• Proceedings of the KIEE Conference
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• 1994.11a
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• pp.165-168
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• 1994

The paper deals with the fuzzy PI control of a switched reluctance motor drive. Fuzzy algorithm based on linguistic rules describing the operator's control strategy is applied to speed control of the SRM. Simulation and experimental results show that performance of the furry PI controller is superior to that of conventional PI controller. In particular the robustness of the system is improved.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.1
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• pp.113-120
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• 1994

The dynamic characteristics of turning processes are complex, non-linear and time-varying. Consequently, the conventional techniques based on crisp mathematical model may not guarantee cutting force regulation. This paper presents a fuzzy controller which can regulate cutting force in turning process under varying cutting conditions. The fuzzy control rules are extablished from operator experience and expert knowledge about the process dynamics. Regulation which increases productivity and tool life is achieved by adjusting feedrate according to the variation of cutting conditions. The performance of the proposed controller is evaluated by cutting experiments in the converted conventional lathe. The results of experiments show that the proposed fuzzy controller has a good cutting force regulation capability in spite of the variation of cutting conditions.

• Journal of Advanced Marine Engineering and Technology
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• v.30 no.7
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• pp.791-799
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• 2006

The aim of this paper is to design an adaptive speed control system of a marine diesel engine by fusion of hard computing based proportional integral derivative (PID) control and soft computing based fuzzy control methods. The model of a marine diesel engine is considered as a typical non oscillatory second order system. When its model and the actual marine diesel engine ate not matched, it is hard to control the speed of the marine diesel engine. Therefore, this paper proposes two methods in order to obtain the speed control characteristics of a marine diesel engine. One is an efficient method to determine the PID control parameters of the nominal model of a marine diesel engine. Second is a reference adaptive speed control method that uses a fuzzy controller and derivative operator for tracking the nominal model of the marine diesel engine. It was found that the proposed PID parameters adjustment method is better than the Ziegler & Nichols' method, and that a model reference adaptive control is superior to using only PID controller. The improved control method proposed here, could be applied to other systems when a model of a system does not match the actual system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.524-526
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• 2021

As the video wall controller market is growing rapidly, issues that have not been addressed so far are raised. One of them is a phenomenon in which a black screen is displayed on a multi-screen. Black screen is displayed due to an error in the video being displayed in the video wall controller. Human intervention is inevitable to recognize and solve the black screen. However, it is impossible for the operator to monitor the multi-screen 24 hours a day. In this paper, we propose a model that detects the black screen being displayed on the video wall controller. We propose a CNN based architecture to detect a black screen.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.265-271
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• 1992

It is the purpose of this paper to present a dialogical designing method for control system using a rough grasp of the unknown process property. We deal with a single-input single-output feedback control system with a fuzzy controller. The process property is roughly estimated by the step response, and the fuzzy controller is interactively modified according to the operator's requests. The modifying rules mainly derived from computer simulation are useful for almost every process, such as an unstable process and a non-minimum phase process. The fuzzy controller is tuned by taking notice of four characteristics of the step response: (1) rising time, (2) overshoot, (3) amplitude and (4) period of vibration. The tuning position of the controller is fourfold: (1) antecedent gain factor GE or GCE, (2) consequent gain factor GDU, (3) arrangement of the antecedent fuzzy labels and (4) arrangement of the control rules. The rules give an instance to the respective items of the controller in an effective order. The modified fuzzy PI controller realizes a good response of a stable process. However, because the GDU tuning becomes difficult for the unstable process, it is necessary to evaluate the stability of the process from the initial step response. The fuzzy PI controller is applied to the process whose initial step response converges with GDU tuning. The fuzzy PI controller with modified sampling time is applied to the process whose step response converges under the repeated application of the GDU tuning. The fuzzy PD controller is applied to the process whose step response never converges by the GDU tuning.

• Design & Manufacturing
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• v.11 no.3
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• pp.41-45
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• 2017

Drones can be manipulated in a variety of ways. One of the most common controller is joystick method. But joystick controller uses both hands and takes a long time to learn. Particularly, in the case of 8-character flight, it is necessary to use both front and rear flight (pitch), left and right flight (Roll), and body rotation (Yaw). Joystick controller has limitations to intuitively control it. In particular, when the main body rotates, the viewpoint of the forward direction is changed between the drones and the user, thereby causing a mental rotation problem in which the user must control the rotating state of the drones. Therefore, we developed a motion matching controller that matches the motion of the drones and the controller. That is, the movement of the drone and the movement of the controller are the same. In this study, we used a gyro sensor and an acceleration sensor to map the controller's forward / backward, left / right and body rotation movements to drone's forward / backward, left / right, and rotational flight motion. The motor output is controlled by the throttle dial at the center of the controller. As the motions coincide with each other, it is expected that the first drone operator will be able to control more intuitively than the joystick manipulator with less learning.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.5
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• pp.436-443
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• 2013

This paper presents design methods of a fuzzy controller and an operator model for a wire-driven heavy material lifting system helping human workers. The wire-driven heavy material lifting system is a kind of human-assistive systems in which a human is involved in the control loop. Thus, human's control characteristics and requirement of reducing worker's force to lift a heavy material are considered in the design process of the proposed fuzzy controller. An automatic weight measurement algorithm during the early stage of lifting is also introduced. Finally, the effectiveness and performance of the proposed system are proved by experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.11
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• pp.912-918
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• 2016

This paper presents various strategies for humanoid vehicle driving and egress tasks. For driving, a tele-operating system that controls a robot based on a human operator's commands is built. In addition, an autonomous assistant module is developed for the operator. Normal position control can result in severe damage to robots when they egress from vehicles. To prevent this problem, another approach that mixes various joint control techniques is adopted in this study. Additionally, a footplate is newly designed and attached to the vehicle floor for the ground landing phase of the egress task. The attached plate enables the robot to step down onto the ground in a safe manner. For stable locomotion, a balance controller is designed for the humanoid. For the design of the controller, the robot is modeled using an inverted pendulum that consists of a spring and a damper. Then, a state feedback controller (with pole placement and a state observer) is built based on the simplified model. Many approaches that are presented in this paper were successfully applied to a full-sized humanoid, DRC-HUBO+, in the DARPA Robotics Challenge Finals, which were held in the United States in 2015.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.12
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• pp.1521-1527
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• 2013

This study proposes a wearable master device that can measure the joint stiffness and the angular displacement of a human operator to enhance the adapting capability of a slave system. A lightweight inertial sensor and the exoskeleton mechanism of the master device can make an operator feel comfortable, and artificial pneumatic muscles having a working principle similar to that of human muscles improve the performance of the slave device on emulating what a human operator does. Experimental results revealed that the proposed master/slave system based on the muscle stiffness sensor yielded uniform tracking performance compared with a conventional position-feedback controller when the payload applied to the slave system changed.

• Journal of IKEEE
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• v.6 no.1 s.10
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• pp.30-39
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• 2002

In this paper, we proposed a new circuit construction method that reduces the number of circuit devices of fuzzy controller. Sasaki had defined a new operator to eliminate the divide circuit comparing with the center of gravity method which often using to design the fuzzy controller. In this paper we obtained the more compacted fuzzy controller's circuit by using the proposed definition of fuzzification and defuzzification than using the Sasaki's method and the fuzzification and defuzzification are reverse operation each other. Using these definitions we exhibit the new design method and circuit structure that can eliminate the bounded product(BP) circuit included in Sasaki's circuit. Using the proposed method to level controlling of the water tank, we verified the fuzzy controller's performance by using existent method and proposed method. As a result that are calculated by using the Proposed fuzzy controller to level controlling of the water tank, total numbers of blocks and devices were decreased. If the number of variables and antecedents are Be11ing larger, this method is more efficient.