Kwon-Soon Lee

Anti-sway position control of an automated transfer crane based on neural network predictive PID controller

In this paper, we develop an anti-sway control in proposed techniques for an ATC system The developed algorithm is to build the optimal path of container motion and to calculate an anti-collision path for collision avoidance in its movement to the finial coordinate Moreover, in order to show the effectiveness in this research, we compared NNP PID controller to be tuning parameters of controller using NN with 2 DOF PID controller The simulation and experimental results show that the proposed control scheme guarantees performances, trolley position, sway angle and settling time in NNP PID controller than other controller As the results in this paper, the application of NNP PID controller is analyzed to have robustness about disturbance which is wind of fixed pattern in the yard. Accordingly, the proposed algorithm in this study can be readily used for industrial applications

Design of Time-varying Stochastic Process with Dynamic Bayesian Networks

We present a dynamic Bayesian network (DBN) model of a generalized class of nonstationary birth-death processes. The model includes birth and death rate parameters that are randomly selected from a known discrete set of values. We present an on-line algorithm to obtain optimal estimates of the parameters. We provide a simulation of real-time characterization of load traffic estimation using our DBN approach.

A study for AGV steering control and identification using vision system

The authors experimented on an AGV driving test with a color CCD camera. This paper can be divided into two parts. One is the image processing part to measure the condition of the guideline and AGV. The other obtains the reference steering angle through using the image processing parts. First, the two dimensional information of image derived from the vision sensor is interpreted to 3 dimension information by the angle and position of the CCD camera. Through these processes, the AGV knows its driving conditions. Using this information, the AGV calculates the reference steering angle changed by its speed. In the case of low speed, it focuses on the left/right error values of the guideline. As the speed of the AGV increases, it focuses on the slope of the guideline. Lastly, the authors model the above descriptions to the type of PID controller and regulate the coefficient value of the AGV speed.

A study on gantry crane control using neural network two degree of PID controller

During the operation of a crane system in the container yard, it is necessary to control the crane trolley position so that the swing of the hanging container is minimized. An automatic control system with high speed and rapid transportation is required. Therefore, we designed a controller to control the crane system with disturbances and weight change. In this paper, we present the neural network two degrees of freedom PID controller to control the swing motion and trolley position. Then we executed the computer simulation to verify the performance of the proposed controller and compared the performance of the neural network PID controller with our proposed controller in terms of the rope swing and the precision of position control. Computer simulation results show that the proposed controller has better performances than neural network PID with disturbances.

Nonlinear Adaptive Control and Stability Analysis for Improving Transient Response of Photovoltaic Converter Systems

In photovoltaic(PV) generator systems, DC-DC converters are significantly considered for control system performance in power quality point of view. This paper presents a novel adaptive control method for DC-DC converters applied in PV generator systems. First, we derive a state-space average model of the converter system and then propose a reset control methodology to enhance transient response performance for time-varying PV systems. For estimating parameters of a reset control, a gradient descent optimization is utilized and an adjustment rule of them are derived respectively. An objective of the optimization is that characteristic equation of an augmented system model which is formed with an converter system model and an reset control is to trace a predefined polynomial given as a reference characteristic model. Next, we accomplish stability analysis by means of a well-known Lyapunov theory for nonlinear converter systems including time-varying voltage excitation from a PV generator. Numerical simulation demonstrates reliability of our control methodology and its superiority by comparison to a traditional control strategy.

Real-time Detection Technique of the Target in a Berth for Automatic Ship Berthing

In this paper vector code correlation(VCC) method and an algorithm to promote the image-processing performance in building an effective measurement system using cameras are described far automatically berthing and controlling the ship equipped with side-thrusters. In order to realize automatic ship berthing, it is indispensable that the berthing assistant system on the ship should continuously trace a target in the berth to measure the distance to the target and the ship attitude, such that we can make the ship move to the specified location. The considered system is made up of 4 apparatuses compounded from a CCD camera, a camera direction controller, a popular PC with a built-in image processing board and a signal conversion unit connected to parallel port of the PC. The object of this paper is to reduce the image-processing time so that the berthing system is able to ensure the safety schedule against risks during approaching to the berth. It could be achieved by composing the vector code image to utilize the gradient of an approximated plane found with the brightness of pixels forming a certain region in an image and verifying the effectiveness on a commonly used PC. From experimental results, it is clear that the proposed method can be applied to the measurement system for automatic ship berthing and has the image-processing time of fourfold as compared with the typical template matching method.

An implementation of HIA (humoral immune algorithm) PID controller using neural network identifier

In this paper, an adaptive mechanism based on HIA (humoral immune algorithm) is designed. When the HIA is applied to the PID controller, there exists the case that the plant is damaged by the abrupt change of PID parameters since the parameters are adjusted almost randomly. To solve this problem, a neural network is used to model the plant and the parameter tuning of the system is performed by the humoral immune algorithm. After the PID parameters are determined through this off-line manner, these gains are then applied to the plant for the online control using immune adaptive algorithm. Moreover, even though the neural network model may not be accurate enough initially, the weighting parameters are adjusted to be accurate through the online fine tuning. The experiment for the control of the AGV system is performed. The results show that the proposed controller has better performances than other conventional controllers.

Online Dynamic Modeling of Ubiquitous Sensor based Embedded Robot Systems using Kalman Filter Algorithm

This paper presents Kalman filter based system modeling algorithm for autonomous robot systems. State of the robot system is measured using embedded sensor systems and then carried to a host computer via ubiquitous sensor network (USN). We settle a linear state-space motion equation for unknown robot system dynamics and modify a popular Kalman filter algorithm in deriving suitable parameter estimation mechanism. To represent time-delay nature due to network media in system modeling, we construct an augmented state-space model which is mainly composed of original state and estimated parameter vectors. We conduct real-time experiment to test our proposed estimation algorithm where speed state of the constructed robot is used as system observation.

A Study on the Tracking Control of a Transfer Crane : Observer Design and Experimental Study

The most important thing in the container terminal is to handle the cargo effectively in the limited time. To achieve this object, many strategies have been introduced and applied to. If we consider the automated container terminal, it is necessary that the cargo handling equipments are equipped with more intelligent control systems. From the middle of the 1990`s, an automated rail-mounted gantry crane(RMGC) and rubber-tired gantry crane(RTG) have been developed and widely used to handle containers in the yards. Recently, in these cranes, the many equipments like CCD cameras and sensors are mounted to cope with the automated terminal environment. In this paper, we try to support the development of more intelligent automated cranes which make the cargo handling be performed effectively in the yards. For this plant, the modelling, tracking control, anti-sway system design, skew motion suppressing and complicated motion control and suppressing problems must be considered. In this paper, the system modelling and a tracking control approach are discussed. And, we design the tracking control system incorporating an observer based on the 2DOF servosystem design approach to obtain the informations of the states. The experiment results show the usefulness of the designed control system.

Position accuracy improvement of linear motor container transfer system using DR-FNNs

We introduced a multi-step prediction control of linear motor-based container transport system for high precision using dynamically constructed recurrent fuzzy neural networks (DR-FNN). Linear motor-based container transport system (LMCTS) is the horizontal transfer system for yard automation, which is proposed to take the place of automated guided vehicle in the maritime container terminal. LMCTS is the system that can suddenly changed its model by loading and unloading container. The proposed control system is using two DR-FNN for multi-step prediction. Consequently, the system has the ability to adapt for a huge rolling friction, cogging force ripple, and sudden changes by loading and unloading.