This paper presents a systematic approach to plan and execute a time-efficient sailboat trajectory under the challenging stochastic wind conditions for automated sailboat. Unlike deterministic scenarios, stochastic wind disturbances introduce challenges such as gust unpredictability, directional shifts, and fluctuating apparent wind speeds. These characteristics render traditional planning methods, such as Line-of-Sight (LoS) and waypoint approaches, to be ineffective and not applicable, as they often rely on static or deterministic environmental models. This paper proposed a new path planner and controller based on nonlinear model predictive control method. It is compared with a baseline planner and controller. A Lie-algebraic analysis of the sailboat dynamics is carried out to identify the operating conditions under which the vessel loses first-order control authority in surge, and these conditions are embedded as constraints in the NMPC. Finally, simulation results are provided to validate the proposed framework.
The DMPC adopts an augmented state-space formulation based on control increments, which incorporates the estimated disturbances to eliminate steady-state tracking offsets while strictly enforcing physical actuator constraints, demonstrating reliable flight operation under realistic conditions.
Effective wind gust rejection and stable hovering are critical for the outdoor operation of autonomous drones. However, existing gust rejection methods are primarily reactive, inferring the disturbance from the resulting motion or measuring it at the airframe. Either way, the wind has already begun to act before it can...
Bas Meere, Eline Wisse, Laurens Vousten et al.· 0 citations
Trajectory tracking for flapping-wing microaerial vehicles (FWMAVs) is challenging due to inherent nonlinear dynamics and unsteady aerodynamics. While incremental model predictive control (IMPC) effectively manages constraints, its reliance on fixed weighting matrices limits performance during aggressive maneuvers. Con...
Zhong-Qi Lu, Zhi-Jie Liu, Hang Zhong et al.· IEEE Transactions on Neural...· 0 citations
To address the challenges of wind-induced uncertainty, decision inconsistency, and safety risks in quadrotor trajectory tracking, this study presents a Wind Adaptive Guidance Reinforcement Learning (WAGRL) framework. Unlike conventional controllers relying on fixed aerodynamic models, WAGRL integrates ensemble-based po...
This paper considers the formation of a navigation path for an unmanned aerial vehicle operating in a dynamic environment. The relevance of the study is determined by the need to ensure stable autonomous flight under external disturbances, navigation measurement uncertainty, and temporal delays in control processes. Th...
Mykola Voitekh, Vitaliy Nechyporuk· Electronics and Control Syst...· 0 citations
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