• 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 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.

• 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 Aerospace System Engineering
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• v.8 no.4
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• pp.24-31
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• 2014

The modern version of aircrafts is allowed to guarantee the superior handing qualities within the entire flight envelope by imposing the adequate stability and flying qualities on a target aircraft through the various techniques of flight control law design. Generally, the flight control law of the aircraft in service applies the various techniques of the verified control algorithm, such as dynamic inversion and eigenstructure assignment. The supersonic trainer employs the RSS(Relaxed Static Stability) concept in order to improve the aerodynamic performance in longitudinal axis and the longitudinal control laws employ the dynamic inversion with proportional-plus-integral control method. And, lateral-directional control laws employ the blended roll system of both beta-betadot feedback and simple roll rate feedback with proportional control method in order to guarantee aircraft stability. In this paper, the lateral-directional flight control law is designed by applying dynamic inversion control technique as a different method from the current supersonic trainer control technique, where the roll rate command system is designed at the lateral axis for the rapid response characteristics, and the sideslip command system is adopted at the directional axis for stability augmentation. The dynamic inversion of a simple 1st order model is applied. And this designed flight control law is confirmed to satisfy the requirement presented from the military specification. This study is expected to contribute to design the flight control law of KF-X(Korean Fighter eXperimental) which will proceed into the full-scale development in the near future.

• International Journal of Aeronautical and Space Sciences
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• v.7 no.2
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• pp.137-144
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• 2006

The objective of this paper is to present trajectory guidance and control system with a dynamic inversion for a small unmanned aerial vehicle (UAV). The UAV model is expressed by fixed-mass rigid-body six-degree-of-freedom equations of motion, which include the detailed aerodynamic coefficients, the engine model and the actuator models that have lags and limits. A trajectory is generated from the given waypoints using cubic spline functions of a flight distance. The commanded values of an angle of attack, a sideslip angle, a bank angle and a thrust, are calculated from guidance forces to trace the flight trajectory. To adapt various waypoint locations, a proportional navigation is combined with the guidance system. By the decision logic, appropriate guidance law is selected. The flight control system to achieve the commands is designed using a dynamic inversion approach. For a dynamic inversion controller we use the two-timescale assumption that separates the fast dynamics, involving the angular rates of the aircraft, from the slow dynamics, which include angle of attack, sideslip angle, and bank angle. Some numerical simulations are conducted to see the performance of the proposed guidance and control system.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.4
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• pp.335-341
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• 2010

To improve the performance of inner loop based on PD controller for a unmanned helicopter, neural networks are applied. The performance of PD controller designed on the response characteristics of error dynamics decreases because of uncertain nonlinearities of the system. The nonlinearities are decoupled to modified dynamic inversion model(MDIM) and are compensated by the neural networks. For the training of the neural networks, online weight adaptation laws which are derived from Lyapunov's direct method are used to guarantee the stability of the controller. The results of the improved performance of PD controller by neural networks are illustrated in the simulation of unmanned helicopter with nonlinearities,

• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.4
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• pp.329-334
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• 2010

This paper presents the design of a neural network based adaptive control for missile. Acceleration of missile by tail fin control cannot be controllable by DMI (Dynamic Model Inversion) directly because it is non-minimum phase system. To avoid the non-minimum phase system, dynamic model inversion is applied with output-redefinition method. In order to evaluate performance of the suggested controllers we selected the three cases such as control surface fail, control surface loss and wing loss for model uncertainty. The corresponding aerodynamic databases to the failure cases were calculated by using the Missile DATACOM. Using a high fidelity 6DOF simulation program of the missile the performance was evaluates.

• 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.