Jiang Ju

Information fusion distributed navigation for UAVs formation flight

High precision navigation is a key technique for unmanned aerial vehicles (UAVs) formation flight. A methodology for fusing data from inertial navigation system (INS), global positioning system (GPS) and vision sensor is presented. For the lead UAV, a Kalman filter based INS/GPS integrated navigation system is designed. For the wing UAV, a local Kalman filter based INS/GPS integrated subsystem and local Kalman filter based INS/Vision/JTIDS subsystem are designed, and a distributed master filter based on information fusion estimation is designed to get the absolute navigation solution of wing UAV. And then, the relative navigation between the lead UAV and the wing UAV in formation can be obtained. Simulation results verify the validity of this formation navigation architecture for UAVs. Moreover, it illustrates that the distributed information fusion INS/GPS/Vision integrated navigation system for formation UAVs has highest geodetic navigation accuracy, when comparing with INS/GPS integrated navigation system and INS/Vision integrated navigation system.

Modified shuffled frog leaping algorithm optimized control for air-breathing hypersonic flight vehicle

This article addresses the flight control problem of air-breathing hypersonic vehicles and proposes a novel intelligent algorithm optimized control method. To achieve the climbing, cruising and descending flight control of the air-breathing hypersonic vehicle, an engineering-oriented flight control system based on a Proportional Integral Derivative (PID) method is designed for the hypersonic vehicle, which including the height loop, the pitch angle loop and the velocity loop. Moreover, as a variant of nature-inspired algorithm, modified shuffled frog leaping algorithm is presented to optimize the flight control parameters and is characterized by better exploration and exploitation than the standard shuffled frog leaping algorithm. A nonlinear model of air-breathing hypersonic vehicle is used to verify the dynamic characteristics achieved by the intelligent flight control system. Simulation results demonstrate that the proposed swarm intelligence optimized PID controllers are effective in achieving better flight trajectory and velocity control performance than the traditional controllers.

Research on effects of sea states on air wake

The effect of carriers air wake, which causes severe landing error, even landing failure, is not avoidable during carrier-based aircraft landing. At the same time, carriers air wake is certainly affected by sea states. From now on, there is no research or paper discussing this phenomenon. The effects of the sea states on air wake are studied in the first time in this paper, and finally got some conclusions. Every component model of carrier air wake was built, which could be used to build the relationships between the air wake and the sea states. According to the models, the wind over deck, the pitch amplitude of carrier, and the pitch frequency are critical factors causing the variety of air wake as sea states are changed. The simulation results show that the carrier air wake is affected severely by sea states. The steady carrier-wake turbulence and the periodic ship-motion-induced turbulence are influenced more significantly, especially for the periodic component. The research results of this paper have important effect on the further studying of landing safety and air wake rejecting.

Research on visual simulation of carrier aircraft based on explicit model following control and fuzzy adaptive control

This paper presents a MATLAB/Simulink aircraft landing control method. The controlled object selected for American fighter F18, numerical simulation of the nonlinear. It is proved that it can realize the inhibitory effect of airwake, and quick response system. Then using MFC, Flight Gear and MATLAB engine to build interactive platform, aircraft landing process in form intuitive 3D animation show.

Monte Carlo approach to the analysis of UAVs control system

Several nonlinear control theories have been implied in UAVs control system, although all of those control system can achieve control objects and satisfy control requirement, the robustness of those system is unknown. This paper introduces Monte Carlo approach which is a statistical method to the study of UAVs control systems robustness. Disturbances which are worthy to consider and detailed process are presented. And Simulation results show that, considering atmospheric turbulence and sensors noises, Monte Carlo approach is a proper tool in the analysis of the robustness of UAVs formation control system.