• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.1871-1876
• /
• 2005

In this paper, We present a new nonlinear adaptive control law using a disturbance accommodating control (DAC) observer for a Japanese automatic landing flight experiment vehicle called ALFLEX. A future spaceplane must have ability to deal with greater fluctuations in the stability and control derivatives of flight dynamics, because its flight region is much wider than that of conventional aircraft. In our previous studies, digital adaptive flight control systems have been developed based on a linear-parameter-varying (LPV) model depending on dynamic pressure, and obtained good simulation results. However, under previous control laws, it is difficult to accommodate uncertainties represented by disturbance and nonlinearity, and to design a stable flight control system. Therefore, in this study, we attempted to design a nonlinear adaptive control law using the DAC Observer and inverse dynamic methods. A good tracking property of the obtained system was confirmed in numerical simulation.

• Journal of Aerospace System Engineering
• /
• v.15 no.4
• /
• pp.75-84
• /
• 2021

A novel robot-operating-system-based flight and mission state communication node for X-Plane 11 flight control simulation environments and its simulation results were discussed. Although the proposed communication method requires considerable implementation steps compared with the conventional MATLAB/Simulink-based User Datagram Protocol (UDP) block utilization method, the proposed method enables a direct comparison of cockpit-view images captured during flight with the flight data. This comparison is useful for data acquisition under virtual environments and for the development of flight control systems. The fixed/rotary-wing and ground terrain elements simulated in virtual environments exhibited excellent visualization outputs, which can overcome time and space constraints on flight experiments and validation of missionary algorithms with complex logic.

• Journal of Institute of Control, Robotics and Systems
• /
• v.10 no.6
• /
• pp.557-565
• /
• 2004

The Korean space program was marked by the successful launching of a KSR-III liquid propelled sounding rocket. The Inertial Navigation System (INS) which carries out critical mission functions of navigation, guidance and control was domestically developed and perfectly certified through the flight test. The system consists of a strapdown inertial measurement, an onboard computer and flight software. This paper will describes the development works of the inertial navigation system, including top level system design, hardware and software. And it summarizes flight results.

• International Journal of Aerospace System Engineering
• /
• v.4 no.1
• /
• pp.1-8
• /
• 2017

This paper proposes the load distribution control allocation technique. The proposed method is designed by combining a conventional control allocation method with load distribution ability in order to reduce the stress acting on ailerons. By designing the weighting matrix as a function of the load distribution rule, the optimal deflection angles of each surface to satisfy both control goal and load distribution can be achieved. Moreover, rule based fault-tolerant control technique is also proposed. The rules are generated by considering both dominant control surfaces and the ratio of load distribution among surfaces. The performance of the proposed method is evaluated through numerical simulations.

• Journal of Institute of Control, Robotics and Systems
• /
• v.17 no.8
• /
• pp.833-842
• /
• 2011

The objectives of this research are development of guidance, navigation and control system for RUAV on virtual instrumentation and real flight test. For this research, the system is divided to DAQ (data acquisition) section, actuator section and controller section. And the hardware and software on each sections are realized on LabVIEW base. Waypoint guidance and control of auto flight are realized using PID gain tuning and waypoint vector tracking guidance algorism. For safe flight test, auto/manual switching module isolated from FCS (Flight Control System) is developed. By using the switch module, swift mode change was achieved during emergency flight case. Consequently, a meter level error of flight performance is achieved.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.55 no.12
• /
• pp.518-525
• /
• 2006

This paper presents the adaptive robust control method for the flight control systems with model uncertainties. The proposed control system can be composed simply by a combination of the adaptive dynamic surface control (DSC) technique and the self recurrent wavelet neural network (SRWNN). The adaptive DSC technique provides us with the ability to overcome the 'explosion of complexity' problem of the backstepping controller. The SRWNNs are used to observe the arbitrary model uncertainties of flight systems, and all their weights are trained on-line. From the Lyapunov stability analysis, their adaptation laws are induced and the uniformly ultimately boundedness of all signals in a closed-loop adaptive system is proved. Finally, simulation results for a high performance aircraft (F-16) are utilized to validate the good tracking performance and robustness of the proposed control system.

• Journal of Institute of Control, Robotics and Systems
• /
• v.10 no.2
• /
• pp.112-124
• /
• 2004

A neural network based adaptive reconfigurable flight controller is presented for a class of discrete-time nonlinear flight systems in the presence of variations of aerodynamic coefficients and control effectiveness decrease caused by control surface damage. The proposed adaptive nonlinear controller is developed making use of the backstepping technique for the angle of attack, sideslip angle, and bank angle command following without two time separation assumption. Feedforward multilayer neural networks are implemented to guarantee reconfigurability for control surface damage as well as robustness to the aerodynamic uncertainties. The main feature of the proposed controller is that the adaptive controller is developed under the assumption that all of the nonlinear functions of the discrete-time flight system are not known accurately, whereas most previous works on flight system applications even in continuous time assume that only the nonlinear functions of fast dynamics are unknown. Neural networks learn through the recursive weight update rules that are derived from the discrete-time version of Lyapunov control theory. The boundness of the error states and neural networks weight estimation errors is also investigated by the discrete-time Lyapunov derivatives analysis. To show the effectiveness of the proposed control law, the approach is i]lustrated by applying to the nonlinear dynamic model of the high performance aircraft.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.31 no.10
• /
• pp.1031-1038
• /
• 2007

A study on the development of control loading system for a pilot command in the helicopter flight training device is performed. The key issue of the device is how to provide closely the real feeling of the stick forces to the trainer during the flight training. Focusing on this proviso and considering the suitable approach than the complexity of the hydraulic system, we adopt the AC servo motor system although its inherent disadvantages such as the torque ripple and the stick-slip friction effect at a low control force. However, we overcome these detrimental effects by introducing the appropriate control device and the robust structural design of the actuating system, thereby the feasibility and applicability to the system can be obtained by showing good performance, meeting the required specification.

• Journal of Satellite, Information and Communications
• /
• v.10 no.3
• /
• pp.32-37
• /
• 2015

Unmaned Aerial Vehical(UAV) is a flight which is automatically flying by remote control on th ground. However UAV has an advantage of control that is easy, but has an disadvantage of not hovering. By comparison, quadcopter which is one of the UAV is easily operated. Also quadcopter has hovering function and high stability. In this paper, we propose stable flight algorithm associated PID(proportional-integral-derivative) control with fuzzy contorl to implement stable quadcopter system. After getting a positioning information of the drone, This proposed system is implemented for stable flight through flight attitude control using gyro and acceleration sensor. We also propose the flight mode system to hover drone with GPS sensor.

• Journal of Institute of Control, Robotics and Systems
• /
• v.13 no.5
• /
• pp.422-428
• /
• 2007

This paper presents a neural network based adaptive control approach to a reconfigurable flight control law that keeps handling qualities in the presence of faults or failures to the control surfaces of an aircraft. This approach removes the need for system identification for control reallocation after a failure and the need for an accurate aerodynamic database for flight control design, thereby reducing the cost and time required to develope a reconfigurable flight controller. Neural networks address the problem caused by uncertainties in modeling an aircraft and pseudo control hedging deals with the nonlinearity in actuators and the reconfiguration of a flight controller. The effect of the reconfigurable flight control law is illustrated in results of a nonlinear simulation of an unmanned aerial vehicle Durumi-II.