• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.37 no.12
• /
• pp.1209-1216
• /
• 2009

This paper presents the pose estimation of a small UAV utilizing visual information from low cost cameras installed indoor. To overcome the limitation of the outside flight experiment, the indoor flight test environment based on multi-camera systems is proposed. Computer vision algorithms for the proposed system include camera calibration, color marker detection, and pose estimation. The well-known extended Kalman filter is used to obtain an accurate position and pose estimation for the small UAV. This paper finishes with several experiment results illustrating the performance and properties of the proposed vision-based indoor flight test environment.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.87-87
• /
• 2000

In this paper, an integrated design of fault detection, diagnosis and reconfigurable control tot multi-input and multi-output system is proposed. It is based on the interacting multiple model estimation algorithm, which is one of the most cost-effective adaptive estimation techniques for systems involving structural and/or parametric changes. This research focuses on the method to recover the performance of a system with failed actuators by switching plant models and controllers appropriately. The proposed scheme is applied to a fault tolerant control design for flight control system.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.23 no.5
• /
• pp.479-486
• /
• 2013

There exist two major difficulties in developing flight control system: nonlinear dynamic characteristics and time-varying properties of parameters of aircraft. Instead of the difficulties, many high reliable and efficient control methodologies have been developed. But, most of the developed control systems are based on the exact mathematical modelling of aircraft and, in the absence of such a model, it is very difficult to derive performance, robustness and nominal stability. From these aspects, recently, some approaches to utilizing the intelligent control theories such as fuzzy logic control, neural network and genetic algorithm have appeared. In this paper, one advanced intelligent lateral control system of a high speed fight has been developed utilizing type-2 fuzzy logic, which can deduce the uncertainty problem of the conventional fuzzy logic. The results will be verified through computer simulation.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.30 no.3
• /
• pp.46-56
• /
• 2002

In this paper, the feasibility of the attitude control of a spacecraft using pulsed plasma thrusters(PPTs) is studied. The PPT consumes less propellant mass requied for the orbit management or attitude control owing to its high specific impulse characteristics, compared with traditional gas propulsion system. The PPT is expected to be highly adequete for the missions requiring long-duration operations because it has relatively long operation time and easy implementation. The feasibility of the PPT for attitude control of a small satellite system is addressed through realistic missions. The classical PD controller and a fuzzy logic controller are tested, and fuel saving fuzzy logic controller is then proposed for more flexible mission performance.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.31 no.7
• /
• pp.75-84
• /
• 2003

To reduce the effects of the uncertainties due to the modeling error and aerodynamic coefficients, a nonlinear adaptive control system based on neural networks is proposed . Neural networks parameters are adjusted by using an adaptive law. The sliding mode control scheme is used to compensate for the effect of the approximation error of neural networks. Control parameters and neural networks structures are optimized to obtain better performance by using the genetic algorithm. By introducing the concept of multi-groups of populations, the genetic algorithm is modified so that individuals and groups can be simultaneously evolved . To verify the performance of the pro posed algorithm, the optimized neural networks control system is applied to an aircraft longitudinal dynamics.

• Journal of Aerospace System Engineering
• /
• v.18 no.4
• /
• pp.1-9
• /
• 2024

In this study, we researched control compensation techniques to enhance control robustness against external forces and responsiveness to output dead zones in direct-actuated voice coil actuators for small guided missiles. An aircraft's wings must optimally control the command angle while managing various nonlinear external forces such as drag, lift, and thrust during flight. The small direct -drive voice coil actuator, when applied, benefits from small current requirements in no-load situations but suffers from diminished control robustness due to rapid increases in control current during external force applications. To address this issue, we designed and implemented a system that compensates for errors by accumulating additional output, thus improving the actuator's responsiveness in control scenarios with external forces. This was verified through experimental results.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.16 no.6
• /
• pp.472-477
• /
• 2023

In this paper, we proposes the use of Model Predictive Control (MPC) techniques to enable quadcopter drones to effectively follow paths and maintain flight safety even under dynamic external environments and disturbances. Through simulations conducted in MATLAB/Simulink, the performance of two controllers, PID and MPC, is compared in flight scenarios with disturbances. The proposed design method shows that the MPC controller, when compared to the PID controller, exhibits a difference in the Mean Squared Error between the intended flight path and the actual path of the quadcopter drone. This difference is 0.2 in performance under no disturbance, and it increases to 0.8 under disturbance, demonstrating the improved path following accuracy of the MPC controller.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.38 no.3
• /
• pp.228-235
• /
• 2010

This paper deals with an autonomous flight controller design problem for a tilt-rotor aircraft in rotary-wing mode. The inner-loop algorithm is designed using the output-based approximate feedback linearization. The model error originated from the feedback linearization is cancelled within allowable tolerance by using single-hidden-layer neural network. According to Lyapunov direct stability theory, the adaptive update law is derived to run the neural network on-line, which is based on the linear observer dynamics. Moreover, the outer-loop algorithm is designed to track the trajectory generated from way-point guidance. Especially, heading and flight-path angle line-of-sight guidance are applied to the outer-loop to improve accuracy of the landing tracking performance. The 6-DOF nonlinear simulation shows that the overall performance of the flight control algorithm is satisfactory even though the collective input response shows instantaneous actuator saturation for a short time due to the lack of the neural network and the saturation protection logic in that loop.

• Journal of Institute of Control, Robotics and Systems
• /
• v.15 no.1
• /
• pp.61-66
• /
• 2009

This paper proposes an efficient sampled-data controller design technique for formation flying. To deal with the nonlinearity in the formation flying dynamics and to obtain a linear, rather than affine, model, we utilize the optimal linearization technique. The digital redesign technique is then developed based on the optimal linear model and formulated in terms of linear matrix inequalities. Simulation results show the advantage of the proposed methodology over the conventional controller emulation technique.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.36 no.12
• /
• pp.1152-1162
• /
• 2008

This paper deals with the State-Dependent Riccati Equation (SDRE) technique for the design of helicopter nonlinear flight controllers. Since the SDRE controller requires a linear system-like structure for nonlinear motion equations, a state-dependent coefficient (SDC) factorization technique is developed in order to derive the conforming structure from a general nonlinear helicopter dynamic model. Also on-line numerical methods of solving the algebraic Riccati equation are investigated to improve the numerical efficiency in designing the SDRE controllers. The proposed method is applied to trajectory tracking problems of the helicopter and computational tips for a real time application are proposed using a high fidelity rotorcraft mathematical model.