Modeling Method and Control Strategy for Hose-Drogue Aerial Refueling System

Conventional method for hose-drogue model of aerial refueling system is known to be complex due to the flexible body of hose.And as reported,drogues are unstable in atmospheric turbulence,which greatly decreases docking success rates.This paper proposes a dynamic model for a hose-drogue aerial refueling system based on Kane equation and rigid multi-body dynamics,and analyzes its performance.Furthermore,the nonlinear dynamic model is linearized at the equilibrium point and simplified from full order to 2 nd order.Based on the simplified 2 nd order model,active control strategies,including proportion integral derivative(PID)and liner quadratic regulator(LQR)control laws,are designed to inhibit the pendulum movement of drogue due to,atmospheric turbulences.Numerical simulation results show the significant correctness of the proposed dynamic model by steady-state drag and balance position of drogue when the tanker flights under different conditions.Moreover,the steady state position error varies within 1 cm,thanks to either controller,when the drogue suffers from moderate-level atmospheric turbulences.Further,the PID controller exhibits better control effect and higher control precision than LQR controller.

Numerical Analysis of Refueling Drogue Oscillation During Refueling Docking

Refueling docking at different velocities is simulated by using computational fluid dynamics(CFD)method.The Osher scheme and S-A turbulence model are used to solve the compressible Navier-Stokes equations,and the Delaunay mapping dynamic grid method is also employed.All the numerical results show that the velocity of refueling docking is very important for aerial refueling.When the velocity is lower than 3m/s,the refueling drogue will move upward with obvious cycle staggering,while moving upward with slight cycle staggering at the speed of3m/s.The results can be referenced by aerial refueling design.

Real-time drogue recognition and 3D locating for UAV autonomous aerial refueling based on monocular machine vision

Drogue recognition and 3D locating is a key problem during the docking phase of the autonomous aerial refueling （AAR）. To solve this problem, a novel and effective method based on monocular vision is presented in this paper. Firstly, by employing computer vision with red-ring-shape feature, a drogue detection and recognition algorithm is proposed to guarantee safety and ensure the robustness to the drogue diversity and the changes in environmental condi- tions, without using a set of infrared light emitting diodes （LEDs） on the parachute part of the dro- gue. Secondly, considering camera lens distortion, a monocular vision measurement algorithm for drogue 3D locating is designed to ensure the accuracy and real-time performance of the system, with the drogue attitude provided. Finally, experiments are conducted to demonstrate the effective- ness of the proposed method. Experimental results show the performances of the entire system in contrast with other methods, which validates that the proposed method can recognize and locate the drogue three dimensionally, rapidly and precisely.

Dynamic modeling of a hose-drogue aerial refueling system and integral sliding mode backstepping control for the hose whipping phenomenon

Dynamic modeling of a hose-drogue aerial refueling system（HDARS） and an integral sliding mode backstepping controller design for the hose whipping phenomenon（HWP） during probe-drogue coupling are studied. Firstly, a dynamic model of the variable-length hose-drogue assembly is built for the sake of exploiting suppression methods for the whipping phenomenon.Based on the lumped parameter method, the hose is modeled by a series of variable-length links connected with frictionless joints. A set of iterative equations of the hose＇s three-dimensional motion is derived subject to hose reeling in/out, tanker motion, gravity, and aerodynamic loads accounting for the effects of steady wind, atmospheric turbulence, and tanker wake. Secondly,relying on a permanent magnet synchronous motor and high-precision position sensors, a new active control strategy for the HWP on the basis of the relative position between the tanker and the receiver is proposed. Considering the strict-feedback configuration of the permanent magnet synchronous motor, a rotor position control law based on the backstepping method is designed to insure global stability. An integral of the rotor position error and an exponential sliding mode reaching law of the current errors are applied to enhance control accuracy and robustness. Finally,the simulation results show the effectiveness of the proposed model and control laws.

Drogue detection for autonomous aerial refueling based on convolutional neural networks

Drogue detection is a fundamental issue during the close docking phase of autonomous aerial refueling（AAR）. To cope with this issue, a novel and effective method based on deep learning with convolutional neural networks（CNNs） is proposed. In order to ensure its robustness and wide application, a deep learning dataset of images was prepared by utilizing real data of ‘‘Probe and Drogue＂ aerial refueling, which contains diverse drogues in various environmental conditions without artificial features placed on the drogues. By employing deep learning ideas and graphics processing units（GPUs）, a model for drogue detection using a Caffe deep learning framework with CNNs was designed to ensure the method＇s accuracy and real-time performance. Experiments were conducted to demonstrate the effectiveness of the proposed method, and results based on real AAR data compare its performance to other methods, validating the accuracy, speed, and robustness of its drogue detection ability.

Physical Hydrography and Algal Bloom Transport in Hong Kong Waters

In sub-tropical coastal waters around Hong Kong, algal blooms and red tides are usually first sighted in the Mirs Bay, in the eastern waters of Hong Kong. A calibrated three-dimensional hydrodynamic model for the Pearl River Estuary （Delft3D） has been applied to the study of the physical hydrography of Hong Kong waters and its relationship with algal bloom transport patterns in the dry and wet seasons. The general 3D hydrodynamic circulation and salinity structure in the partially-mixed estuary are presented. Extensive numerical surface drogue tracking experiments are performed for algal blooms that are initiated in the Mirs Bay under different seasonal, wind and tidal conditions. The probability of bloom impact on the Victoria Harbour and nearby urban coastal waters is estimated. The computations show that： i） In the wet season （May - August）, algal blooms initiated in the Mirs Bay will move in a clockwise direction out of the bay, and be transported away from Hong Kong due to SW monsoon winds which drive the SW to NE coastal current; ii） In the dry season （November- April）, algal blooms initiated in the northeast Mirs Bay will move in an anti-clockwise direction and be carried away into southern waters due to the NE to SW coastal current driven by the NE monsoon winds; the bloom typically flows past the east edge of the Victoria Harbeur and nearby waters. Finally, the role of hydrodynamic transport in an important episodic event -- the spring 1998 massive red tide -- is quantitatively examined. It is shown that the strong NE to E wind during late March to early April, coupled with the diurnal tide at the beginning of April, significantly increased the probability of bloom transport into the Port Shelter and East Lamma Channel, resulting in the massive fish kill. The results provide a basis for risk assessment of harmful algal bloom （HAB） impact on urban coastal waters around the Victoria Habour.