Kyeum-Rae Cho

Ground Test of the Flight Control System Using PC104

This paper presents the flight control system using a PC104 with GPS and IMU. This System includes an Auto/Manual conversion module by PIC16 for safety, and homing type guidance algorithm to flight toward a scheduled target. We verify the performance of the flight control system via ground test, and present the possibility of application into UAV control system via comparison with the commercial system.

Application of neural network for airship take-off and landing mode by buoyancy control

For long time, the takeoff and landing control of airship was worked by human handling. With the development of the autonomous control system, the exact controls during the takeoff and landing were required and lots of methods and algorithms were suggested. This paper presents the result of airship take-off and landing by buoyancy control using air ballonet volume change and performance control of pitch angle for stable flight within the desired altitude. For the complexity of airship`s dynamics, firstly, simple PID controller was applied. Due to the various atmospheric conditions, this controller didn`t give satisfactory results. Therefore, new control method was designed to reduce rapidly the error between designed trajectory and actual trajectory by learning algorithm using an artificial neural network. Generally, ANN has various weaknesses such as large training time, selection of neuron and hidden layer numbers required to deal with complex problem. To overcome these drawbacks, in this paper, the RBFN (radial basis function network) controller developed. The weight value of RBFN is acquired by learning which to reduce the error between desired input output through and airship dynamics to impress the disturbance. As a result of simulation, the controller using the RBFN is superior to PID controller which maximum error is 15M.

The Analyses of Dynamic Characteristics and Flight Test Results of Airship Throughout the Flight Test

For decades, airships have being developed in Europe (especially German) and America. Airships are planning to be used for advertisements and airliners as well. In Korea, KARI (Korea Aerospace Research Institute) is developing stratospheric communication airship and the similar research is carried out in Japan. Among them, Zeppelin of German has the cutting-edge airship technology with Zeppelin NT. In this paper, the flight performance and stability were evaluated by comparing mathematical theory and the real test. The stability was examined through dynamic modeling and assured by designing controllers at each flight mode. Elevator angle, rudder angle, magnitude of thrust and tilting angle of thrust vector were used as control inputs. Moreover, after measuring the airship velocity, flight direction, magnitude and direction of the wind, attitude angles and trajectories of the airship at each flight mode, the results were compared with the simulation. To get the reasonable data, low-pass filter and band-stop filter were designed to get rid of the sensor noise and engine vibration. The test was accomplished at cruise mode, turning mode, and deceleration. To conclude, with comparing the simulation data and flight test data, it could be known that the dynamic model used in this paper was reasonable.

Dynamic Response and Control of Airship with Gust

To acquire the dynamic response and design the controller of the airship, the longitudinal motion of the airship with respect to the vertical gust, which is the nonlinear system, was studied. The effects of the apparent mass and moment of the airship delay the dynamic response and the settling time, which are slower than those of conventional airplanes. The current object of the airship is designed to cruise at 500~1000m altitude. At that height, the atmospheric conditions are generally unstable by wind gust. In this paper, it has been studied for the case of vertical gust, since the apparent mass effects are dominant in has been studied for the case of vertical gust, since the apparent mass effects are dominant in that plane. In addition to the study of the dynamic responses of the airship, the controller was designed using the PID-controller. When the gust was applied, airship responses were recovered of equilibrium states. However, it takes too ling time for recovery and the speed of airship is reduced. So, the aim in this paper was to fasten the recovery speed and to get back the cruising velocity. The control parameters were determined from the stability mode analysis, and the control inputs were the thrust and the elevator deflection angle.

Evaluation of Performance of Atmospheric Re-Entry System for the Uncertainties Using the Monte-Carlo Simulation

The Monte-Carlo simulation of statistical analysis is used to investigate the final conditions of states as well as the footprint boundaries resulting from the atmospheric re-entry dispersions. The re-entry dispersions in this paper are specified by a covariance matrix of latitude, longitude, altitude, bank angle, flight path angle, heading error, and range at entry velocity. The error sources that affect these at re-entry for a deboost are the uncertainties associated with atmospheric density and temperature, initial errors, wind, and estimation error of aerodynamic coefficients. Using deviations of these errors and a nominal flight trajectory, the covariance matrix of state variables can be determined by performing a trajectory error analysis. Major considerations in the application of the Monte-Carlo method are the simulation of perturbed trajectories, bank reversal, and determination of the impact points for each of these trajectories. This paper analyzes the results of uncertainties from the viewpoint of aero-coefficients and bank reversal.