Autonomous takeoff control system design for unmanned seaplanes

Du, Haibo; Fan, Guoliang; Yi, Jianqiang

doi:10.1016/j.oceaneng.2014.04.003

Cited by 11 publications

(5 citation statements)

References 26 publications

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“…A large diversity of real processes can be modeled using CARIMA models, for instance, unmanned seaplanes [29], stirred tank reactors [30], vehicle yaw [31], gas engines [32], and distillation columns [33,34]. Therefore, the development of control design techniques that are suitable for those models is relevant.…”

Section: Problem Statementmentioning

confidence: 99%

“…Statement (i) comes from the fact that, in the case of a precisely known system, the deadbeat control (Lemma 4) (1) Initialization: Define the model and the uncertainty set C, also the control parameters , , and , the reference signal and the initial conditions z. (2) ← 0 (3) Determine the matrix M according to (29). (4) while < max do (5) Calculate Λ and Λ, according to (24).…”

mentioning

confidence: 99%

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Stability Constraints for Robust Model Predictive Control

Ottoni

Takahashi

Raffo

2015

Mathematical Problems in Engineering

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This paper proposes an approach for the robust stabilization of systems controlled by MPC strategies. Uncertain SISO linear systems with box-bounded parametric uncertainties are considered. The proposed approach delivers some constraints on the control inputs which impose sufficient conditions for the convergence of the system output. These stability constraints can be included in the set of constraints dealt with by existing MPC design strategies, in this way leading to the “robustification” of the MPC.

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Section: Problem Statementmentioning

confidence: 99%

mentioning

confidence: 99%

Stability Constraints for Robust Model Predictive Control

Ottoni

Takahashi

Raffo

2015

Mathematical Problems in Engineering

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“…Then, Eubank 8 designed and built an autonomous unmanned seaplane for persistent ocean surveillance, which was equipped with solar energy system, autonomous control, and guidance system. Du, 9 Fan, 10 and Yi 11 developed autonomous takeoff control system for unmanned seaplane in recent years. Sazak and Kurtulus 12 conducted some research of hull-shaped fuselage for an amphibious UAV in 2016.…”

Section: Introductionmentioning

confidence: 99%

Preliminary design and performance analysis of a solar-powered unmanned seaplane

Liang¹,

Wang²,

Huang³

et al. 2019

Proceedings of the Institution of Mechanical Engineers, Part G:

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A solar-powered unmanned seaplane is proposed as a new strategy to avoid the challenges faced in a long nonstop solar-powered flight, and is especially designed for sea surveillance mission, like resource exploration, environmental monitoring, and observation of animal migration. A preliminary design of the solar-powered unmanned seaplane is carried out while its flight performance is analyzed later. The conceptual design of a twin-tail boom with large aspect ratio wings and buoyancy system is put forward. Aerodynamic loading of the wings is analyzed and determined by computational fluid dynamics. The energy balance models of the proposed seaplane system are created for the periods that the seaplane moors on the sea to harvest solar energy and flies in the sky to perform the mission. The parameter effects, such as wing loading, takeoff time, weight, cruise speed, takeoff ground distance, takeoff ground time, flight envelope, and endurance are discussed. The energy balance models shows that the proposed solar-powered seaplane can perform the sea surveillance mission at an altitude of around 8 km for months and seasons between latitude 60 ° N and 60 ° S.

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“…According to the proposed solution method, the use of more than one operating point provides more accurate trajectory tracking performance also in the aggressive maneuver. Another study is seen in [195]. The considered platform is an unmanned seaplane and a generalized predictive control algorithm is applied to its longitudinal dynamics for takeoff phase.…”

Section: B23 Pwa Modelsmentioning

confidence: 99%

“…Ocean hydrodynamic effects are taken into consideration together with nonlinear dynamics. Moreover, a trajectory tracking investigation by using certain linearized points is proposed in [195]. A detailed comparison between piecewise linear models and linear time-invariant models is examined in [196].…”

Section: B23 Pwa Modelsmentioning

confidence: 99%

Design, modeling, and predictive control of aerial physical interaction towards proactive maintenance

Koçer¹

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Modern cities are dependent on basic services like water and sewer systems including tunnels, which are supported by a pervasive infrastructure. The structural condition of these places is prone to deterioration. To protect the integrity of such systems, regular inspection is required to detect the onset of damage and material failure. It is envisaged that several robotic systems may provide a solution for the inspection task. When the inspection is purely visual, cameras might provide the necessary functionality. However, subsurface inspection may require a different approach. It is explored that unmanned aerial vehicle (UAV) with contacting probes may be an option.Deploying a UAV to perform contact inspection can be a more demanding task. First, the inspection tool shifts the center of mass and moment of inertias. Second, the terminal velocity needs to be regulated for a soft contact. This phase necessitates the system to be working in faster cycles as compared to the free-flight regime. Last challenge, posed by the interaction tool, comes from the sliding phase on the surface because bouncing occurs while it moves. In addition, ceiling effect where variable rotor wake degrades the performance of tracking predefined trajectory, and an unknown surface that must be included in the control algorithm and interaction tool design.The available approaches can handle the UAV control while it flies in free-flight. However, the challenges associated with the interaction require the system to be more responsive, adaptive and resilient. Since the level of interaction requires a force bound, the system has to explicitly consider this limit. The system needs to maintain the contact in a certain force range to collect the data while not crashing the sensor at the top. The current state of the art considering constraints makes use of two individual models for interaction problems; free-flight and contact phase models that bring additional complexity. Moreover, nominal optimization-based approaches are considered in the UAV control for the physical interaction tasks, wherein the system is lacking the ability to take external forces, changing parameters and unmodelled dynamics into account.In this thesis, a predictive UAV control is proposed to investigate interactions during the contact phase operation in close proximities to the surroundings. The main contribution of this study lies in two aspects: modeling and control of the UAV interaction problem. As opposed to multi-model approaches, a modeling of the whole system is presented with a centralized algorithm in which free flight, target approach, interaction, and sliding have been included. Additionally, a constraint optimization-based algorithm is designed to identify the external forces coming from the interaction tool and environment. It has shown through experiments that the proposed approach is efficient in terms of the optimized performance and applicability. The external force information increases the model size but the efficient open-source solver is adapted to lever...

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Autonomous takeoff control system design for unmanned seaplanes

Cited by 11 publications

References 26 publications

Stability Constraints for Robust Model Predictive Control

Stability Constraints for Robust Model Predictive Control

Preliminary design and performance analysis of a solar-powered unmanned seaplane

Design, modeling, and predictive control of aerial physical interaction towards proactive maintenance

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