An Optimal Guidance Law Applied to Quadrotor Using LQR Method

In this paper, a nonlinear robust control method is developed for trajectory tracking of a quadrotor aircraft. The proposed approach combines the robust signal compensation method and the backstepping technique. First, the quadrotor dynamic system with multiple disturbances and uncertainties is divided into four subsystems. Then, the nominal controllers are constructed for the subsystems without disturbance terms, while the robust signal compensators are introduced to compensate for the effect of nonlinearities and uncertainties. Furthermore, the Lyapunov analysis has shown that the proposed controller can achieve stable tracking in the presence of violent discontinuous disturbances and uncertainties. The tracking error converges to an arbitrarily small neighborhood of zero. Finally, the proposed control design is validated with real flight experiments. The results show superior trajectory tracking performance of the quadrotor system affected by external disturbances. INDEX TERMS Robust control, quadrotor, trajectory tracking, signal compensation. JIA SUN received the B.S. degree in automation from the School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China, in 2015, where she is currently pursuing the Ph.D. degree in control science and engineering. She was a visiting Ph.D. student with the

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“…in [15]- [17]. The LQR controller is designed for linear models, while the quadrotor model has strong nonlinearities.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear Robust Compensation Method for Trajectory Tracking Control of Quadrotors

Sun

Wang

et al. 2019

IEEE Access

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“…To solve the quadrotor helicopter control problem, many techniques have been proposed such as linear quadratic regulator (LQR) control (Nuchkrua & Parnichkun 2012;Jafari et al 2010;Castillo et al 2005), proportional-integral-derivative (PID) control (Junior et al 2013;Bolandi et al 2013;Hwang et al 2012), fuzzy logic (FL) control (Baek et al 2013;Erginer & Altug 2012;Santos et al 2010), feedback linearization control (Zhang et al 2013;Mukherjee & Waslander 2012;Mokhtari et al 2006), sliding mode control (Sumantri et al 2013;Guisser & Medromi 2009;Bouadi et al 2007) and backstepping control Regula & Lantos 2011;Madani & Benallegue 2006). Initially, most of the control strategies are based on linearized models without compensation of modeling errors and external disturbances.…”

Section: Introductionmentioning

confidence: 99%

Stabilization and trajectory tracking control for underactuated quadrotor helicopter subject to wind-gust disturbance

Basri

Husain

Danapalasingam

2015

Sadhana

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The control of quadrotor helicopter has been a great challenge for control engineers and researchers since quadrotor is an underactuated and a highly unstable nonlinear system. In this paper, the dynamic model of quadrotor has been derived and a so-called robust optimal backstepping control (ROBC) is designed to address its stabilization and trajectory tracking problem in the existence of external disturbances. The robust controller is achieved by incorporating a prior designed optimal backstepping control (OBC) with a switching function. The control law design utilizes the switching function in order to attenuate the effects caused by external disturbances. In order to eliminate the chattering phenomenon, the sign function is replaced by the saturation function. A new heuristic algorithm namely Gravitational Search Algorithm (GSA) has been employed in designing the OBC. The proposed method is evaluated on a quadrotor simulation environment to demonstrate the effectiveness and merits of the theoretical development. Simulation results show that the proposed ROBC scheme can achieve favorable control performances compared to the OBC for autonomous quadrotor helicopter in the presence of external disturbances.

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“…Thus, it is a great challenge to design a quadrotor control system due to these features. Many methods have been proposed to control a quadrotor helicopter, such as linear quadratic regulator (LQR) control, 1 proportional–integral–derivative (PID) control, 2 fuzzy logic (FL) control, 3 feedback linearization control, 4 sliding mode control, 5 and backstepping control. 6,7 Initially, most of the control strategies are based on simplified models.…”

Section: Introductionmentioning

confidence: 99%

A hybrid optimal backstepping and adaptive fuzzy control for autonomous quadrotor helicopter with time-varying disturbance

Basri

Husain

Danapalasingam

2015

Proceedings of the Institution of Mechanical Engineers, Part G:

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In this paper, a hybrid control system called as backstepping adaptive fuzzy control system, which integrates nominal and compensation controller is developed for autonomous quadrotor helicopter with inherent time-varying disturbance. In this hybrid control system, the nominal controller based on backstepping technique is the main controller, and the compensation controller containing a fuzzy control approach is used to eliminate the effect of uncertainties caused by external disturbance. In addition, in order to relax the requirement of prior knowledge on the bound of external disturbance, an online adaptation law is derived. Asymptotical stability of the closed-loop control system is analytically proven via the Lyapunov theorem. For the problem of determining the backstepping control parameters, particle swarm optimization algorithm has been employed. Finally, the designed controller is experimentally evaluated on a quadrotor simulation environment to demonstrate the effectiveness and merits of the theoretical development.

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An Optimal Guidance Law Applied to Quadrotor Using LQR Method

Cited by 34 publications

References 6 publications

Nonlinear Robust Compensation Method for Trajectory Tracking Control of Quadrotors

Nonlinear Robust Compensation Method for Trajectory Tracking Control of Quadrotors

Stabilization and trajectory tracking control for underactuated quadrotor helicopter subject to wind-gust disturbance

A hybrid optimal backstepping and adaptive fuzzy control for autonomous quadrotor helicopter with time-varying disturbance

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