조광현 교수

This paper presents a novel disturbance compensation scheme to attenuate periodic disturbances on repetitive motion using permanent magnet linear synchronous motors (PMLSMs), and this scheme is called the periodical adaptive disturbance observer. The scheme is based on assumptions that all measured states and disturbances are periodic and repetitive when the tasks executed by PMLSM motion systems have periodic and repetitive characteristics. In the proposed control scheme, a lumped disturbance i

BACKGROUND: We consider the problem of identifying the dynamic interactions in biochemical networks from noisy experimental data. Typically, approaches for solving this problem make use of an estimation algorithm such as the well-known linear Least-Squares (LS) estimation technique. We demonstrate that when time-series measurements are corrupted by white noise and/or drift noise, more accurate and reliable identification of network interactions can be achieved by employing an estimation algorith

Airbag systems have become an essential safety device for guaranteeing the physical well-being of drivers and their passengers. Unlike other safety devices, airbags are used as the last resort in a collision, and because they are directly linked to the life of the driver and passengers, the proper functioning of the system is an issue of paramount importance. Hence, to ensure the precision and reliability of airbag operation, it is necessary to design a robust crash algorithm. Currently, several

This paper proposes the vehicle longitudinal controller for the Anti-lock Braking System(ABS) and Traction Control System(TCS). The sliding mode control scheme without a sign function is used to design a controller. Instead of a sign function, the adaptation mechanism is used to reduce the actuator chattering as a problem of the sliding mode control. The proposed systems use the equivalent model from engine to wheel to control the brake and engine actuator. Using the integrated logic frame, it r

For vehicle stability control system to function properly under a variety of changing road conditions and driver's inputs, precise estimations of vehicle states are necessarily required. In particular, information on the side-slip angle is critical to vehicle handling and safety control. Since commercial sensors measuring the side-slip angle are not cost effective, estimation methods that use available sensor measurements and vehicle dynamics models are necessarily required. This paper proposes

This study investigates the long-term instability problem of periodic-feedback-loop-based control schemes such as repetitive control, periodic adaptive disturbance observer (PADOB), and iterative learning control. The long-term instability problem is the one wherein a closed-loop system becomes unstable because a tracking error diverges with the increase in the number of iterations. A novel robust PADOB is proposed in this article to guarantee the long-term stability of the closed-loop system. T

The airbag system has been a standard safety equipment for vehicles and it is efficient for enhancing the safety of a driver and passengers from crash. However, inadvertent injuries have been caused by airbag deployment in a rough and uncertain temporal interval. In this paper, a pre-crash discrimination system is proposed to prevent airbag deployment from malfunction. The system consists of a radar sensor of ACC system and vehicle state sensors of VDC system. The pre-crash information includes

This paper demonstrates a method for compensating the gravity component of the lateral acceleration through the estimation of the roll angle. The lateral acceleration has a direct influence on the road disturbance and suspension motion by driver's steering input. It is difficult to differenciate the bias(gravity component) induced by the road bank disturbance and suspension motion from the actual lateral acceleration measured by a sensor. Although the roll rate sensor can estimate the roll angle

This study is concerned with the problem of system identification for permanent magnet linear synchronous motor(PMLSM) based motion systems with disturbances such as parametric uncertainty, friction force, and force ripple. In order to identify the disturbances, a novel system identification method is proposed. The main idea of the proposed scheme is to separate and identify each element from a lumped disturbance by using even and odd characteristics of the state-dependent disturbances. The lump

This paper proposes a periodic adaptive disturbance observer (PADOB) for a precision position control of a PMLSM (Permanent Magnet Linear Synchronous Motor), which is based on a periodic adaptive learning control(PALC). It updates the output of a classical linear DOB to compensate modeling errors between a nominal plant and actual plant and external disturbance forces such as the friction and detent force. Therefore, it can improve problems occured by inaccurate parameters of the nominal plant a

This study is concerned with the problem of compensating for periodic disturbances under repetitive motion conditions. In order to achieve high precision positioning for high load systems with periodic disturbances, a practical motion control scheme based on a multi-rate periodic adaptive disturbance observer (MPADOB) is proposed. Nonlinear disturbances such as the force ripple, friction force, and cable tension force occur when linear actuators for high load systems are used on linear motors wi

This paper proposes a periodic adaptive disturbance observer (PADOB) to control a PMLSM (Permanent Magnet Linear Synchronous Motor). The PADOB consists of a classical linear DOB and an adaptive mechanism which has been known as the periodic adaptive learning control (PALC). The key idea is to compensate parametric errors between the actual plant and the nominal model of DOB and disturbance forces such as the friction and detent force. The PADOB can improve the instability problem occurred by upd