• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1500-1503
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• 1996

This paper combines the disturbance accommodating control(DAC) and nonlinear model inversion control for a skid-to-turn(STT) missile. The missile autopilot may be designed to be robust with respect to a variety of uncertainties. We proposes the two step control design method. Nonlinear model inversion control is used as the main design method. Due to the model uncertainties and external disturbances, the exact nonlinear model inversion can not be achieved. DAC is designed to detect, to identify, and to compensate these uncertainties. DAC's disturbance observer is linear. Thus it is easy to implement. It does not cause the convergence problem due to coexistence between the modeling uncertainties and external disturbances. 6 DOF simulation results show that the proposed method may improve the missile tracking performance.

• Journal of the Korea Institute of Military Science and Technology
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• v.10 no.2
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• pp.53-60
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• 2007

This paper presents a robust nonlinear autopilot design method based on dynamic inversion and PI(Proportional-Integral) control law. The new controller structure which is different from previous work is composed of classical linear PI control law and nonlinear fast dynamic inversion. A pitch axis model of highly maneuverable missiles and a linearized model for designing Pl controller are presented. The performance of proposed method is illustrated via nonlinear simulations including aerodynamic uncertainties and actuator dynamics.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1492-1495
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• 1996

In this paper, an approach to autopilot design based on the robust nonlinear dynamic inversion method is proposed. Both unknown parameters and uncertainty bounds are estimated and parameter estimates are used in the fast inversion. Furthermore, to get more robustness slow inversion is incorporated with MRAC(Model Reference Adaptive Control) and sliding mode control where the estimates of uncertainty bounds are used. The proposed method is applied to the pitch autopilot design of a missile system and excellent performance is shown via computer simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.7
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• pp.574-581
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• 2001

In this paper we design and evaluate the longitudinal nonlinear N(aub)z-CSAS(Command and Stability Augmentation System) flight control law in \"DMI(Dynamic Model Inversion)-method\" and classical \"Gain Scheduling-method\", respectively, to meet the handling quality requirements associated with push-over pull-up maneuver. It is told that the flight control law designed in \"DM-method\" is adequate to the full flight regime without gain scheduling and is efficient to produce the time response shape desired to the handling quality requirements. On the contrary, the flight control law designed in \"Gain Scheduling-method\" is easy to be implemented in flight control computer and insensitive to variation of the actuator model characteristics.n of the actuator model characteristics.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.3
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• pp.207-213
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• 2005

This paper deals with an autonomous flight guidance and control algorithm design for TR301 tilt-rotor airplane under development by Korea Aerospace Research Institute for simulation purpose. The objective of this study is to design autonomous flight algorithm in which the tilt-rotor airplane should follow the given waypoints precisely. The approach to this objective in this study is that, first of all, model-based inversion is applied to the highly nonlinear tilt-rotor dynamics, where the tilt-rotor airplane is assumed to fly at helicopter flight mode(nacelle angle=0 deg), and then the control algorithm, based on classical control, is designed to satisfy overall system stabilization and precise waypoint following performance. Especially, model uncertainties due to the tiltrotor model itself and inversion process are adaptively compensated in a simple neural network(Sigma-Phi NN) for performance robustness. The designed algorithm is evaluated in the tilt-rotor nonlinear airplane in helicopter flight mode to analyze the following performance for given waypoints. The simulation results show that the waypoint following responses for this algorithm are satisfactory, and control input responses are within control limits without saturation.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.35 no.11
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• pp.990-998
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• 2007

Adaptive output feedback control technique using Neural Networks(NN) is proposed for uncertain nonlinear Multi-Input Multi-Output(MIMO) systems. Modified Dynamic Inversion Model(MDIM) is introduced to decouple uncertain nonlinearities from inversion-based control input. MDIM consists of approximated dynamic inversion model and inversion model error. One NN is applied to compensate the MDIM of the system. The output of the NN augments the tracking controller which is based upon a filtered error approximation with online weight adaptation laws which are derived from Lyapunov's direct method to guarantee tracking performance and ultimate boundedness. Several numerical results are illustrated in the simulation of Van der Pol system and unmanned helicopter with model uncertainties.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.57-62
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• 2004

This paper deals with a waypoint trajectory following problem for the tilt-rotor UAV under development in Korea (TR-KUAV). In this problem, dynamic model inversion based on the linearized model and Sigma-Phi neural network with adaptive weight update are involved to realize the waypoint following algorithm for the vehicle in the helicopter flight mode (nacelle angle=0 deg). This algorithms consists of two main parts: outer-loop system as a command generator and inner-loop system as stabilizing controller. In this waypoint following problem, the position information in the inertial axis is given to the outer-loop system. From this information, Attitude Command/Attitude Hold logic in the longitudinal channel and Rate Command/Attitude Hold logic in the lateral channel are realized in the inner-loop part of the overall structure of the waypoint following algorithm. The nonlinear simulation based on the TR-KUAV is carried out to evaluate the stability and performance of the algorithm. From the numerical simulation results, the algorithm shows very good tracking performance of passing the waypoints given. Especially, it is observed that ACAH/RCAH logic in the inner-loop has the satisfactory performance due to adaptive neural network in spite of the model error coming from the linear model based inversion.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1074-1078
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• 2005

In precision positioning applications, such as scanning tunneling microscopy and diamond turning machines [1], it is often required that actuators have nanometer resolution in displacement, high stiffness, and fast frequency response. These requirements are met by the use of piezoceramic actuators. A major limitation of piezoceramic actuators, however, is their lack of accuracy due to hysteresis nonlinearity and drift. The maximum error due to hysteresis can be as much as 10-15% of the path covered if the actuators are run in an open-loop fashion. Hence, the accurate control of piezoceramic actuators requires a control strategy that incorporates some form of compensation for the hysteresis. One approach is to develop an accurate model of the hysteresis and the use the inverse as a compensator. The Preisach model has frequently been employed as a nonlinear model for representing the hysteresis, because it encompasses the basic features of the hysteresis phenomena in a conceptually simple and mathematically elegant way. In this paper, a new numerical inversion scheme of the Preisach model is developed with an aim of compensating hysteresis in piezoceramic actuators. The inversion scheme is implemented using the first-order reversal functions and is presented in a recursive form. The inverted model is then incorporated in an open-loop control strategy that regulates the piezoceramic actuator and compensates for hysteretic effects. Experimental results demonstrate satisfactory regulation of the position of the piezoceramic actuator to the desired trajectories.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.12
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• pp.857-866
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• 2022

Fixed-wing UAVs have long endurance and range capabilities compared to other aerial platforms. These advantages led fixed-wing UAVs to become a popular platform for reconnaissance missions in the military. In this research, we modeled fixed-wing UAVs, including the landing gear model and developed a guidance and control system for flight control computers to construct a HILS environment. We also developed an autopilot system that includes automated take-off, cruise, and landing control for UAVs. We also retrived the Aerodynamic coefficients an UAV using Datcom and AVL software and used them for 6 degrees of freedom modeling. The Flight control computer calculates guidance commands using the Carrot chasing guidance law after distinguishing the condition of the UAV based on 16 pre-defined flight modes and calculates control inputs using Nonlinear Dynamic Inversion (NDI) control scheme. We used RTNngine to integrate the Simulink model and flight control computer for HILS environment formulation.

• International Journal of Control, Automation, and Systems
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• v.1 no.3
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• pp.315-320
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• 2003

This paper presents a control augmentation system (CAS) based on the dynamic model inversion (DMI) architecture for a highly maneuverable aircraft. In the application of DMI not treating actuator dynamics, significant instabilities arise due to limitations on the aircraft inputs, such as actuator time delay based on dynamics and actuator displacement limit. Actuator input saturation usually occurs during high angles of attack maneuvering in low dynamic pressure conditions. The pseudo-control hedging (PCH) algorithm is applied to prevent or delay the instability of the CAS due to a slow actuator or occurrence of actuator saturation. The performance of the proposed CAS with PCH architecture is demonstrated through a nonlinear flight simulation.