1-5hit |
Tae Hoon LEE Won Sang RA Seung Hee JIN Tae Sung YOON Jin Bae PARK
A new robust extended Kalman filter is proposed for the discrete-time nonlinear systems with norm-bounded parameter uncertainties. After linearization of the nonlinear systems, the uncertainties described by the energy bounded constraint can be converted into an indefinite quadratic cost function to be minimized. The solution to the minimization problem is given by the extended Kalman filter derived in a Krein space, which leads to a robust version of the extended Kalman filter. Since the resulting robust filter has the same structure as a standard extended Kalman filter, the proposed filter can be readily designed by simply including the uncertainty terms in its formulas. The results of simulations are presented to demonstrate that the proposed filter achieves the robustness against parameter variation and performs better than the standard extended Kalman filter.
Min Kook SONG Jin Bae PARK Young Hoon JOO
This paper is concerned with exploring an extended approach for the stability analysis and synthesis for Markovian jump nonlinear systems (MJNLSs) via fuzzy control. The Takagi-Sugeno (T-S) fuzzy model is employed to represent the MJNLSs with incomplete transition description. In this paper, not all the elements of the rate transition matrices (RTMs), or probability transition matrices (PTMs) are assumed to be known. By fully considering the properties of the RTMs and PTMs, sufficient criteria of stability and stabilization is obtained in both continuous and discrete-time. Stabilization conditions with a mode-dependent fuzzy controller are derived for Markovian jump fuzzy systems in terms of linear matrix inequalities (LMIs), which can be readily solved by using existing LMI optimization techniques. Finally, illustrative numerical examples are provided to demonstrate the effectiveness of the proposed approach.
Yong Hwi KIM Ka Hyung CHOI Tae Sung YOON Jin Bae PARK
An instrumental variable (IV) based linear estimator is proposed for effective target localization in sensor network by using time-difference-of-arrival (TDOA) measurement. Although some linear estimation approaches have been proposed in much literature, the target localization based on TDOA measurement still has a room for improvement. Therefore, we analyze the estimation errors of existing localization estimators such as the well-known quadratic correction least squares (QCLS) and the robust least squares (RoLS), and demonstrate advantages of the proposition by comparing the estimation errors mathematically and showing localization results through simulation. In addition, a recursive form of the proposition is derived to consider a real time application.
Jae Man KIM Yoon Ho CHOI Jin Bae PARK
This paper investigates the consensus problem of heterogeneous uncertain multi-agent systems with jointly connected topology, where the considered systems are composed of linear first-order, second-order dynamics and nonlinear Euler-Lagrange (EL) dynamics. The consensus protocol is designed to converge the position and velocity states of the linear and nonlinear heterogeneous multi-agent systems under joint connected topology, and then the adaptive consensus protocol is also proposed for heterogeneous multi-agent systems with unknown parameters in the EL dynamics under jointly connected topology. Stability analysis for piecewise continuous functions induced by the jointly connection is presented based on Lyapunov function and Cauchy's convergence criteria. Finally, some simulation results are provided to verify the effectiveness of the proposed methods.
Kyoung Joo KIM Jin Bae PARK Yoon Ho CHOI
In this paper, we propose a novel path tracking control algorithm for an underactuated autonomous underwater vehicle (AUV). The underactuated AUV is controlled by the thrust force and the yaw torque: no sway thruster is used. To deal with this underactuated AUV problem in the path tracking, we introduce an approach angle which makes the AUV converge to the reference path. To design the path tracking controller, we obtain the vehicle's error dynamics in the body-fixed frame, and then design the path tracking controller based on the dynamic surface control (DSC) method. The proposed controller only needs the information of the position and the heading angle of the reference path. Some simulation results demonstrate the effectiveness of the proposed controller.