Effect of Rotor Tilt on the Gust Rejection Properties of Multirotor Aircraft

Whidborne, James F.; Mendez, Arthur P.; Cooke, Alastair

doi:10.3390/drones6100305

Cited by 5 publications

(6 citation statements)

References 35 publications

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“…Although more comprehensive models for the C T and C P coefficients are common when modeling UAVs [34], a second-degree dependence on the advance ratio J of the form C T/P = c T/P,2 J 2 + c T/P,1 J + c T/P,0 was considered satisfactory for the purposes of this research, and the required parameters are provided in Appendix A.…”

Section: Propulsion Forces and Momentsmentioning

confidence: 99%

Experimental Nonlinear and Incremental Control Stabilization of a Tail-Sitter UAV with Hardware-in-the-Loop Validation

Athayde,

Moutinho,

Azinheira

2024

Robotics

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Tail-sitters aim to combine the advantages of fixed-wing aircraft and rotorcraft but require a robust and fast stabilization strategy to perform vertical maneuvers and transitions to and from aerodynamic flight. The research conducted in this work explores different nonlinear control solutions for the problem of stabilizing a tail-sitter when hovering. For this purpose, the first controller is an existing strategy for tail-sitter control obtained from the literature, the second is an application of Nonlinear Dynamic Inversion (NDI), and the last one is its incremental version, INDI. These controllers were implemented and tuned in a simulation in order to stabilize a model of the tail-sitter, complemented by estimation methods that allow the feedback of the necessary variables. These estimators and controllers were then implemented in a microcontroller and validated in a Hardware-in-the-Loop (HITL) scenario with simple maneuvers in vertical flight. Lastly, the developed control solutions were used to stabilize the aircraft in experimental flight while being monitored by a motion capture system. The experimental results allow the validation of the model of the X-Vert and provide a comparison of the performance of the different control solutions, where the INDI presents itself as a robust control strategy with accurate tracking capabilities and less actuator demand.

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Section: Propulsion Forces and Momentsmentioning

confidence: 99%

Experimental Nonlinear and Incremental Control Stabilization of a Tail-Sitter UAV with Hardware-in-the-Loop Validation

Athayde,

Moutinho,

Azinheira

2024

Robotics

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“…The expressions for the coefficients and mappings to various incidence angles, rotational speeds, and airspeeds are omitted here for brevity and since they are already detailed in previous related works, Refs. [ 37 , 38 , 39 ]. The airframe drag for the quadrotor is considered as follows:

where

is the airframe drag coefficient and

is the surface area of the airframe along each respective axes.…”

Section: Methods and Systemsmentioning

confidence: 99%

Wind Preview-Based Model Predictive Control of Multi-Rotor UAVs Using LiDAR

Mendez

Whidborne

Chen

2023

Sensors

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Autonomous outdoor operations of Unmanned Aerial Vehicles (UAVs), such as quadrotors, expose the aircraft to wind gusts causing a significant reduction in their position-holding performance. This vulnerability becomes more critical during the automated docking of these vehicles to outdoor charging stations. Utilising real-time wind preview information for the gust rejection control of UAVs has become more feasible due to the advancement of remote wind sensing technology such as LiDAR. This work proposes the use of a wind-preview-based Model Predictive Controller (MPC) to utilise remote wind measurements from a LiDAR for disturbance rejection. Here a ground-based LiDAR unit is used to predict the incoming wind disturbance at the takeoff and landing site of an autonomous quadrotor UAV. This preview information is then utilised by an MPC to provide the optimal compensation over the defined horizon. Simulations were conducted with LiDAR data gathered from field tests to verify the efficacy of the proposed system and to test the robustness of the wind-preview-based control. The results show a favourable improvement in the aircraft response to wind gusts with the addition of wind preview to the MPC; An 80% improvement in its position-holding performance combined with reduced rotational rates and peak rotational angles signifying a less aggressive approach to increased performance when compared with only feedback based MPC disturbance rejection. System robustness tests demonstrated a 1.75 s or 120% margin in the gust preview’s timing or strength respectively before adverse performance impact. The addition of wind-preview to an MPC has been shown to increase the gust rejection of UAVs over standard feedback-based MPC thus enabling their precision landing onto docking stations in the presence of wind gusts.

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“…Hence, the studies on the aerodynamics characteristics of the multirotor body and rotating propeller are carried out via wind tunnel tests [3] and Computational Fluid Dynamics (CFD) [4]. In addition, the mathematical modeling of the rotating propeller is developed by utilizing the established rotorcraft dynamics [5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

“…Various control methods have been designed to operate multirotor UAV for trajectory tracking problem or stabilizing its attitudes. Classic linear controller, Proportional-Integrator-Derivative (PID) controller, Linear Quadratic (LQ) controller [8,9], and nonlinear controller, backstepping control, nonliner dynamic inversion [1,10,11], are implemented in the multirotor UAV control problem. Among them, Sliding Mode Control (SMC) that is one of robust control methods is a promising approach to deal with uncertainties acting on the multirotor UAV flight such as implicit system fault, external wind and disturbances in a practical application.…”

Section: Introductionmentioning

confidence: 99%

“…The standard six Degree of Freedom (6DOF) dynamics is modeled by Newton's 2nd law and the air surrounding dynamics is derived considering the relative wind effect from initially referenced dynamics. The Blade Element Momentum Theory (BEMT) incorporating blade lelement theory and momentum theory is utilized on the thrust force modeling to investigate aerodynamic forces and moments acting on the multirotor UAV [6,8]. The conventional SMC is then designed by utilizing a cascaded control structure: position and attitude loops.…”

Section: Introductionmentioning

confidence: 99%

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Dynamics Modeling of Multirotor type UAV with the Blade Element Momentum Theory and Nonlinear Controller Design for a Wind Environment

Park,

Shin

2024

AIAA SCITECH 2024 Forum

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This paper presents an aerodynamics modeling of a rotary type Vertical Take-Off and Landing (VTOL) aircraft using the Blade Element Momentum Theory (BEMT). The BEMT is incorporated into the rigid body dynamics to describe main force and its reactive torque by rotor of the multirotor UAV. The dynamics modeling can demonstrate the motion of the multirotor UAV in the presence of gust or wind in an unsteady environment effectively. In order to operate the multirotor UAV, a robust nonlinear control technique is designed to track the desired command and stabilize the UAV subject to uncertainties such as modeling error, external disturbances. The hierarchical Sliding Mode Control (SMC) is adopted to organize a multi-loop structure: the outer-loop and inner-loop mode. Actual control input is distributed by physical configuration of the multirotor UAV with the described thrust and torque modeling by the BEMT in the control allocation. Numerical simulation evaluates the feasibility of the dynamic modeling of the multrirotor UAV with BEMT in the presence of external wind effects, which enables to understand a motion of rotary type UAV in a windy environment.

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Effect of Rotor Tilt on the Gust Rejection Properties of Multirotor Aircraft

Cited by 5 publications

References 35 publications

Experimental Nonlinear and Incremental Control Stabilization of a Tail-Sitter UAV with Hardware-in-the-Loop Validation

Experimental Nonlinear and Incremental Control Stabilization of a Tail-Sitter UAV with Hardware-in-the-Loop Validation

Wind Preview-Based Model Predictive Control of Multi-Rotor UAVs Using LiDAR

Dynamics Modeling of Multirotor type UAV with the Blade Element Momentum Theory and Nonlinear Controller Design for a Wind Environment

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