Youdan Kim

Adaptive Sliding Mode Controller Design for Fault Tolerant Flight Control System

In this study, a fault tolerant flight control system based on adaptive and sliding mode control scheme is proposed. The merits of adaptive and sliding mode control scheme are that (i) the magnitude of sliding mode controller gain can be reduced and (ii) the fault detection and isolation process is not required. Using the timescale separation principle, the aircraft system can be decomposed into fast inner-loop dynamics and slow outer-loop dynamics. Angular velocity components are used as virtual inputs for the slow dynamics, which are angular variables in the outer-loop control system. The inner-loop controller is designed to make the fast states, that is, angular velocities, follow the outer-loop control input trajectories using the aileron, elevator, and rudder to complete the maneuver. The stability analysis of the proposed control law is performed using Lyapunov theory and LaSalleYoshizawa theorem. To verify the effectiveness of the proposed control scheme, numerical simulation is performed for a high performance six degree of freedom nonlinear aircraft model. Simulation results demonstrate that the closed-loop system has good performance in spite of the actuator fault and the nonlinearity of aircraft system.

Adaptive support vector regression for UAV flight control

This paper explores an application of support vector regression for adaptive control of an unmanned aerial vehicle (UAV). Unlike neural networks, support vector regression (SVR) generates global solutions, because SVR basically solves quadratic programming (QP) problems. With this advantage, the input-output feedback-linearized inverse dynamic model and the compensation term for the inversion error are identified off-line, which we call I-SVR (inversion SVR) and C-SVR (compensation SVR), respectively. In order to compensate for the inversion error and the unexpected uncertainty, an online adaptation algorithm for the C-SVR is proposed. Then, the stability of the overall error dynamics is analyzed by the uniformly ultimately bounded property in the nonlinear system theory. In order to validate the effectiveness of the proposed adaptive controller, numerical simulations are performed on the UAV model.

Pursuit Guidance Law and Adaptive Backstepping Controller Design for Vision-Based Net-Recovery UAV

This paper presents a guidance law and a nonlinear controller for a vision-based netrecovery UAV. A vision sensor enhances the performance of precise interception with an accurate impact angle, which can be applied for the net-recovery UAV system. A pursuit guidance law and an adaptive backstepping controller are adopted for the vision-based netrecovery instead of tracking the pre-designed glide slope. The landing performance of a pure pursuit guidance, a lead pursuit guidance, and a pseudo pursuit guidance is compared. Dynamic characteristics of aircraft states and control surface actuators are considered in the design of the constrained adaptive backstepping controller. Six degree-of-freedom nonlinear aircraft landing simulation was performed to verify the performance of the proposed guidance law and controller.

Adaptive sliding mode control using slack variables for affine underactuated systems

This paper presents an adaptive sliding mode control scheme using slack variables for affine and underactuated nonlinear systems. Slack variables are introduced to overcome the underactuated properties. A proper slack variable generating method is proposed to guarantee the stability of the proposed controller. Lyapunov stability theorem and LaSalles invariance theorem are used to analyze the stability of the proposed nonlinear control scheme. Numerical simulations are performed for a quadrotor Unmanned Aerial Vehicle, one of the affine underactuated systems, to verify the proposed control scheme.

Asymptotic attitude tracking of the rotorcraft-based UAV via RISE feedback and NN feedforward

This paper presents an asymptotic attitude tracking controller for a rotorcraft-based unmanned aerial vehicle (RUAV) using the robust integral of the signum of the error(RISE) feedback and neural network (NN) feedforward terms. Usually, the typical NN-based attitude controller guarantees the uniformly ultimately bounded stability. In this study, semi-global asymptotic tracking of the RUAV is guaranteed by the RISE feedback term and NN feedforward term adapted by the projection method. The controller is basically designed by the linear dynamic model inversion method whose model is obtained by the linearization of the nonlinear RUAV model at the hover flight. Then, the uncertainty generated in the linearization is removed by the RISE feedback and NN feedforward terms. The asymptotic tracking of the attitude states is proven with the Lyapunov stability analysis, and a numerical simulation using the nonlinear RUAV model is performed to validate the effectiveness of the proposed controller.

Adaptive feedback linearization for an uncertain nonlinear system using support vector regression

This paper explores an adaptive feedback linearization for an uncertain nonlinear system using support vector regression (SVR). SVR, which assures global solution by quadratic programming (QP) problem, is used to learn the nominal dynamics of the input-output feedback-linearized system. Then, an adaptation algorithm of the offline-trained SVR is proposed for eliminating the offline-training error and uncertainties in the control process. In addition, the derivation of the adaptive rule considers the controller singularity problem by utilizing the affine property of the nonlinear system and the concept of the virtual control. Uniformly ultimately bound property of the overall system is analyzed by the Lyapunov stability theory. Simulations using a longitudinal dynamics of the F-16 model validate the performance of the proposed approach.

Spiral Landing Trajectory and Pursuit Guidance Law Design for Vision-Based Net-Recovery UAV

This paper deals with spiral landing trajectory and terminal landing guidance law for a net-recovery landing of a fixed-wing UAV(Unmanned Aerial Vehicle). The net-recovery landing flight is divided into two phases. In the first phase, a spiral descending path is designed from any initial position to a final approaching waypoint toward a recovery net. The flight path angle of the UAV is controlled to be aligned to the approaching direction at the end of the spiral descent. In the second phase, the aircraft is directly guided from the approaching waypoint to the recovery net with a pseudo pursuit landing guidance law. Sequential imaginary landing and approaching points are generated using a cubic polynomial in the pseudo pursuit landing guidance law. Therefore, the UAV at high altitude with any heading angle can spiral down toward the recovery net without loitering and can fly into the recovery net smoothly. Six degree-of-freedom numerical simulation is performed to verify the performance of the spiral descent path and pseudo pursuit guidance law. Nomenclature α = angle of attack β = angle of sideslip γ = flight path angle a δ = aileron deflection angle e δ = elevator deflection angle r δ = rudder deflection angle A η = heading angle of aircraft ,0 c

Adaptive Sliding Mode Control for Non-affine Nonlinear Vehicle Systems

This paper presents an adaptive sliding mode control method for non-affine and nonsquare nonlinear systems. By differentiating the nonlinear dynamic equation, an increasedorder nonlinear system is obtained, and the derivative of the control signal can be used as a new control variable. To overcome the non-square property of the system, the slack variable vector is introduced to make the system input influence matrix square. A systematic procedure is developed and related theoretical and practical issues are discussed. Stability and robustness of the proposed control scheme are also analyzed using Lyapunov approach and LaSalle-Yoshizawa theorem. Numerical simulations performed for a nonlinear UAV and a supercavitation vehicle model demonstrate that the closed-loop system has good performance.

Guidance Law for Stando Tracking of a Moving Target with Leader-Follower Unmanned Aerial Vehicles

A guidance law that enables a coordinated surveillance and target acquisition is proposed to make multiple xed-wing aircraft circle around a moving target while maintaining a speci c distance from it with a desired circling rate. The stabilization of a spherical pendulum to a conical motion is applied to the aircraft motion in order to obtain the stando tracking guidance law. Aircraft acceleration commands are designed to regulate the errors between the current position and the desired position using the Lyapunov stability theory and backstepping scheme. The coordinated stando tracking with multiple aircraft is accomplished by applying the proposed guidance law to the leader-follower formation. Numerical simulation was performed to verify the e ectiveness of the proposed method. Multiple aircraft are successfully guided to a circular motion around a moving target while maintaining tight spatial phase spacing to the neighboring aircraft.

Fault-Tolerant Attitude Estimation for Satellite Using Federated Unscented Kalman Filter

Satellites provide various services essential to the modern life of human being. For example, satellite images are used for many applications such as reconnaissance, geographic information system, etc. Therefore, design and operation requirements of the satellite system have become more severe, and also the system reliability during the operation is required. Satellite attitude control systems including sensors and actuators are critical subsystems, and any fault in the satellite control system can result in serious problems. To deal with this problem, various attitude estimation algorithms using multiple sensors have been actively studied for fault tolerant satellite system (Edelmayer & Miranda, 2007; Jiancheng & Ali, 2005; Karlgaard & Schaub, 2008; Kerr, 1987; Xu, 2009). Satellites use various attitude sensors such as gyroscopes, sun sensors, star sensors, magnetometers, and so on. With these sensors, satellite attitude information can be obtained using the estimation algorithms including Kalman filter, extended Kalman filter (EKF), unscented Kalman filter (UKF), and particle filter. Agrawal et al. and Nagendra et al. presented the attitude estimation algorithm based on Kalman filter for satellite system (Agrawal & Palermo, 2002; Nagendra et al., 2002). Mehra and Bayard dealt with the problems of satellite attitude estimation based on the EKF algorithm using the gyroscope and star tracker as attitude sensors (Mehra & Bayard, 1995). In the EKF algorithm, the nonlinearities of the satellite system are approximated by the first-order Taylor series expansion, and therefore it sometimes provides undesired estimates when the system has severe nonlinearities. Recently, researches on UKF have been performed because the UKF can capture the posterior mean and covariance to the third order of nonlinear system. It is known that the UKF can provide better results for the estimation of highly nonlinear systems than EKF (Crassidis & Markley, 2003; Jin et al., 2008; Julier & Uhlmann, 2004). Crassidis and Markley proposed the attitude estimation algorithm based on unscented filter, and showed that the fast convergence can be obtained even with inaccurate initial conditions. The UKF was used to solve the relative attitude estimation problem using the modified Rodrigure parameter (MRP), where the gyroscope, star tracker, and laser rendezvous radar were employed as the attitude sensors (Jin et al., 2008). For multi-sensor systems, there are two different filter schemes for the measured sensor data process: centralized Kalman fileter (CKF) and decentralized Kalman filter (DKF) (Kim & Hong, 2003). In the CKF, all measured sensor data are processed in the center site, and