trackingTracking. The strategy consists of two controllers: (i) a primary one that assumes a nominal model without disturbanceDisturbance to compute the optimalOptimal state and input trajectories, and (ii) an ancillary controllerController that maintains the real (disturbed) system trajectoryTrajectory in a tubeTube encompassing the nominal trajectory. To preserve closed-loop system performance, it is crucial to adequately define invariant sets for the disturbed system or an equivalent error system. In this work, we employ constrained polynomial zonotopes—an extension of classical zonotopesZonotopes—as a general non-convex representation based on a generator. This unique representation leverages group theory operationsOperations and reachabilityReachability algorithmsAlgorithm to compute accurate invariant sets, thereby enhancing the overall control strategy. A realistic quadcopter model is used to illustrate and discuss the performancePerformance of the proposed strategy.

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Tube-Based Nonlinear Model Predictive Control of Multirotor Aircraft Using a Polynomial Zonotopic Framework

  • 章节

  • 发表日期：

    2025年

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  • Gilles Delansnay,
  • Laurent Dewasme,
  • Alain Vande Wouwer

摘要

This work presents an application of tube-based model predictive control to aNonlinearMultirotor aircraftMultirotorAircraftFrameworkMultirotor aircraft  OptimizationmultirotorMultirotor aircraftAircraft subject to disturbances and model mismatch. The objective of this study is to design a robustRobust control strategy that ensures both stabilityStability and high-performancePerformance operation during trajectoryTrajectory trackingTracking. The strategy consists of two controllers: (i) a primary one that assumes a nominal model without disturbanceDisturbance to compute the optimalOptimal state and input trajectories, and (ii) an ancillary controllerController that maintains the real (disturbed) system trajectoryTrajectory in a tubeTube encompassing the nominal trajectory. To preserve closed-loop system performance, it is crucial to adequately define invariant sets for the disturbed system or an equivalent error system. In this work, we employ constrained polynomial zonotopes—an extension of classical zonotopesZonotopes—as a general non-convex representation based on a generator. This unique representation leverages group theory operationsOperations and reachabilityReachability algorithmsAlgorithm to compute accurate invariant sets, thereby enhancing the overall control strategy. A realistic quadcopter model is used to illustrate and discuss the performancePerformance of the proposed strategy.