• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.60 no.2
• /
• pp.293-300
• /
• 2011

A number of techniques have been developed for estimation of speed or position in motor drives. The accuracy of these techniques is affected by the variation of motor parameters such as the stator resistance, stator inductance or torque constant. This paper is proposed a neural network based estimator for torque and stator resistance and adaptive fuzzy learning contrroller(AFLC) for speed control in IPMSM Drives. AFLC is chaged fuzzy rule base by rule base modifier for robust control of IPMSM. The neural weights are initially chosen randomly and a model reference algorithm adjusts those weights to give the optimum estimations. The neural network estimator is able to track the varying parameters quite accurately at different speeds with consistent performance. The neural network parameter estimator has been applied to slot and flux linkage torque ripple minimization of the IPMSM. The validity of the proposed parameter estimator and AFLC is confirmed by comparing to conventional algorithm.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.135-135
• /
• 2000

In this Paper. the DSP implementation of induction motor drive is Presented on the viewpoint of the design and experiment. The speed estimation of control system for induction motor drive is designed on the base of neural network speed estimator. This neural network speed estimator is experimentally applied to the induction motor system. This system Provides the satisfactory results.

• Journal of Institute of Control, Robotics and Systems
• /
• v.19 no.12
• /
• pp.1132-1137
• /
• 2013

In swarm robot systems, it is vital to maintain network connectivity to ensure cooperative behavior between robots. This paper deals with the behavior control algorithm of the swarm robots for maintaining network connectivity. To do this, we divide swarm robots into search-robots, base-robots, and relay-robots. Using these robots, we propose behavior control algorithm to maintain network connectivity. The behavior control algorithms to maintain network connectivity are proposed for the local path planning using virtual force and global path planning using the Delaunay triangulation, respectively. Finally, we demonstrate the effectiveness and applicability of the proposed method through some simulations.

• Journal of the Korean Society of Industry Convergence
• /
• v.19 no.1
• /
• pp.1-9
• /
• 2016

In this paper, we propose a new learning control scheme for various walk motion control of biped robot with same learning-base by neural network. We show that learning control algorithm based on the neural network is significantly more attractive intelligent controller design than previous traditional forms of control systems. A multi layer back propagation neural network identification is simulated to obtain a dynamic model of biped robot. Once the neural network has learned, the other neural network control is designed for various trajectory tracking control with same learning-base. The biped robots have been received increased attention due to several properties such as its human like mobility and the high-order dynamic equation. These properties enable the biped robots to perform the dangerous works instead of human beings. Thus, the stable walking control of the biped robots is a fundamentally hot issue and has been studied by many researchers. However, legged locomotion, it is difficult to control the biped robots. Besides, unlike the robot manipulator, the biped robot has an uncontrollable degree of freedom playing a dominant role for the stability of their locomotion in the biped robot dynamics. From the simulation and experiments the reliability of iterative learning control was illustrated.

• Proceedings of the IEEK Conference
• /
• 1998.06a
• /
• pp.897-900
• /
• 1998

Through fuzzy logic controller is very useful to many areas, it is difficult to build up the rule-base by experience and trial-error. So, effective self-tuning fuzzy controller for the position control of ball and beam is designed. In this paper, we developed the neural network control system with fuzzy-neuron which conducts the adjustment process for the parameters to satisfy have nonlinear property of the ball and beam system. The proposed algorithm is based on a fuzzy logic control system using a neural network learinign algorithm which is a back-propagation algorithm. This system learn membership functions with input variables. The purpose of the design is to control the position of the ball along the track by manipulating the angualr position of the serve. As a result, it is concluded that the neural network control system with fuzzy-neuron is more effective than the conventional fuzzy system.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.18 no.3
• /
• pp.315-320
• /
• 2009

The purpose of this study is to predict the roundness of Numerical Control Machining so that helps the operator to choose the right machining conditions to produce a product within the given error limits. Learning of neural network is Backpropagation theory. From this study, the base was set to setup the database to produce precisely machined product by predicting the rate of error in the fabrication facility which does not have the environment to analyze it.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.161.4-161
• /
• 2001

This paper presents adaptive control of robot manipulator using neuro-fuzzy controller Fuzzy logic is control incorrect system without correct mathematical modeling. And, neural network has learning ability, error interpolation ability of information distributed data processing, robustness for distortion and adaptive ability. To reduce the number of fuzzy rules of the FLS(fuzzy logic system), we consider the properties of robot dynamic. In fuzzy logic, speciality and optimization of rule-base creation using learning ability of neural network. This paper presents control of robot manipulator using neuro-fuzzy controller. In proposed controller, fuzzy input is trajectory following error and trajectory following error differential ...

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.27 no.4C
• /
• pp.353-364
• /
• 2002

To prevent the performance degradation of TCP due to packet loss in the smooth handoff by the route optimization extension of Mobile If protocol, a buffering of packets at a base station is needed. A buffering of packets at a base station recovers the packets dropped during the handoff by forwarding the buffered packets at the old base station to the mobile user. But, when the mobile user moves to a new foreign network which is connected to a congested router, the buffered packets forwarded by the old base station are dropped and the link utilization performance degraded due to increased congestion by the forwarded packets. In this paper, when the mobile user moves to a new foreign network which is connected to a congested router, Ive propose a packet forwarding control scheme required far the old base station to improve TCP performance in mobile networks. The old base station forwards or discards the buffered packets during handoff by proposed packet forwarding control scheme based on congestion states of RED(Random Early Detection) at the congested router. Simulation results slow that link utilization performance can be improved by applying proposed packet forwarding control scheme.

• Proceedings of the KIEE Conference
• /
• 2002.07d
• /
• pp.2344-2346
• /
• 2002

A vacuum control system has been developed for using Ethernet Multi Serial Device Severs (EMSDS) for the Pohang Accelerator Laboratory (PAL) storage ring. There are 124 vacuum ion pumps at the storage ring. It was a very important problem to solve the problem how to control such a big number of vacuum pumps distributed around the ring. After discussions, we decided to develop a serial to ethernet interrace device sever that will be mounted in the control system rack. It has a 32-bits microprocessor embedded Linux, 12 ports RS485 (or RS232) slave interface. one channel 10/100BaseTx ethernet host port, one channel UART host port, and 16 Mbytes large memory buffer. These vacuum pumps are connected to Ion-Pump serial controllers, which chop the AC current so as to control the current in the pumps. The EMSDS connect either 100BaseTx or 10BaseT ethernet networks to asynchronous serial ports for communication with serial device. It can simultaneously control up to 12 ion-pump serial controllers. 12 EMSDS are connected to a personal computer (PC) through the network. The PC can automatically control the EMSDS by sending a set of commands through the TCP/IP network. Upon receiving a command from a PC running under Windows2000 through the network, the EMSDS communicate through the stave serial interrace ports to ion-pump controller. We added some software components on the top of EPICS (Experimental Physics and Industrial Control System) toolkit.

• The Transactions of the Korea Information Processing Society
• /
• v.3 no.5
• /
• pp.1253-1261
• /
• 1996

The base station (BS) of CDMA mobile system (CMS) provides mobile call services by controlling call processing functions. The call Processing part of the BS is divided into two components; the base station transceiver subsystem (BTS) and the base station controller (BSC). In this paper, we present the call capacity estimation of the BS about control signals and traffic data of calls by the simulation, and find the bottleneck points and problems which may occur in the BS. In order to estimate the call capacity, first we extract the major parameters for the modeling the BS. Second, we suggest the simulation model for the BS. Third, we estimate the simulation results by finding major objective factors such that the call blocking probability, the utilization ratio and the delay time in the traffic channel elements (TCEs), the BTS interconnection network (BIN)-COMA interconnection network (CIN) trunks, the transcoding channels and the CIN packet router.