Comparison of two quadrotor dynamic models

Rubio, José de Jesús; Cruz, Janethe; Zamudio, Zizilia; Salinas, Annel J.

doi:10.1109/tla.2014.6868851

Cited by 41 publications

(17 citation statements)

References 35 publications

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“…As we said previously, the present work uses the model structure exposed in [6], [12], [15] as a starting point. Figure 2 shows the Earth and Body reference frames.…”

Section: Analysis and Evaluation Model (Aem)mentioning

confidence: 99%

“…The inputs of the subsystem composed by the electronic speed controllers (ESC), the brushless motors, and the propellers are the duty-cycles values of the PWM signal applied to each ESC, D i , and its outputs are the thrust forces and torques developed by each rotor. Despite the model structure is based on that has been proposed by [6], [12], [15], its parameters have been identified to obtain a trustworthy model of these parts of the DJI F-450 quadrotor. The identification has been carried out applying step and ramp signals to the inputs (D i ) and recording the rotation frequencies, thrusts, and torques.…”

Section: Analysis and Evaluation Model (Aem)mentioning

confidence: 99%

“…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%

“…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. Several methods have been published to control the fly of SUAV [1,2,5,[9][10][11]13,14,[28][29][30][31][32][33][34][35].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

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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“…As we said previously, the present work uses the model structure exposed in [6], [12], [15] as a starting point. Figure 2 shows the Earth and Body reference frames.…”

Section: Analysis and Evaluation Model (Aem)mentioning

confidence: 99%

Section: Analysis and Evaluation Model (Aem)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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

Guardeño¹,

López²,

Sánchez³

2019

Preprint

View full text Add to dashboard Cite

show abstract

“…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][13]. The present work uses the model structure exposed in [6,12,14] as a starting point but, as a novel contribution, introduces a nonlinear mathematic model (obtained experimentally) 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

2019

View full text Add to dashboard Cite

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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Robust Trajectory‐Tracking Control of a PVTOL under Crosswind

Aguilar-Ibáñez

Sira‐Ramírez

Suárez-Castañón

et al. 2018

Asian Journal of Control

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This work proposes a robust controller to solve the trajectory-tracking control problem of planar vertical take-off and landing (PVTOL) aircraft under crosswind. The controller combines input-output feedback linearization and active disturbance rejection control techniques. The former linearizes the PVTOL dynamics and the latter actively estimates and compensates for the crosswind effects. Numerical simulations assess the effectiveness of the proposed approach.

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Comparison of two quadrotor dynamic models

Cited by 41 publications

References 35 publications

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

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

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

Robust Trajectory‐Tracking Control of a PVTOL under Crosswind

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