The simulator-in-hardware: a low cost and hard real-time hardware-in-the-loop simulator for flying vehicles

Chiappinelli, Romain; Nahon, Meyer; Apkarian, Jacob

doi:10.1109/icuas48674.2020.9213963

Cited by 1 publication

(1 citation statement)

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“…The 'flat plate area', C D A, can be found experimentally by 13.407 s measuring the drag force as the quadrotor flies through a known air flow [38]. In [40], a C D A of 0.139 m 2 was found experimentally for the Spiri quadrotor platform, the platform that will be used for simulations in this thesis.…”

Section: Wind Disturbance Modelmentioning

confidence: 99%

Constrained Control Allocation Approaches in Trajectory Control of a Quadrotor Under Actuator Saturation

Tariq

Nahon

2020

2020 International Conference on Unmanned Aircraft Systems (ICUAS)

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Quadrotors are highly agile vehicles that can be used to perform aggressive maneuvers.Commanding a quadrotor to perform a maneuver that is beyond the physical capabilities of its actuators leads to actuator saturation. A prolonged state of saturated actuators can cause the vehicle to behave unpredictably. This work investigates the use of constrained control allocation methods in a cascaded control structure to mitigate the adverse effects of actuator saturation. More specifically, a constrained weighted least squares approach is used in the position controller and mixer to prioritize certain control efforts while considering constraints on the actuators and, optionally, vehicle attitude. Additionally, a yawdecoupled attitude controller is adopted to complement the control allocation method employed in the mixer. The proposed strategy offers a more comprehensive approach to addressing actuator saturation and was found to enhance the stability and tracking performance of the vehicle when compared to conventional approaches in simulation. Furthermore, waypoints-based motion planning is also investigated for generating trajectories that avoid actuator saturation, as opposed to 'handling' saturation as is done by the controllers and mixer. The trajectories are designed for a 'lawnmower maneuver' and are initially generated using a minimum snap optimization algorithm. However, this method does not consider actuator or state constraints, and thus avoiding constraint violations is not guaranteed. To address this, differential flatness properties are used to evaluate these trajectories to determine whether actuator and state constraints are violated.Time scaling is then used to adjust the trajectory to meet the constraints. The appropriate scale needed for time scaling can be obtained analytically or iteratively. Analytical i

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Section: Wind Disturbance Modelmentioning

confidence: 99%