LQR controller design for quad‐rotor helicopters

Okyere, Emmanuel; Bousbaine, Amar; Poyi, Gwangtim Timothy; Joseph, A. K.; Andrade, J.M.

doi:10.1049/joe.2018.8126

Cited by 87 publications

(54 citation statements)

References 3 publications

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“…Hence, in this research, the cost-function J e is used to tune the state-weighting factors. The iterative tuning procedure aids in fine-tuning the weighting factors [28]. A large state-weighting factor minimizes the state-errors but also increases the actuator's servo requirements of the actuator, and vice versa.…”

Section: Baseline Control Schemementioning

confidence: 99%

Self-tuning state-feedback control of a rotary pendulum system using adjustable degree-of-stability design

2020

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Section: Baseline Control Schemementioning

confidence: 99%

Self-tuning state-feedback control of a rotary pendulum system using adjustable degree-of-stability design

2020

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“…e difficulty of the high-speed stable trajectory control is the rapid correction of the attitude and the improvement of the response speed. Trajectory tracking controllers are often divided into attitude control and position control, which include linear controllers such as linear-quadratic regulator (LQR) [10,11] and nonlinear controllers such as sliding-mode technique [12], backstepping technique [13], and fuzzy-PID controller [14].…”

Section: Introductionmentioning

confidence: 99%

Stable High-Speed Quadrotor Flight using Differential Trajectory

Xie

et al. 2021

Mathematical Problems in Engineering

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This paper addresses the trajectory tracking control issue of a quadrotor with environmental disturbances, which particularly focuses on attitude correction during flight and response speed improvement. In this paper, the proposed control method uses the differential equation to transform the desired trajectory for improving the robustness of a quadrotor during high-speed flight. Meanwhile, a nonlinear controller based on the rotation matrix is designed to avoid singularities of Euler angles. The controller can also stabilize the position error to zero without reducing the control thrust when the attitude error is large. Finally, we conduct simulations on a tethered quadrotor to achieve high-speed flight in limited space. The simulation results show that the control method can stabilize a quadrotor at high-speed trajectory flight and keep a quadrotor stable when it is disturbed by aerodynamic drag and mass change.

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“…Hence, the attitude and altitude stability problems are the primary goals for most research in this sector. Some of the methods used to control the quadrotor platform are the proportional-integral-derivative (PID) control [1][2][3], linear quadratic regulator (LQR) control [4][5][6], sliding mode control [7][8][9], feedback linearization control [10][11][12], fuzzy logic (FL) [13][14][15] and backstepping control [16][17][18]. In this paper, the quadrotor helicopter's stability issue is regarded.…”

Section: Introductionmentioning

confidence: 99%

Optimal backstepping control of quadrotor UAV using gravitational search optimization algorithm

Basri

Noordin

2020

Bulletin EEI

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Quadrotor unmanned aerial vehicle (UAV) has superior characteristics such as ability to take off and land vertically, to hover in a stable air condition and to perform fast maneuvers. However, developing a high-performance quadrotor UAV controller is a difficult problem as quadrotor is an unstable and underactuated nonlinear system. The effort in this article focuses on designing and optimizing an autonomous quadrotor UAV controller. First, the aerial vehicle's dynamic model is presented. Then it is suggested an optimal backstepping controller (OBC). Traditionally, backstepping controller (BC) parameters are often selected arbitrarily. The gravitational search algorithm (GSA) is used here to determine the BC parameter optimum values. In the algorithm, the control parameters are calculated using an integral absolute error to minimize the fitness function. As the control law is based on the theorem of Lyapunov, the asymptotic stability of the scheme can be ensured. Finally, several simulation studies are conducted to show the efficacy of the suggested OBC.

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LQR controller design for quad‐rotor helicopters

Cited by 87 publications

References 3 publications

Self-tuning state-feedback control of a rotary pendulum system using adjustable degree-of-stability design

Self-tuning state-feedback control of a rotary pendulum system using adjustable degree-of-stability design

Stable High-Speed Quadrotor Flight using Differential Trajectory

Optimal backstepping control of quadrotor UAV using gravitational search optimization algorithm

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