Hyun-Sik Ahn

Iterative learning control in feedback systems

Abstract An iterative learning control method is proposed to achieve precise tracking control of a class of nonlinear systems over a finite time interval. The learning is done in a feedback configuration and the learning law updates the feedforward input from the plant input of the previous trial. A sufficient condition which guarantees the convergence of the learning is given. It is shown that the convergence condition of the learning control in the feedback configuration does not change from the condition in an open-loop configuration. But the learning speed can be improved greatly in the feedback configuration. Employing an input saturator which limits the control input within a reasonable bound, the class of nonlinear systems to which the proposed learning scheme can be applied is extended. The proposed learning control process is applied to the tracking control of a two link robot manipulator, and good tracking performance is obtained in the simulation.

Sliding mode-like fuzzy logic control with self-tuning the dead zone parameters

In this paper, a fuzzy logic controller (FLC) is designed based on the similarity between the FLC and the sliding mode control. The proposed scheme has advantages that it permits one to use more formalized, engineering type of knowledge to construct the FLC, and it provides the sliding-like FLC with fast self-tuning the dead zone parameters (boundary layer thickness) under parameter variations of the controlled system. Simulation examples using the proposed method for a rotary inverted pendulum are performed to show the properties of the developed FLC.

Iterative learning control for discrete-time nonlinear systems

An iterative learning control method is proposed for a class of nonlinear discrete-time systems. The output of a system is shown to converge to a desired output for a finite time interval by using the proposed learning method under a certain condition. The proposed learning control method is applied to the tracking control of a two-link robot manipulator and the effectiveness of the learning is observed in the simulation

JPEG Quantization Table Design for Face Images and Its Application to Face Recognition

This paper proposes a new codec design method based on JPEG for face images and presents its application to face recognition. Quantization table is designed using the R-D optimization for the Yale face database. In order to use in the embedded systems, fast codec design is also considered. The proposed codec achieves better compression rates than JPEG codec for face images. In face recognition experiments using the linear discriminant analysis (LDA), the proposed codec shows better performance than JPEG codec.

Implementation of a ZigBee-based high performance sensor node for the robot environment platform

In this paper, a ZigBee-based wireless sensor network is configured for the robot to effectively communicate with the environment platform where each sensor node is implemented using a high performance microcontroller. The localization and the navigation functions are also required for the robot and the functions are executed with various types of sensor information. A new type of ZigBee stack is developed using the RUM(Router Under MAC) of the Atmel Corp. and it is applied to 32-bit ARM core microcontroller for the high performance sensor data manipulation and transmission. It is verified by experiments that the wireless sensor network consisting of developed high performance sensor nodes can be effectively used for the robot environment platform.

Design of a Repetitive Control System for a Piezoelectric Actuator Based on the Inverse Hysteresis Model

In this paper, first, we formulate the mathematical modeling of a piezoelectric actuator which is characterized by the hysteresis behavior. Second, we propose a controller design method for the PZT actuator which is subject to repetitive tasks. A linearization method using the inverse hysteresis model is considered and a repetitive controller with PI controllers is designed to improve the tracking performance. For a practical piezoelectric actuator, the polynomials in the nonlinear hysteresis modeling are found and it is shown by simulations that high precision tracking control can be performed by the proposed control system when the reference input is repetitive.

Power distribution control law for FCHEV - a fuzzy logic-based approach

In this paper, the power distribution control method for the fuel cell hybrid electric vehicle (FCHEV) is proposed using the fuzzy logic-based algorithm. The mathematical models of subsystems of a FCHEV are formulated and coded using the Matlab/Simulink software. To show the validity and the performance of the proposed control algorithm, it is applied to a vehicle for a given desired drive cycle. It is shown by simulations that the fuel consumption is reduced compared with the static power control while the battery SOC is maintained at the desired level.

Design of a robust thickness controller for a single-stand cold rolling mill

We derive a mathematical model of a single-stand cold rolling mill and design control systems to improve the thickness precision while maintaining prescribed tension for the strip. On the basis of a linearized model of the rolling mill system, we propose a thickness controller using an internal model control (IMC) structure which effectively rejects periodic disturbances. We also discuss how the so-called BISRA AGC method can be combined with the proposed thickness controller in the presence of modeling error. It is illustrated by simulations that the proposed thickness controller yields better performance than existing methods when a periodic thickness disturbance exists, and that it is robust to the uncertainty of the mill modulus.

Development of a Controller Area Network Interface Unit and Its Application to a Fuel Cell Hybrid Electric Vehicle

In this paper, a CAN-based network interface unit is presented and it is applied to an experimental set-up for studying the timing analysis for the power train control of a fuel cell hybrid electric vehicle. Next generation vehicles like fuel cell electric vehicles usually require a lot of communication data between subsystems or ECUs to improve the fuel economy and the advanced safety. Unexpected transmission delay on a data bus may be a cause for an unstable operation of a vehicle which may also yield a serious result and thus, a simple method for varying controller sampling period is proposed based on holistic scheduling method. It is illustrated by applying the presented interface unit to the simple experimental set-up of a fuel cell hybrid electric vehicle that the transmission delay problem of a lower priority data, which results from the activation of a higher priority task, can be resolved

A comparative study of fuzzy logic-based control strategies for a parallel mild Hybrid Electric Vehicle

In this paper, power distribution control strategies are applied to a mid-size parallel mild Hybrid Electric Vehicle (HEV) and the control performances are compared. The structure and the operation principle of a HEV are introduced, and it is shown that a conventional fuzzy logic-based power control strategy can be modified for fuel consumption optimization. Through simulation results, the fuel-optimized fuzzy logic-based power control method is shown to give better control performance than other methods especially for the urban driving conditions.