• Transactions on Control, Automation and Systems Engineering
• /
• v.2 no.2
• /
• pp.136-139
• /
• 2000

A neural controller for process control is proposed that combines a conventional multi-loop PID controller with a neural network. The concept of target signal based on feedback error is used for on-line learning of the neural network. This controller is applied to distillation column control to illustrate its effectiveness. The result shows that the proposed neural controller can cope well with disturbance, strong interactions, time delays without any prior knowledge of the process.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2000.10a
• /
• pp.135-139
• /
• 2000

This research proposes a nonlinear sliding mode control. The sliding mode control is designed according to Lyapunov function. The equivalent control term is estimated by neural network. To estimate the unknown part in the control law in on-line fashion, A recurrent neural network is given as on-line estimator. The stability of the control system is guaranteed owing to the on-line learning ability of the recurrent neural network. It is certificated through simulation results to be applied to nonlinear system that the function approximation and the proposed control scheme is very effective.

• Journal of the Korean Society for Precision Engineering
• /
• v.15 no.3
• /
• pp.50-60
• /
• 1998

This paper is concerned with the design of two residual control charts for real-time monitoring of the continuous flow processes. Two different control charts are designed under the situation that observations are correlated each other. Kalman-Filter based model estimation is employed when the process model is known. A black-box approach, based on Back-Propagation Neural Network, is also applied for the design of control chart when there is no prior information of process model. Performance of the designed control charts and traditional control charts is evaluated. Average run length(ARL) is adopted as a criterion for comparison. Experimental results show that the designed control chart using the Neural Network's modeling has shorter ARL than that of the other control charts when process mean is shifted. This means that the designed control chart detects the out-of-control state of the process faster than the others. The designed control chart using the Kalman-Filter based model estimation also has better performance than traditional control chart when process is out-of-control state.

• 한국정보통신설비학회:학술대회논문집
• /
• 2009.08a
• /
• pp.219-220
• /
• 2009

Many surveillance cameras used in security system are controlled with RS-485 communication protocol. In this situation, if RS-485 connection can be replaced with wireless connection using sensor network technology, an installation will become ease because of no wired connection and also a deployment of cameras will become free. This paper explains about the design of wireless sensor node and the necessary implementation for an operation, which can be replacing RS-485 connection for the development of CCTV control system based on wireless sensor network. The hardware platform of sensor node was designed based on MicaZ and the software was developed based on TinyOS. To control surveillance cameras deployed on wide area, the supporting of multi-hop also was implemented. With the result of experiment deploying on real environment, it was revealed that the controller could control cameras quickly with wireless.

• Journal of the Korean Society of Industry Convergence
• /
• v.24 no.3
• /
• pp.351-361
• /
• 2021

This study proposes an intelligent control of manufacturing robot with dual arm based on neural network for smart factory implementation. In the control method of robot system, the perspectron structure of single layer based on neural network is useful for simple computation. However, the limitations of computation are emerging in areas that require complex computations. To overcome limitation of complex parameters computation a new intelligent control technology is proposed in this study. The performance is illustrated by simulation and experiments for manufacturing robot dual arm robot with eight axes.

• 한국정보통신설비학회:학술대회논문집
• /
• 2005.08a
• /
• pp.290-296
• /
• 2005

In this paper, we describe ubiquitous environments and the trend of convergence that is an evolution path of current telecommunication, and show the concept of broadband convergence network, service feature and evolution path. In order to converge wire and wireless communication, telecommunication and broadcasting, voice and data efficiently, broadband convergence network divides a network into service layer, control layer, transport layer, ubiquitous access and terminal layer. Broadband convergence network will be a network that can provide and control broadband multimedia services with QoS and securityof different and customized level. Then we depict characteristics and types of broadband multimedia service, and describe the characteristic of broadband convergence network. Finally, we show ubiquitous network based on the broadband convergence network to provide ubiquitous service which is a future telecommunication service. We also describe requirements of ubiquitous network such as an intelligent and context based platform, convergence terminals, ubiquitous computing devices, etc., and give various emerging technologies and those applications.

• Proceedings of the KIEE Conference
• /
• 2002.07d
• /
• pp.2445-2447
• /
• 2002

In this paper, CAN-based feedback control system is proposed for the pressurization system of korean high-speed train. The control performance of the system is evaluated. According to the requirement of the pressurization system A process model considering network delay and an adaptive PID control method based on the process model are proposed here. And it is shown that the proposed adaptive PID control method considering the network delay has on adequate feature compared to some other existing methods consequently it can be considered to be applied the pressurization system of korean high-speed train.

• Journal of Institute of Control, Robotics and Systems
• /
• v.16 no.9
• /
• pp.898-904
• /
• 2010

Unmanned autonomous forklifts have a great potential to enhance the productivity of material handling in various applications because these forklifts can pick up and deliver loads without an operator and any fixed guide. There are, however, many technical difficulties in developing such forklifts including localization, map building, sensor fusion, control and so on. Implementation, which is often neglected, is one of practical issues in developing such an autonomous device. This is because the system requires numerous sensors, actuators, and controllers that need to be connected with each other, and the number of connections grows very rapidly as the number of devices grows. Another requirement on the integration is that the system should allow changes in the system design so that modification and addition of system components can be accommodated without too much effort. This paper presents a network-based distributed approach where system components are connected to a shared CAN network, and control functions are divided into small tasks that are distributed over a number of microcontrollers with a limited computing capacity. This approach is successfully applied to develop an unmanned forklift.

• Journal of Information Processing Systems
• /
• v.5 no.2
• /
• pp.97-104
• /
• 2009

In this paper we propose a Differentiated Services Based Admission Control and Routing Algorithm for IPv6 (ACMRA). The basic DiffServ architecture lacks an admission control mechanism, the injection of more QoS sensitive traffic into the network can cause congestion at the core of the network. Our Differentiated Services Based Admission Control and Routing Algorithm for IPv6 combines the admission control phase with the route finding phase, and our routing protocol has been designed in a way to work alongside DiffServ based networks. The Differentiated Services Based Admission Control and Routing Algorithm for IPv6 constructs label switched paths in order to provide rigorous QoS provisioning. We have conducted extensive simulations to validate the effectiveness and efficiency of our proposed admission control and routing algorithm. Simulation Results show that the Differentiated Services Based Admission Control and Routing Algorithm for IPv6 provides an excellent packet delivery ratio, reduces the control packets' overhead, and makes use of the resources present on multiple paths to the destination network, while almost each admitted flow shows compliance with its Service Level Agreement.

• Smart Structures and Systems
• /
• v.11 no.3
• /
• pp.315-329
• /
• 2013

The construction of an experimental nonlinear structural model with little cost and unlimited repeatability for vibration control study represents a challenging task, especially for material nonlinearity. This paper reports the design, analysis and vibration control of a nonlinear structural experiment platform with adjustable hinges. In our approach, magnetorheological rotary brakes are substituted for the joints of a frame structure to simulate the nonlinear material behaviors of plastic hinges. For vibration control, a separate magnetorheological damper was employed to provide semi-active damping force to the nonlinear structure. A dynamic neural network was designed as a state observer to enable the feedback based semi-active vibration control. Based on the dynamic neural network observer, an adaptive fuzzy sliding mode based output control was developed for the magnetorheological damper to suppress the vibrations of the structure. The performance of the intelligent control algorithm was studied by subjecting the structure to shake table experiments. Experimental results show that the magnetorheological rotary brake can simulate the nonlinearity of the structural model with good repeatability. Moreover, different nonlinear behaviors can be achieved by controlling the input voltage of magnetorheological rotary damper. Different levels of nonlinearity in the vibration response of the structure can be achieved with the above adaptive fuzzy sliding mode control algorithm using a dynamic neural network observer.