Modeling of powered parafoil based on Kirchhoff motion equation

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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“…Meanwhile, in this paper, this section just outlines the modeling method. More details are presented in the reference from the work of Zhu et al…”

Section: Modeling Of Flexible Wing Uav Systemmentioning

confidence: 99%

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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“…The state equation is given as a conclusion at the end. The detailed modeling procedure can be shown in the work of Zhu et al, in which we focused on the modeling problem of parafoil and payload system.…”

Section: Trajectory Tracking Control Of Parafoil and Payload System Amentioning

confidence: 99%

“…Parafoil and payload system has a strong nonlinearity and is highly susceptible to wind disturbance due to low flight speed and the flexible fabric materials of the canopy . The actuators for parafoil and payload system involve lateral brake deflection and longitudinal thrust provided by propeller.…”

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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“…In the modeling process, the velocity, angular rate and force constraints are introduced and the detailed modeling process is provided. Zhu et al [4] considered the relative motion of canopy and payload; two coordinates are built separately to analyze the motion properties of canopy and payload. According to the Kirchhoff motion equation, the 8-DOF dynamic model of the powered parafoil is built.…”

Section: Introductionmentioning

confidence: 99%

6-DOF Modeling and 3D Trajectory Tracking Control of a Powered Parafoil System

Zhao

Yao

et al. 2020

IEEE Access

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The powered parafoil system is obtained by adding the propeller thrust to the unpowered parafoil system, and has coupling and nonlinear characteristics, which make its precise control more difficult than that of the unpowered parafoil system. To achieve the trajectory tracking control of the powered parafoil system in the field of precision airdrop, a mathematical model of the 6-DOF of the powered parafoil system is established first. Then, a new trajectory tracking strategy is proposed, which can overcome the limitations of the traditional guidance-based trajectory tracking strategy. We design lateral, longitudinal, and velocity controllers on the basis of the motion characteristics of the powered parafoil system. Then, we adopt the widely used PID control strategy in engineering. In response to the difficult of the PID controller parameter tuning of the powered parafoil system, we achieve the PID controller parameter tuning with the ecosystem particle swarm optimization (ESPSO) of the swarm intelligence optimization algorithm. The effectiveness of the algorithm is verified by simulation experiments. Results show that the proposed algorithm can obtain high trajectory tracking accuracy even when a deviation in the initial state and a random gust wind disturbance in the outside world occur regardless of the method of the multiphase homing or the optimal control homing adopted. The proposed trajectory tracking strategy also has strong robustness and adaptability.

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Modeling of powered parafoil based on Kirchhoff motion equation

Cited by 57 publications

References 14 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

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

6-DOF Modeling and 3D Trajectory Tracking Control of a Powered Parafoil System

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