Robust estimation algorithm of altitude and vertical velocity for multirotor UAVs

Ga̧sior, Przemysław; Bondyra, Adam; Gardecki, Stanisław; Giernacki, Wojciech

doi:10.1109/mmar.2016.7575224

Cited by 7 publications

(8 citation statements)

References 10 publications

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“…Accurate vertical velocity estimates can be obtained by fusing the barometer and IMU measurements, 31,32 and are thus obtained separately, as will be addressed in a later discussion. Therefore, in this section we consider that v z is a known input, and instead use the following system…”

Section: Altitude Estimationmentioning

confidence: 99%

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Micro air vehicle local pose estimation with a two-dimensional laser scanner: A case study for electric tower inspection

Viña

Morin

2017

International Journal of Micro Air Vehicles

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Automation of inspection tasks is crucial for the development of the power industry, where micro air vehicles have shown a great potential. Self-localization in this context remains a key issue and is the main subject of this work. This article presents a methodology to obtain complete three-dimensional local pose estimates in electric tower inspection tasks with micro air vehicles, using an on-board sensor set-up consisting of a two-dimensional light detection and ranging, a barometer sensor and an inertial measurement unit. First, we present a method to track the tower's cross-sections in the laser scans and give insights on how this can be used to model electric towers. Then, we show how the popular iterative closest point algorithm, that is typically limited to indoor navigation, can be adapted to this scenario and propose two different implementations to retrieve pose information. This is complemented with attitude estimates from the inertial measurement unit measurements, based on a gain-scheduled non-linear observer formulation. An altitude observer to compensate for barometer drift is also presented. Finally, we address velocity estimation with views to feedback position control. Validations based on simulations and experimental data are presented.

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Section: Altitude Estimationmentioning

confidence: 99%

“…29,30 More recently, differential barometry has been gaining popularity. 31,32 In this configuration, a second barometer is set stationary on the ground and used as a reference measurement to track changes in local pressure, effectively reducing drift and increasing accuracy.…”

Section: Related Workmentioning

confidence: 99%

Micro air vehicle local pose estimation with a two-dimensional laser scanner: A case study for electric tower inspection

Viña

Morin

2017

International Journal of Micro Air Vehicles

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“…Performance and robustness analysis of the control system is carried out by employing numerical simulations, which take into account the presence of uncertainty in the plant model and external disturbances. The obtained results show the proposed controller design 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.Kalman filters (KF) [6,16,22,23], extended Kalman filters (EKF) [21][22][23][24] and complementary filters [4,25] among others.Several methods have been published to control the fly of SUAV [1,2,5,[9][10][11]13,17,[26][27][28][29][30][31][32][33][34][35][36][37][38][39], of which [17,30,31,33,[35][36][37][38][39] use PID (Proportional Integral Derivative) controllers for attitude, altitude and/or horizontal position. However, as MIMO (Multiple-input Multiple-output) systems, the tuning of PID controllers for multi-rotor vehicles is not an easy issue.…”

mentioning

confidence: 99%

“…Kalman filters (KF) [6,16,22,23], extended Kalman filters (EKF) [21][22][23][24] and complementary filters [4,25] among others.…”

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confidence: 99%

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

2019

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In this work, a new pre-tuning multivariable PID (Proportional Integral Derivative) controllers method for quadrotors is put forward. A procedure based on LQR/LQG (Linear Quadratic Regulator/Gaussian) theory is proposed for attitude and altitude control, which suposes a considerable simplification of the design problem due to only one pretuning parameter being used. With the aim to analyze the performance and robustness of the proposed method, a non-linear mathematical model of the DJI-F450 quadrotor is employed, where rotors dynamics, together with sensors drift/bias properties and noise characteristics of low-cost commercial sensors typically used in this type of applications are considered. In order to estimate the state vector and compensate bias/drift effects in the measures, a combination of filtering and data fusion algorithms (Kalman filter and Madgwick algorithm for attitude estimation) are proposed and implemented. Performance and robustness analysis of the control system is carried out by employing numerical simulations, which take into account the presence of uncertainty in the plant model and external disturbances. The obtained results show the proposed controller design 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.

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“…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 |…”

mentioning

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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Robust estimation algorithm of altitude and vertical velocity for multirotor UAVs

Cited by 7 publications

References 10 publications

Micro air vehicle local pose estimation with a two-dimensional laser scanner: A case study for electric tower inspection

Micro air vehicle local pose estimation with a two-dimensional laser scanner: A case study for electric tower inspection

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

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

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