Attitude tracking of quadrotor UAV via mixed H2/H&lt;inf&gt;∞&lt;/inf&gt; controller: An LMI based approach

Emam, Masoud; Fakharian, Ahmad

doi:10.1109/med.2016.7535919

Cited by 19 publications

(7 citation statements)

References 6 publications

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“…A variety of algorithms are designed to control the flight trajectory stability of UAV,such as PID (Li et al, 2016), linear quadratic regulator (LQR) (Dong et al, 2015), H-infinity (Emam and F Ak.Harian, 2016), sliding mode control (Zhou et al, 2016), back-stepping (Shi and Lin, 2018), and adaptive control (Fan D et al, 2018) and so on. Specifically, A PID intelligent fuzzy control system is designed for spraying operation of agricultural UAV (Zheng and Chen, 2021).…”

Section: Introductionmentioning

confidence: 99%

Design of anti-load perturbation flight trajectory stability controller for agricultural UAV

Wang¹,

XianYu²,

Liu³

et al. 2023

Front. Plant Sci.

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The unmanned aerial vehicle(UAV) used in agricultural fields usually has a load, which affects stability of flight trajectory. This problem is a great technical challenge and critical issue which has fascinated many researchers in this area. This research paper presents a flight dynamics model for agricultural UAV under load condition. The robust T-S fuzzy control method is applied in the attitude angle control part, and the traditional PID controller is used in the position loop control part. Results of simulation depict that the flight trajectory of agricultural UAV can reach certain stability when the load is relatively small.

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Section: Introductionmentioning

confidence: 99%

Design of anti-load perturbation flight trajectory stability controller for agricultural UAV

Wang¹,

XianYu²,

Liu³

et al. 2023

Front. Plant Sci.

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“…Further, the quadrotor attitude is controlled by an adaptive model predictive controller to achieve real‐time stability [7]. A robust mixed

H_2/H_{\infty }

controller has been developed for attitude tracking of a UAV with fast time response via regional pole‐placement constraints [8]. As a popular control design, a linear ADRC (active disturbance rejection control) can also be used in UAV tracking control for the desired attitude and height [9].…”

Section: Introductionmentioning

confidence: 99%

UAV based adaptive trajectory tracking control with input saturation and unknown time‐varying disturbances

Zhou

Tian

Lin

2022

IET Intelligent Trans Sys

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This paper proposes an adaptive control method for an underactuated complex nonlinear system, that is, unmanned aerial vehicle (UAV), to realize high‐precision trajectory tracking under input saturation constraint and other disturbances via artificial neural network and anti‐saturation auxiliary system. First, the rigid body motion theory is applied to establish a simplified nonlinear dynamic model of the UAV. Then a Lyapunov function is designed with the error surface to form the preliminary control law based on dynamic surface control. Afterwards, a radical basis function neural network is developed and used to estimate and compensate the disturbance, while the input saturation is also addressed via the designed anti‐saturation auxiliary system. Thus the stability and signal consistency of the closed‐loop UAV control system can be proved via the Lyapunov stability theory with appropriately tuned parameters. Simulation experiments are performed to verify that the proposed control algorithm can be used for UAV high‐precision trajectory tracking under time‐varying disturbances.

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“…Precise attitude control of quadrotor is fundamental and necessary to complete tasks, which has become an important research hotspot (Zhao et al , 2019; Raza et al , 2017), and it is a challenging task how to design a controller robust to external disturbance, noise, wind and actual parameter changes (Roohul et al , 2016). A hybrid H2/H∞ static feedback tracking controller with measurement noise and external disturbance robustness is proposed, and the time response of mixed H2/H∞ controller is improved by increasing the regional pole assignment constraint (Emam and Fakharian, 2016). A control strategy combining feedback linearization and linear quadratic regulator is proposed to stabilize the attitude of the disturbed quadrotor (Zhao et al , 2016).…”

Section: Introductionmentioning

confidence: 99%

Active disturbance rejection attitude control of unmanned quadrotor via paired coevolution pigeon-inspired optimization

Yuan¹,

Duan

2021

AEAT

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Purpose The purpose of this paper is to develop a novel active disturbance rejection attitude controller for quadrotors and propose a controller parameters identification approach to obtain better control results. Design/methodology/approach Aiming at the problem that quadrotor is susceptible to disturbance in outdoor flight, the improved active disturbance rejection control (IADRC) is applied to design attitude controller. To overcome the difficulty that adjusting the parameters of IADRC controller manually is complex, paired coevolution pigeon-inspired optimization (PCPIO) algorithm is used to optimize the control parameters. Findings The IADRC, where nonlinear state error feedback control law is replaced by non-singular fast terminal sliding mode control law and a third-order tracking differentiator is designed for second derivative of the state, has higher control accuracy and better robustness than ADRC. The improved PIO algorithm based on evolutionary mechanism, named PCPIO, is proposed. The optimal parameters of ADRC controller are found by PCPIO with the optimization criterion of integral of time-weighted absolute value of the error. The effectiveness of the proposed method is verified by a series of simulation experiments. Practical implications IADRC can improve the accuracy of attitude control of quadrotor and resist external interference more effectively. The proposed PCPIO algorithm can be easily applied to practice and can help the design of the quadrotor control system. Originality/value An improved active disturbance rejection controller is designed for quadrotor attitude control, and a hybrid model of PIO and evolution mechanism is proposed for parameters identification of the controller.

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Attitude tracking of quadrotor UAV via mixed H2/H<inf>∞</inf> controller: An LMI based approach

Cited by 19 publications

References 6 publications

Design of anti-load perturbation flight trajectory stability controller for agricultural UAV

Design of anti-load perturbation flight trajectory stability controller for agricultural UAV

UAV based adaptive trajectory tracking control with input saturation and unknown time‐varying disturbances

Active disturbance rejection attitude control of unmanned quadrotor via paired coevolution pigeon-inspired optimization

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