• 제어로봇시스템학회논문지
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• 제13권5호
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• pp.422-428
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• 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.

• International Journal of Aeronautical and Space Sciences
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• 제18권2호
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• pp.290-299
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• 2017

Reconfigurable flight control using various kinds of adaptive control methods has been studied since the 1970s to enhance the survivability of aircraft in case of severe in-flight failure. Early studies were mainly focused on the failure of actuators. Recently, studies of reconfigurable flight controls that can accommodate complex damage (partial wing and tail loss) in conventional aircraft were reported. However, the partial wing loss effects on the aerodynamics of conventional type aircraft are quite different to those of BWB(blended wing body) aircraft. In this paper, a reconfigurable flight control algorithm was designed using a direct model reference adaptive method to overcome the instability caused by a complex damage of a BWB aircraft. A model reference adaptive control was incorporated into the inner loop rate control system enhancing the performance of the baseline control to cope with abrupt loss of stability. Gains of the model reference adaptive control were polled out using the Liapunov's stability theorem. Outer loop attitude autopilot was designed to manage roll and pitch of the BWB UAV as well. A 6-DOF dynamic model was built-up, where the normal flight can be made to switch to the damaged state abruptly reflecting the possible real flight situation. 22% of right wing loss as well as 25% loss for both vertical tail and rudder control surface were considered in this study. Static aerodynamic coefficients were obtained via wind tunnel test. Numerical simulations were conducted to demonstrate the performance of the reconfigurable flight control system.

• 제어로봇시스템학회논문지
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• 제9권2호
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• pp.99-106
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• 2003

A new reconfigurable model following flight control method based on direct adaptive scheme is presented. Using the timescale separation principle, both the inner-loop and the outer-loop states are controlled simultaneously. For the timescale separation assumption to be satisfied, the inner-loop model dynamics is set to be fast whereas the outer-loop model dynamics is set to be relatively slow. The stability and convergence of the proposed control law is proved by Lyapunov theorem. One of the merits of the proposed reconfigurable controller is that the FDI process and the persistent input excitation are not necessary, which is suitable for the flight control system. To evaluate the reconfiguration performance of the proposed control method, numerical simulation is performed using six degree-of-freedom nonlinear dynamics.

• 로봇학회논문지
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• 제6권2호
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• pp.97-107
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• 2011

This paper describes efficient flight control algorithms for building a reconfigurable ad-hoc wireless sensor networks between nodes on the ground and airborne nodes mounted on autonomous vehicles to increase the operational range of an aerial robot or the communication connectivity. Two autonomous flight control algorithms based on adaptive gradient climbing approach are developed to steer the aerial vehicles to reach optimal locations for the maximum communication throughputs in the airborne sensor networks. The first autonomous vehicle control algorithm is presented for seeking the source of a scalar signal by directly using the extremum-seeking based forward surge control approach with no position information of the aerial vehicle. The second flight control algorithm is developed with the angular rate command by integrating an adaptive gradient climbing technique which uses an on-line gradient estimator to identify the derivative of a performance cost function. They incorporate the network performance into the feedback path to mitigate interference and noise. A communication propagation model is used to predict the link quality of the communication connectivity between distributed nodes. Simulation study is conducted to evaluate the effectiveness of the proposed reconfigurable airborne wireless networking control algorithms.

• 제어로봇시스템학회논문지
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• 제10권2호
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• pp.112-124
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• 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.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.40.2-40
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• 2002

This paper presents the reconfigurable flight controller in the presence of jammed actuator fault using the adaptive sliding mode control scheme. It is developed under the assumption that the control surface fault cannot be detected and the positions of stuck control surfaces are unknown. It is well known that sliding mode controller shows good performance for the systems with various uncertainties. None-operating stuck actuator makes the system behave like bias which degrades the system performance and sometimes destabilizes the system. Therefore, the bias term generated by actuator faults has to be compensated by the control system. To the objective, we adopt the adaptive sliding mode cont...

• 제어로봇시스템학회논문지
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• 제9권4호
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• pp.329-339
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• 2003

A neural network based adaptive controller design method is proposed for reconfigurable flight control systems in the presence of variations in aerodynamic coefficients or control effectiveness decrease caused by control surface damage. The neural network based adaptive nonlinear controller is developed by making use of the backstepping technique for command following of the angle of attack, sideslip angle, and bank angle. On-line teaming neural networks are implemented to guarantee reconfigurability and robustness to the uncertainties caused by aerodynamic coefficients variations. The main feature of the proposed controller is that the adaptive controller is designed with assumption that not any of the nonlinear functions of the system is known accurately, whereas most of the previous works assume that only some of the nonlinear functions are unknown. Neural networks loam through the weight update rules that are derived from the Lyapunov control theory. The closed-loop stability of the error states is also investigated according to the Lyapunov theory. A nonlinear dynamic model of an F-16 aircraft is used to demonstrate the effectiveness of the proposed control law.

• 한국항공우주학회지
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• 제34권3호
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• pp.67-73
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• 2006

본 논문에서는 매개변수 추종기법과 모델추종 적응제어기법을 이용하여 재형상 모델 추종 비행제어기법을 제안하였다. 기준 모델을 추종하기 위하여 모델의 신호와 입력, 오차를 이용하여 적응제어기를 구성하였다. 고장이 발생하는 경우 시스템에 발생하는 불확실성에 대처하기 위해 시스템 식별기법을 도입하였으며, 역변환 계산의 용이성을 위해 회귀적 재귀 푸리에 변환기법을 사용하였다. 회귀적 재귀 푸리에 변환을 이용한 적응제어기법을 통해 고장에 능동적으로 대처하는 비행제어시스템을 구성하였으며, 항공기 제어면 파손을 모사하기 위하여 안정미계수 및 조종미계수 기법을 이용하여 고장을 정식화 하였다. 수치 시뮬레이션을 통해 제안된 제어시스템의 타당성을 검증하였다.

• International Journal of Aerospace System Engineering
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• 제4권1호
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• pp.1-8
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• 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.

• 한국항공우주학회지
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• 제39권7호
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• pp.660-665
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• 2011

공대공 공대지 가상 공중 교전모의시험이 가능한 가상현실기술이 구현된 가변형 비행 시뮬레이터를 개발하였다. 가변형 비행시뮬레이터의 가변 조종실은 국내에서 운용 중인 F-15K, KF-16, T/A-50 급 기종 모의가 가능하며, 터치형 액정시현기를 활용하여 그래픽 계기를 구현함으로써 누구나 손쉽고 빠르게 기종변경이 가능하다. 조종간과 쓰로틀은 모의기종에 맞게 교체가 가능하며, 외부영상시현장치는 국내최초로 Video See-Through Type HMD를 적용하여 조종사의 몰입감을 최대화 시킬 수 있도록 구성하였다.