Active disturbance rejection control (ADRC)-based autonomous homing control of powered parafoils

Jin, Tao; Sun, Qinglin; Tan, Panlong; Chen, Zengqiang; He, Yiqian

doi:10.1007/s11071-016-2972-1

Cited by 43 publications

(17 citation statements)

References 23 publications

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“…It will largely reduce the control difficulty of the nonlinear system. Hence, it is very suitable for the flexible wing UAV …”

Section: Preliminariesmentioning

confidence: 99%

“…Hence, it is very suitable for the flexible wing UAV. 23 Firstly, a state, such as the flight direction of the flexible wing UAV, can be expressed as…”

Section: Principle Of Adrcmentioning

confidence: 99%

“…From Equation (4) and Equation (11), it can be seen that the observation ability of ESO is essential for ADRC. Its advantage will be distinct, only by minimizing the error between f and z 23 . In this way, the control effect will be improved with better observation precision and the fluctuation of the control quantity.…”

Section: Active Disturbance Rejection Control With Feedforward Compenmentioning

confidence: 99%

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Altitude control for flexible wing unmanned aerial vehicle based on active disturbance rejection control and feedforward compensation

Sun

Chen

et al. 2019

Intl J Robust & Nonlinear

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Summary For achieving the accurate trajectory tracking of the flexible wing unmanned aerial vehicle in the complicated missions, especially the vertical component, a feedforward compensation unit–based active disturbance rejection control (ADRC) is proposed. In ADRC, the internal dynamics and complicated influence of the total disturbance will be estimated and dynamically compensated by extended state observer (ESO). It puts a very high request on the observation ability of ESO with the unpredictable external disturbance, complex internal coupling influence, and the strong nonlinear characteristic of the proposed system. For this reason, by deeply analyzing the model of this system, the varying attitude influence on the altitude control will be deduced. Then, this influence will be compensated previously by a feedforward compensation unit. Through the previous compensation of the calculable part of the internal dynamics and total disturbance, the burden of ESO can be reduced largely. In this way, it improves the control effect of the ADRC with better observation precision of ESO. After that, based on the hardware‐in‐the‐loop simulation, the effectiveness of the proposed method is verified completely with the complicated flight missions. The robustness of the control effect and observation ability of ESO are also verified by the Monte Carlo simulation. At last, the results of actual flight experiment prove the advancement and practicability of the proposed ADRC method.

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“…It will largely reduce the control difficulty of the nonlinear system. Hence, it is very suitable for the flexible wing UAV …”

Section: Preliminariesmentioning

confidence: 99%

“…Hence, it is very suitable for the flexible wing UAV. 23 Firstly, a state, such as the flight direction of the flexible wing UAV, can be expressed as…”

Section: Principle Of Adrcmentioning

confidence: 99%

Section: Active Disturbance Rejection Control With Feedforward Compenmentioning

confidence: 99%

See 1 more Smart Citation

Altitude control for flexible wing unmanned aerial vehicle based on active disturbance rejection control and feedforward compensation

Sun

Chen

et al. 2019

Intl J Robust & Nonlinear

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“…A parafoil system is a type of unmanned autonomous vehicle, which possesses the advantages of exceptional controllability and gliding performance, and can achieve fixed-point autonomous homing and soft landing compared with traditional parachute systems [1][2][3][4]. Parafoil systems play a significant role and have wide applications in the area of disaster assistance, aerospace, and military fields [5][6][7][8]. Due to their slow airspeed in comparison to conventional fixed-wing aircrafts, the parafoil systems are extremely susceptible to wind fields [9,10].…”

Section: Introductionmentioning

confidence: 99%

In-flight Wind Field Identification and Prediction of Parafoil Systems

et al. 2020

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The wind field is an essential factor that affects accurate homing and flare landing of parafoil systems. In order to obtain the ambient wind field during the descent of a parafoil system, a combination method of in-flight wind field identification and prediction is proposed. First, a wind identification method only using global position system information is derived based on the flight dynamics of parafoil systems. Then a wind field prediction model is constructed using the atmospheric dynamics, and the low-altitude wind field is predicted based on the identified wind field of high-altitude. Finally, simulations of wind field identification and prediction are conducted. The results demonstrate that the proposed method can identify the wind fields precisely and also predict the wind fields reasonably. This method can potentially be applied in practical parafoil systems to provide wind field information for homing tasks.

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“…Li et al also utilized a three‐term PID controller where an energy function considering the altitude and forward velocity were added. Since the parafoil and payload system suffers from the variable wind disturbance substantially, a trajectory tracking controller based on active disturbance rejection control was constructed to improve the antidisturbance ability . However, for the parafoil and payload system, disturbances such as nonlinear cross‐coupling influences and variable external disturbance will cause the considerable influence, resulting in the limitation of the controller to achieve satisfactory performance.…”

Section: Introductionmentioning

confidence: 99%

Characteristic model–based generalized predictive control and its application to the parafoil and payload system

Tan

Sun

Chen

et al. 2019

Optim Control Appl Methods

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Generalized predictive control (GPC) has been applied in systems to improve the control performance during the last decades. The designing of predictive model is the essential and vital problem in GPC application. Using characteristic model (CM) as predictive model in GPC can simplify the modeling procedure and improve computing efficiency of GPC. The CM is a kind of simple and easy-to-use dynamic model that is equivalent with precise model. Moreover, the creation of CM requires less system information than the practical models. The GPC with CM as predictive model named characteristic model-based generalized predictive control (CMGPC) is proposed in this paper, and it is used in the trajectory tracking control for parafoil and payload system. Simulations and analysis prove that CMGPC is equivalent to traditional GPC and CMGPC is a more efficient way for trajectory tracking of parafoil and payload system compared with conventional proportional integral derivative (PID) method. KEYWORDS characteristic model (CM), generalized predictive control (GPC), parafoil and payload system, trajectory tracking Optim Control Appl Meth. 2019;40:659-675.wileyonlinelibrary.com/journal/oca

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Active disturbance rejection control (ADRC)-based autonomous homing control of powered parafoils

Cited by 43 publications

References 23 publications

Altitude control for flexible wing unmanned aerial vehicle based on active disturbance rejection control and feedforward compensation

Altitude control for flexible wing unmanned aerial vehicle based on active disturbance rejection control and feedforward compensation

In-flight Wind Field Identification and Prediction of Parafoil Systems

Characteristic model–based generalized predictive control and its application to the parafoil and payload system

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