Optimal Kalman Filter for state estimation of a quadrotor UAV

Xiong, Jing-Jing; Zheng, Enhui

doi:10.1016/j.ijleo.2015.07.032

Cited by 40 publications

(21 citation statements)

References 23 publications

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“…Theorem: Considering the dynamical model of the quadrotor and assuming all state information available, the sliding mode controller is designed as in (10), (11), (12), and (13). Under the sliding mode controller, the system will be asymptotically stable.…”

Section: Controller Designmentioning

confidence: 99%

“…In addition, the designed tlight controllers converge to their "steady" values and are bounded. Thus, the designed controllers (10), (11), (12), and (13) are able to stabilize the quadrotor UAV. This verifies the robustness of the control approach when faced with model parameter uncertainties.…”

Section: Simulationmentioning

confidence: 99%

“…In [11], a feedback linearization-based controller with high-order sliding mode ob server running parallel was applied to a quadrotor unmanned aerial vehicle. In [12], a optimal kaiman filtering method was studied to estimate the state vector of a small quadrotor UAV through incorporating the interna I disturbances including the white Gaussian process and measurement noises. The stability and tracking control problem of a quadrotor unmanned tlying robot vehicle in the presence of modeling error and disturbance uncertainty was addressed via a robust adaptive control algorithm [14].…”

Section: Introductionmentioning

confidence: 99%

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Sliding mode control for a quadrotor UAV with parameter uncertainties

Xiong

Zhang

2016

2016 2nd International Conference on Control, Automation and Robotics (ICCAR)

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ln this paper, we use the recently developed second order sliding mode control approach to design a robust flight controller for a small quadrotor unmanned aerial vehicle (UA V). Due to the underactuated property of a quadrotor UA V, the flight controller can make the quadrotor move three positions and the yaw angle to their desired values and stabilize the pitch and roll angles. The flight controller is designed to provide robust position and attitude tracking control of a quadrotor UA V with respect to model parameter uncertainties. Simulations show that the designed controller robustly stabilizes a quadrotor UAV.

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Section: Controller Designmentioning

confidence: 99%

Section: Simulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Sliding mode control for a quadrotor UAV with parameter uncertainties

Xiong

Zhang

2016

2016 2nd International Conference on Control, Automation and Robotics (ICCAR)

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“…Where, Drag force is generated by the friction in the air, and acts opposite to the relative motion of the aircraft (Xiong and Zheng, 2015). Drag force was calculated by using Equation 4: The agility could be an important issue for multirotors when they are scaled up in outdoor environments (Segui-Gasco et al, 2014).…”

Section: Flight Performance Stationmentioning

confidence: 99%

Unmanned Aerial Vehicle (UAV) assisted water sampling

Koparan

2016

2016 ASABE International Meeting

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Water quality assessment programs require the collection of water samples for physical, chemical, and bacteriological analysis. Lack of personnel, accessibility of water bodies, and time constraints for water sampling, especially after natural disasters and emergencies, are some of the challenges of water sampling. To overcome these challenges, a water collection mechanism was developed and mounted on a multirotor unmanned aerial vehicle (UAV) for autonomous water sampling from water bodies. The payload capacity and endurance of the UAV (hexacopter) were verified using an indoor test station. The hexacopter was equipped with floating foam, and the electronic components were coated against water damage in case of landing on water due to emergencies or water sampling. The system was able to collect water samples 48 times out of 73 autonomous flight missions from a pond. The unsuccessful missions were mainly due to the malfunctions of the servo motor used in water sampler's triggering mechanism. The servo motor for the mechanism was replaced to prevent the future malfunctions. UAV-assisted autonomous water sampling is a promising method for collection of water from water bodies. The system would be useful for collection of water samples from large lakes or difficult to access water sources. The details of the developed water sampling mechanism and the multirotor UAV, and experiment results are reported in this thesis.iii ACKNOWLEDGMENTS

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“…In order to achieve the required level of performance, the vehicle must include a proper automatic control system as well as electronics, sensors, communications, and signal processing algorithms. To develop and validate the control system is very useful to count with an accurate mathematical model of the vehicle, sensors and actuators dynamics [4][5][6][7][8][9][10][11][12]14]. The present work uses the model structure exposed in [6,12,15] as a starting point but, as a novel contribution, introduces a nonlinear time-varying mathematic model of the rotors used in the DJI F-450 quadrotor (Figure 1), that is used to perform a more detailed and realistic analysis of the control system through numerical simulations.…”

Section: Introductionmentioning

confidence: 99%

MIMO PID Controller Tuning Method for Quadrotor Based on LQR/LQG Theory

Guardeño¹,

López²,

Sánchez³

2019

Preprint

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In this work a new pre-tuning multivariable PID controllers method for quadrotors is put forward. A procedure based on LQR/LQG theory is proposed for attitude and altitude control. With the aim of analyzing performance and robustness of the proposed method, a non-linear mathematical model of the DJI-F450 quadrotor is employed, where rotors dynamics, togheter with sensors drift/bias properties and noise characteristics of low-cost comercial sensors typically used in this type of applications (such as MARG with MEMS technology and LIDAR) are considered. In order to estimate the state vector and compensate bias/drift effects on rate gyros of the MARG, a combination of filtering and data fusion algorithms (Kalman filter and Madgwick algorithm for attitude estimation) are proposed and implemented. Performance and robutsness analysis of the control system is carried out by means of numerical simulations, which take into account the presence of uncertainty in the plant model and external disturbances. The obtained results show that the proposed pre-tuning method for multivariable PID controller is robust with respect to: a) parametric uncertainty in the plant model, b) disturbances acting at the plant input, c) sensors measurement and estimation errors.One crucial concern to allow the indoor operation of a SUAV is the attitude and position estimation, typically based on the use of inertial measurement units (IMU) and cameras [6,8,[17][18][19][20][21]. To estimate the attitude, position and velocity state variables of the vehicle from the measurements provided by the sensors, a variety of methods are used, such as Kalman filters (KF) [6,18,22,23], extended Kalman filters (EKF) [23][24][25] and complementary filters [4,27] among others.Preprints (www.preprints.org) | NOT PEER-REVIEWED |

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Optimal Kalman Filter for state estimation of a quadrotor UAV

Cited by 40 publications

References 23 publications

Sliding mode control for a quadrotor UAV with parameter uncertainties

Sliding mode control for a quadrotor UAV with parameter uncertainties

Unmanned Aerial Vehicle (UAV) assisted water sampling

MIMO PID Controller Tuning Method for Quadrotor Based on LQR/LQG Theory

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