• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1382-1385
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• 1993

In order to improve productivity, an intelligent control system is presented in the pater. In this intelligent control system, a feedforward neural network and a fuzzy feedback mechanism are adopted to achieve a constant milling force with an adjustable feedrate under a variety of cutting conditions in milling operations.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.2
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• pp.106-115
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• 2013

LED lighting control system using unidirectional DMX512 (digital multiplex with 512 pieces of information)) protocol has been the most popular. Nowadays, the user's consumption has been upgrading to the more intelligent system but the upgrading process does not affect the existing infrastructure. There were many researches use the additional communication for the feedback communication way such as WiFi, Controller Area Network (CAN), Power Line Communication (PLC), etc but all researches had inherent disadvantages that created the independent feedback with the existing DMX512 system. Our paper represents the novel method that uses the remote device management (RDM) protocol to associate the additional feedback with existent DMX512 infrastructure in the one system. The data in DMX512 frame sending to the DMX512 client is split and repacked to become the RDM packet. This RDM packet is transferred to the RDM monitor console and the response RDM packet is converted to the DMX512 frame for control DMX512 client devices. This is the closed loop control model which uses the bidirectional convertibility between RDM packet and DMX512 frame. The proposed method not only upgrades the feedback control function for the old DMX512 system without changing the existent infrastructure, but also solves compatible problems between new RDM devices and old DMX512 devices and gives the low cost solution for extending DMX512 universe.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1802-1807
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• 2005

Tangible interface can be understood as a newly defined concept, which can provide an effective and seamless interaction between the human as a subjective existence and the cyberspace as an objective existence. Tactile sensation is essential for many exploration and manipulation tasks in the tangible space. In this paper, we suggest the design of an integrated tactile sensor-display system that provides both of sensing and feedback with kinesthetic force, pressure distribution, vibration and slip/stretch. A new tactile sensor with PDVF strips and display system with bimorph actuators has been developed and integrated by developed signal processing algorithm. In the scenario of haptic navigation in the tangible space, tactile feedback system is successfully experimented.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.5
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• pp.120-129
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• 2001

As many sensors and actuators are used in many automated systems, various industrial networks are adopted for real-time distributed control. In order to take advantages of the networking, however, the network implementation should be carefully designed to satisfy real-time requirements considering network delays. This paper presents the implementation of a remote feedback control system via Profibus-DP net work for real-time distributed control More specifically, the effect of the network delay on the control performance evaluated on Profibus-DP testbed. Also, the traditional PID gain tuning methods are used to demonstrate the feasibility of the remote feedback control.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.3
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• pp.260-269
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• 2000

The fuzzy and state-feedback control systems have been applied in various areas from non-linear to linear systems. A Fuzzy controller is endowed with control rules and membership function that are constructed on the knowledge of expert, as like intuition and experience. but It is very difficult to obtain the exact values which are the membership function and consequent parameters. though apply back-propagation algorithm to the system, the convergence time a much. Besides, the state-feedback system is most widely used in industry due to its simple control structure and easily able to design the controller. but it is weak in complex system of higher degree and non-linear. In this paper presents the design of a fuzzy switching mode, it these two controllers work at different operation conditions, the advantages of both controller can be retained and the disadvantages can be removed. Between the Fuzzy and the State-feedback controlles, the good outputs are selected by the switching mode. Moreover it is powerful in complex system of higher degree and non-linear. In these sense compared with the state-feedback controller, the performance of the proposed controller was improvedin the section of linearization.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.7
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• pp.977-980
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• 2007

Observer design for the nonlinear systems is known to be difficult in general. This paper suggests a feedback GA-based model predictive observer for the observable systems. Feedback concept makes on-line design possible for the cases including observer design, where GA is implemented repeatedly every time instant. The effectiveness of our observer is shown by simulation.

• Proceedings of the Korea Society of Design Studies Conference
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• 2005.10a
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• pp.26-27
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• 2005

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.6
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• pp.494-499
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• 2013

Based on the state-feedback adaptive neuro-control algorithm for a SISO nonaffine pure-feedback nonlinear system proposed in [15], an output-feedback controller is proposed in this paper. The output-feedback adaptive neural-net controller for the considered nonlinear system has not been previously proposed in any other literatures yet. The proposed output-feedback controller inherits all the advantages of [15] such that it does not adopt backstepping and this results in relatively simple control and adapting laws. Only one neural network is required for the proposed adaptive controller. The proposed neural-net control scheme expands the applicable class of nonlinear systems.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.5
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• pp.401-408
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• 2000

In this paper, we proposed a fuzzy controller that founded by the general feedback control with the new adjustment method when it's tuning. The general feedback controller is operated that supply to the plant making the control input multiplying the appropriate gain of controller on the error between the output of the plant and the reference, But proposed feedback fuzzy controller consist of three loops. The inner loop consists of plant and an ordinary feedback controller. The fuzzy inference of controller performed by the outer loops, which is composed of a fuzzy modeling and inference. We can observe that the output of control system converges toward the reference. Also, the behaviour of feedback fuzzy system is converged from the transient. That is, we verified that designed fuzzy controllers was adapted effectively through the experiments in the hydraulic motor system using floating point DSP processor.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1009-1012
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• 1993

An association memory, solving an optimization problem, a Boltzmann machine scheme learning and a back propagation learning in our chaos neuron models are reviewed and some new results are presented. In each model its microscopicrule (a parameter of a chaos system in a neuron) is subject to its macroscopic state. This feedback and chaos dynamics are essential mechanisms of our model and their roles are briefly discussed.