Different linearization control techniques for a quadrotor system

Belkheiri, Mohammed; Rabhi, Abdelhamid; Pégard, C.

doi:10.1109/ccca.2012.6417914

Cited by 35 publications

(15 citation statements)

References 9 publications

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“…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]. In the present work, we propose a control law structure based on a combination of PID and LQR/LQG algorithms but, in contrast to those exposed in others works [5,[30][31][32][33][34][35], a modified LQR/LQG controller is used to obtain the optimal pre-tuning parameters of four PID controllers, commonly employed for attitude and altitude control in multirotor systems (hover maneuver).…”

Section: Introductionmentioning

confidence: 99%

“…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]. In the present work, we propose a control law structure based on a combination of PID and LQR/LQG algorithms but, in contrast to those exposed in others works [5,[30][31][32][33][34][35], a modified LQR/LQG controller is used to obtain the optimal pre-tuning parameters of four PID controllers, commonly employed for attitude and altitude control in multirotor systems (hover maneuver). Additionally, the uncertainty affecting the measurements are taken into account through the errors and noise modeling of a LIDAR, an optical flow camera, and a MEMS type MARG (Magnetic, Angular Rate, Gravity) sensor.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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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Section: Introductionmentioning

confidence: 99%

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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“…Many prior works in the area of quadrotor control, e.g., [3], [4], approximate the quadrotor dynamics by a linear system, for which standard linear controllers can be designed. More recent papers [5], [6], [7] use nonlinear control techniques like feedback linearization, backstepping, and sliding mode control.…”

Section: Introductionmentioning

confidence: 99%

Dynamic control of autonomous quadrotor flight in an estimated wind field

Sydney

Smyth

Paley

2013

52nd IEEE Conference on Decision and Control

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Abstract-We present a nonlinear, dynamic controller for a 6DOF quadrotor operating in an estimated, spatially varying, turbulent wind field. The quadrotor dynamics include the aerodynamic effects of drag, rotor blade flapping, and induced thrust due to translational velocity and external wind fields. To control the quadrotor we use a dynamic input/output feedback linearization controller that estimates a parametric model of the wind field using a recursive Bayesian filter. Each rotor experiences a possibly different wind field, which introduces moments that are accounted for in the controller and allows flight in wind fields that vary over the length of the vehicle. We add noise to the wind field in the form of Dryden turbulence to simulate the algorithm in two applications: autonomous ship landing and quadrotor proximity flight.

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“…The linear controllers were very sensitive to its parameter and even small changes in the parameterisation could lead to an unstable response. To solve the stabilisation problem of quadrotor, different linearisation control algorithms [4][5][6][7] have been proposed. These control techniques are restricted to control the certain condition like the hover flight condition.…”

Section: Linear Quadratic Regulator (Lqr) Control Techniquementioning

confidence: 99%

Tracking Control Design for Quadrotor Unmanned Aerial Vehicle

Nadda

Swarup

2017

Def. Sc. Jl.

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The model of a quadrotor unmanned aerial vehicle (UAV) is nonlinear and dynamically unstable. A flight controller design is proposed on the basis of Lyapunov stability theory which guarantees that all the states remain and reach on the sliding surfaces. The control strategy uses sliding mode with a backstepping control to perform the position and attitude tracking control. This proposed controller is simple and effectively enhance the performance of quadrotor UAV. In order to demonstrate the robustness of the proposed control method, White Gaussian Noise and aerodynamic moment disturbances are taken into account. The performance of the nonlinear control method is evaluated by comparing the performance with developed linear quadratic regulator and existing backstepping control technique and proportional-integral-derivative from the literature. The comparative performance results demonstrate the superiority and effectiveness of the proposed control strategy for the quadrotor UAV.

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Different linearization control techniques for a quadrotor system

Cited by 35 publications

References 9 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

Dynamic control of autonomous quadrotor flight in an estimated wind field

Tracking Control Design for Quadrotor Unmanned Aerial Vehicle

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