• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.3
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• pp.67-73
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• 2006

In this paper, a reconfigurable model following flight control method is proposed based on direct adaptive scheme using parameter estimation. Adaptive control scheme updates the control gains to make the system output follow the reference output even when fault occurs. By adopting the frequency domain parameter estimation method, system changes by the fault can be estimated. Recursive Fourier transformation is used for system identification. Using recursive Fourier transform, the proposed adaptive control algorithm guarantees the system stability and improves the system characteristics. To evaluate the performance of proposed control method, numerical simulations are performed.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.21 no.3
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• pp.1-8
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• 2013

An application of adaptive flight controller is required for the non-linear and high uncertain system that configuration of tiltrotor aircraft is dramatically changed from rotary wing mode to fixed wing mode. In this paper, the applicable adaptive controller for the tiltrotor aircraft was designed using Neural Networks and DMI (Dynamic Model Inversion). The performance of the SCAS (Stability and Control Augmentation System) was simulated against manned military specification, using the fullscale model of 'Smart UAV(Unmanned Aerial Vehicle)' developed by Korea Aerospace Research Institute. And Neural Networks based adaptive controller was verified through its whole operating envelope using the established HQ (Handling Quality) criteria.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.5
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• pp.416-422
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• 2016

This paper presents preliminary performance analysis of a satellite formation flying testbed, which is under development by Astrodynamics and Control Laboratory, Department of Astronomy, Yonsei University. A model reference adaptive controller (MRAC) with a first-order reference model is chosen to enhance the response of reaction wheel system which is subject to uncertainties caused by unmodelled dynamics and measurement noise. In addition, an on-line parameter estimation (OPE) technique based on the least square is combined to eliminate the effect of angular measurement noise by estimating the moment of inertia. Both numerical simulations and hardware experiments with MRAC support the effectiveness and applicability of the adaptive control scheme, which maintains the tracking error below $0.25^{\circ}$ for the entire time span. However, the high frequency control input generated in hardware experiment strongly suggests design modifications to reduce the effect of deadzone.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.3
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• pp.171-179
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• 1988

This paper deals with the controller design of the flight control system using the model reference adaptive control approach. The structure of the adaptive control system is based on the structure suggested by NARENDRA and VALAVANI. In particular, the problem is considered in case of the relative degree n=2 of plant. The flight control system is single-input single-output system, and the control input is given from the input-output data of the referencemodel and plant. For the analysis of the designed control system, thesimulation is perfarmed in cases of analog plant and analog plant with flight motion table, and reviewed.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.5
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• pp.342-349
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• 2013

A damage imposed on an unmanned aerial vehicle changes the flight dynamic characteristics, and makes difficult for a conventional controller based on undamaged dynamics to stabilize the vehicle with damage. This paper presents a neural network based adaptive control method that guarantees stable control performance for an unmanned aerial vehicle even with damage on the main wing. Additionally, Pseudo Control Hedging (PCH) is combined to prevent control performance degradation by actuator characteristics. Asymmetric dynamic equations for an aircraft are chosen to describe motions of a vehicle with damage. Aerodynamic data from wind tunnel test for an undamaged model and a damaged model are used for numerical validation of the proposed control method. The numerical simulation has shown that the proposed control method has robust control performance in the presence of wing damage.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.2
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• pp.114-121
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• 2019

Tailless aircraft have advantages of low visibility compared to conventional aircraft, but drawback of poor stability as well which makes designing controller difficult. The controller design is more difficult, especially when the center of gravity moves due to store release or fuel consumption during flight. In this paper, an L1 adaptive controller is proposed as a way to overcome these problems. The reliability and performance of the controllers were verified by non-linear simulations. RPV Flying Quality Design criteria were used for design criteria. Using the simulation, it is shown that the adaptive controller maintains stability of the unmanned aircraft for sudden large change in the inertial properties. It is also shown that the calculation burden can be reduced when it is used with the gain scheduling method.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.5
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• pp.464-469
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• 2009

In this study, a new fault tolerant controller based on a model following adaptive technique is applied to the reconfiguration mode of supersonic advanced trainer. The designed controller is applied to the flight control system of high performance aircraft. To verify the performance of the proposed controller, numerical simulations are executed using a non-realtime nonlinear verification tool.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.3
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• pp.228-235
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• 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 the Korean Society for Aeronautical & Space Sciences
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• v.42 no.10
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• pp.842-850
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• 2014

This paper presents a trajectory tracking controller for rotorcraft UAVs to improve the tracking performances in the presence of various uncertainties. The proposed tracking method consists of a velocity guidance law based on the relative distance and L1 adaptive augmentation loop for tracking the velocity commands. In the proposed structure, the desired velocity generated by the guidance law is the reference value of the adaptive controller for accurate path tracking. In the guidance law, the desired acceleration is generated based on the relative distance and its derivatives, and then the velocity command of the inner control loop is calculated by integrating the accelerations. $L_1$ augmentation loop supplements the linear controller to guarantee the flight performances such as a tracking accuracy in the presence of the uncertainties. The proposed controller was validated in actual flight tests to successfully demonstrate its capability using a quadrotor UAV.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.2
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• pp.141-149
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• 2018

This paper presents a neural network controller design for complex damage to a blended wing Unmanned Aerial Vehicle(UAV): partial loss of main wing and vertical tail. Longitudinal/lateral axis instability and the change of flight dynamics is investigated via numerical simulation. Based on this, neural network based adaptive controller combined with two types of feedback linearization are designed in order to compensate for the complex damage. Performance of two kinds of dynamic inversion controllers is analyzed against complex damage. According to the structure of the dynamic inversion controller, the performance difference is confirmed in normal situation and under damaged situation. Numerical simulation verifies that the instability from the complex damage of the UAV can be stabilized via the proposed adaptive controller.