• International Journal of Automotive Technology
• /
• v.7 no.6
• /
• pp.687-695
• /
• 2006

This paper presents a network-based traction control system(TCS), where several electric control units(ECUs) are connected by a controller area network(CAN) communication system. The control system consists of four ECUs: the electric throttle controller, the transmission controller, the engine controller and the traction controller. In order to validate the traction control algorithm of the network-based TCS and evaluate its performance, a Hardware-In-the-Loop Simulation(HILS) environment was developed. Herein we propose a new concept of the HILS environment called the network-based HILS(Net-HILS) for the development and validation of network-based control systems which include smart sensors or actuators. In this study, we report that we have designed a network-based TCS, validated its algorithm and evaluated its performance using Net-HILS.

• Journal of Information Processing Systems
• /
• v.18 no.6
• /
• pp.755-762
• /
• 2022

The existing electrical engineering design method and the dynamic objective function in the application process of automatic control system fail to meet the unbounded condition, which affects the control tracking accuracy. In order to improve the tracking control accuracy, this paper studies the electrical engineering design method based on neural network and the application of automatic control system. This paper analyzes the structure and working mechanism of electrical engineering automation control system by an automation control model with main control objectives. Following the analysis, an optimal solution of controllability design and fault-tolerant control is figured out. The automatic control power coefficient is distributed based on an ideal control effect of system. According to the distribution results, an automatic control algorithm is based on neural network for accurate control. The experimental results show that the electrical automation control method based on neural network can significantly reduce the control following error to 3.62%, improve the accuracy of the electrical automation tracking control, thus meeting the actual production needs of electrical engineering automation control system.

• Proceedings of the KIEE Conference
• /
• 2007.04a
• /
• pp.409-412
• /
• 2007

Demand for the technology for access to device control network in industry and for access to building automation system via internet is on the increase. In such technology integration of a device control network with a data network such as internet and organizing wide-ranging DCS(distributed control system) is needed, and it can be realized in the framework of VDN(virtual device network). Specifications for device control network and data network are quite different because of the differences in application. So a router that translates the communication protocol between device control network and data network, and efficiently transmits information to destination is needed for implementation of the VDN(virtual device network). This paper proposes the concept of NCS(networked control system) based on VDN(virtual device network) and suggests the routing algorithm that uses embedded system.

• Journal of Institute of Control, Robotics and Systems
• /
• v.9 no.11
• /
• pp.963-968
• /
• 2003

A feedback control implementation for a high speed train pressurization system is proposed based on CAN (Controller Area Network). Firstly, system model including network latencies by CAN arbitration mechanisms is proposed, and an analytical compensation method of control parameters based on the system model is proposed for the network latencies. For the practical implementation of the control, global synchronization is adopted for controller to measure network latencies and to utilize them for the compensation of the control parameters. Simulation results are shown with practical tunnel data response. The proposed method is evaluated to be the most effective for the system through the control performances comparing among a controller not considering network latencies, other two off-line compensation methods, and the proposed method.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.549-549
• /
• 2000

In the previous work, we dealt with a traffic analysis of network-based control system and its architecture using the CAN protocol. It is difficult to determine an optimal network architecture for a specific system. In this paper, we propose the architecture of network-based control system applicable to a specific AGV system with manipulator arms. We define the fixed number of periodic messages to be occurred in this system. In the proposed system architecture, we analyse its traffic for the real-time communication of all messages, determine the optimal sampling period of an analog sensor to be satisfied with the required specification and the number of possible sensors to be added through simulation.

• Journal of Institute of Control, Robotics and Systems
• /
• v.18 no.5
• /
• pp.433-438
• /
• 2012

In this paper, a operation network system equipped with onboard wireless communication systems and ground-based mission control systems is proposed for swarm flight of small UAVs. This operating system can be divided into two networks, UAV communication network and ground control system. The UAV communication network is intend to exchange the informations of navigation, mission and flight status with minimum time delay. The ground control system consisted of mission control systems and UDP network. Proposed operation network system can make a swarm flight of various UAVs, execute complex missions decentralizing mission to several UAVs and cooperte several missions. Finally, PILS environments are developed based on the total operating system.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• v.1
• /
• pp.301-306
• /
• 2006

The important field of research on ship operation is related to the high efficiency of transportation, the convenience of maneuvering ships and the safety of navigation. As a way of practical application for a smart ship based on network system, this paper proposes the intelligent support system for ship steering control system based on TCP/IP and desires to testify the validity of the proposal by applying the fuzzy control model to the steering control system. As the specific study methods, the fuzzy inference was adopted to build the maneuvering models of steersman, and then the network system was implemented using the TCP/IP socket-based programming. Lastly, the miniature model steering control system combined with LIBL (Linguistic Instruction-based Learning) was designed to testify for its effectiveness.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.14 no.5
• /
• pp.47-57
• /
• 2006

This paper presents a network-based traction control system(TCS), where several electric control units (ECUs) are connected by a controller area network(CAN) communication system. The control system consists of four ECUs: the electricthrottle controller, the transmission controller, the engine controller and the traction controller. In order to validate the traction control algorithm of the network-based TCS and evaluate its performance, a Hardware-In-the-Loop Simulation(HILS) environment was developed. Herein we propose a new concept of the HILS environment called the network-based HILS(Net-HILS) for the development and validation of network-based control systems which include smart sensors or actuators. In this study, we report that we have designed a network-based TCS, validated its algorithm and evaluated its performance using Net-HILS.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.48 no.7
• /
• pp.815-823
• /
• 1999

This study considers an implementation of artificial neural networks to the receding horizon optimal control and is applications to power systems. The Generalized Backpropagation-Through-Time (GBTT) algorithm is presented to deal with a quadratic cost function defined in a finite-time horizon. A decentralized approach is used to control the complex global system with simpler local controllers that need only local information. A Neural network based Receding horizon Optimal Control (NROC) 1aw is derived for the local nonlinear systems. The proposed NROC scheme is implemented with two artificial neural networks, Identification Neural Network (IDNN) and Optimal Control Neural Network (OCNN). The proposed NROC is applied to a power system to improve the damping of the low-frequency oscillation. The simulation results show that the NROC based power system stabilizer performs well with good damping for different loading conditions and fault types.

• Journal of Institute of Control, Robotics and Systems
• /
• v.13 no.5
• /
• pp.414-421
• /
• 2007

This paper presents a engine/brake integrated VDC(Vehicle Dynamic Control) system using neural network algorithm methods for wheel slip and yaw rate control. For stable performance of vehicle, not only is the lateral motion control(wheel slip control) important but the yaw motion control of the vehicle is crucial. The proposed NNPI(Neural Network Proportional-Integral) controller operates at throttle angle to improve the performance of wheel slip. Also, the suggested NNPID controller performs at brake system to improve steering performance. The proposed controller consists of multi-hidden layer neural network structure and PID control strategy for self-learning of gain scheduling. Computer Simulation have been performed to verify the proposed neural network based control scheme of 17 dof vehicle dynamic model which is implemented in MATLAB Simulink.