Shuzhen Luo

Modeling and Control of a Powered Parafoil in Wind and Rain Environments

A novel modeling method, based on computational fluid dynamics (CFD) to simulate a parafoil flying in rain and wind environments, is proposed. Then, the dynamic model of the powered parafoil in the complex environment is established on the basis of revised aerodynamic equations. By introducing path-following controllers based on active disturbance rejection control (ADRC), horizontal and longitude trajectory tracking of the powered parafoil in realistic environments are simulated. Results verify the effectiveness of the model and control methods.

A hybrid control approach for powered parafoil combining active disturbance rejection control and unbalanced load compensation

Powered parafoil is a kind of low-speed unmanned air vehicle and is widely used in aerospace applications. However, the wind interference and the unbalanced load on the actuators of its horizontal controller extremely reduce the control effect and the disturbance rejection ability of the trajectory tracking. In order to solve these problems, a hybrid control approach for powered parafoil based on active disturbance rejection control is proposed. In this control approach, distinguished from other existing ones, the horizontal controller consists of the inner and outer loops. The outer loop is applied to accurately control the flight direction and offset the wind disturbance of the whole system. Meanwhile, the inner loop is designed to offer higher control precision and dynamically compensate the unbalanced load on the actuators of the horizontal controller. In order to verify the control approach, the model of the powered parafoil is improved by the model of rudders and flap deflection. Then, the effectiveness of the proposed control method is illustrated by the experiment. The results show that compared with the proportional–integral–derivative controller, the control effect and the anti-disturbance ability are all substantially improved.

Soft landing control of unmanned powered parafoils in unknown wind environments

For autonomous landing powered parafoils, the ability to perform a final flare maneuver against the wind direction can generate a considerable reduction of lateral and longitudinal velocities at impact, enabling a soft landing for a safe delivery of sensible loads. To realize accurate, soft landing in the unknown wind environment, an in-flight wind identification algorithm is first proposed. The wind direction and speed can be obtained online by only using the GPS sampling data based on the recursive least square method. Moreover, the 3D trajectory tracking strategy for the powered parafoil is also established, which is globally asymptotically stable. Furthermore, the lateral trajectory tracking controller and longitudinal altitude controller based on active disturbance rejection control are presented, respectively. Eventually, results from simulations demonstrate that the proposed landing control method can effectively realize accurate soft landing in unknown wind environments with the in-flight wind identification algorithm applied in the trajectory tracking process.

In-flight wind identification and soft landing control for autonomous unmanned powered parafoils

ABSTRACT For autonomous unmanned powered parafoil, the ability to perform a final flare manoeuvre against the wind direction can allow a considerable reduction of horizontal and vertical velocities at impact, enabling a soft landing for a safe delivery of sensible loads; the lack of knowledge about the surface-layer winds will result in messing up terminal flare manoeuvre. Moreover, unknown or erroneous winds can also prevent the parafoil system from reaching the target area. To realize accurate trajectory tracking and terminal soft landing in the unknown wind environment, an efficient in-flight wind identification method merely using Global Positioning System (GPS) data and recursive least square method is proposed to online identify the variable wind information. Furthermore, a novel linear extended state observation filter is proposed to filter the groundspeed of the powered parafoil system calculated by the GPS information to provide a best estimation of the present wind during flight. Simulation experiments and real airdrop tests demonstrate the great ability of this method to in-flight identify the variable wind field, and it can benefit the powered parafoil system to fulfil accurate tracking control and a soft landing in the unknown wind field with high landing accuracy and strong wind-resistance ability.

Accurate calculation of aerodynamic coefficients of parafoil airdrop system based on computational fluid dynamic

Accurate calculation of canopy aerodynamic parameters is a prerequisite for precise modeling of a parafoil airdrop system. This investigation analyses the aerodynamic performance of the canopy in airdrop testing combining the leading-edge incision and the trailing-edge deflection. Aerodynamic parameters of the canopy are obtained using the computational fluid dynamic simulations, and then, the output data are used to estimate the deflection and incision factors. The estimated lift and drag coefficients instead of the traditional parameters based on lifting-line theory are incorporated into the eight degrees of freedom dynamic model of an airdrop system and make some simulations. The effectiveness of the proposed method for calculating aerodynamic coefficients is verified by actual airdrop testing.

Longitudinal Control of Unmanned Powered Parafoil with Precise Control Gain

Unmanned powered parafoil is a complex nonlinear system. In this paper, a novel approach based on active disturbance rejection control (ADRC) with precise control gain is constructed for unmanned powered parafoil to reach the precise reference altitude. We first outline the dynamic model of unmanned powered parafoil. Moreover, the longitudinal altitude controller is introduced, where the extended state observer (ESO) estimates the total disturbances involving model uncertainties, internal coupling and external wind disturbance. Furthermore, the highlight of paper, is that the control gain is directly obtained from the system model rather than a trial value, which can optimize the state error feedback (SEF) and enhance the stability and disturbance-rejection of the controller. After that, the introduction of semi-physical platform is presented and the experimental results are analyzed. The experiment results verify the efficiency of this control approach.