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Energy‐Efficient Aerial Rendezvous Control of Electric Fixed‐Wing Uavs: A Hierarchical Multi‐Objective MPC Approach.

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Title: Energy‐Efficient Aerial Rendezvous Control of Electric Fixed‐Wing Uavs: A Hierarchical Multi‐Objective MPC Approach.
Authors: Zhang, Xiaotian1,2 (AUTHOR), He, Defeng3 (AUTHOR) hdfzj@zjut.edu.cn, Yang, Xu‐hua1 (AUTHOR)
Source: Optimal Control - Applications & Methods. Nov2025, Vol. 46 Issue 6, p2812-2828. 17p.
Subjects: Multi-objective optimization, Predictive control systems, Feedback control systems, Lithium cells, Energy consumption, Airplanes, Trajectory measurements
Abstract: This article proposes an energy‐efficient hierarchical multi‐objective model predictive control (MOMPC) strategy to address the aerial rendezvous problem of fixed‐wing unmanned aerial vehicles (UAVs) with aerial moving platforms. The study focuses on an electric fixed‐wing UAV (eUAV) powered by a Lithium‐Polymer (LiPo) battery, whose full dynamics are integrated with the kinematics of the aerial platform to establish a constrained rendezvous model. Based on this model, a hierarchical control architecture is developed to achieve dynamic trade‐offs between energy efficiency and rendezvous accuracy, while satisfying system‐level constraints and ensuring real‐time implementations. In the high‐layer, MOMPC is executed at a low frequency within a piecewise constant framework, where the multi‐objective problem with dynamically varying priorities is reformulated into two sequential lexicographic optimizations. The resulting optimal state trajectories are transmitted to the low‐layer controller, which operates at a higher frequency to ensure accurate trajectory tracking for aerial rendezvous. Additionally, a neural network‐based observer is embedded in the low‐layer to estimate and compensate for lumped disturbances. Theoretical analysis is provided to establish recursive feasibility and closed‐loop performance for both control layers. Simulation results validate the effectiveness of the proposed strategy in achieving accurate rendezvous with enhanced energy efficiency. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
Description
Abstract:This article proposes an energy‐efficient hierarchical multi‐objective model predictive control (MOMPC) strategy to address the aerial rendezvous problem of fixed‐wing unmanned aerial vehicles (UAVs) with aerial moving platforms. The study focuses on an electric fixed‐wing UAV (eUAV) powered by a Lithium‐Polymer (LiPo) battery, whose full dynamics are integrated with the kinematics of the aerial platform to establish a constrained rendezvous model. Based on this model, a hierarchical control architecture is developed to achieve dynamic trade‐offs between energy efficiency and rendezvous accuracy, while satisfying system‐level constraints and ensuring real‐time implementations. In the high‐layer, MOMPC is executed at a low frequency within a piecewise constant framework, where the multi‐objective problem with dynamically varying priorities is reformulated into two sequential lexicographic optimizations. The resulting optimal state trajectories are transmitted to the low‐layer controller, which operates at a higher frequency to ensure accurate trajectory tracking for aerial rendezvous. Additionally, a neural network‐based observer is embedded in the low‐layer to estimate and compensate for lumped disturbances. Theoretical analysis is provided to establish recursive feasibility and closed‐loop performance for both control layers. Simulation results validate the effectiveness of the proposed strategy in achieving accurate rendezvous with enhanced energy efficiency. [ABSTRACT FROM AUTHOR]
ISSN:01432087
DOI:10.1002/oca.70030