• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1996.10a
• /
• pp.166-171
• /
• 1996

Generally, when we control the robot, we should calculate exactly Inverse Kinematics. However, Inverse Kinematics calculation is complex and it takes much time for the manipulator to control in real-time. Therefore, the calculation of Inverse Kinematics can result in significant control delay in real time. In this paper, we will present that Inverse Kinematics can be calculated through Fuzzy Logic Mapping, Based on an exact solution through fuzzy reasoning instead of Inverse Kinematics calculation Also, the result provides sufficient precision and transient tracking error can be controlled based on a fuzzy adaptive scheme proposed in this paper. Based on the Denavit-Hartenberg parameters specification, after the Jacobian matrix of arbitrary manipulator is calculated, we will construct Fuzzy Inverse Kinematics Mapping(FIKM) using fuzzy logic and represent a good control efficiency through simulation of 2-DOF manipulator.

• Proceedings of the KIEE Conference
• /
• 1995.07a
• /
• pp.300-302
• /
• 1995

This paper describes a current control method for a single-phase PWM inverter. The proposed PWM inverter utilizes the instantaneous control method which is based on the real-time digital feedback control and the microprocessor-based deadbeat control. For the deadbeat current controller, the system's order becomes a high order and increases computation delay time. Therefore, The delay time produces current ripple. To minimize the current ripple, a new method based on deadbeat control theory for current regulation is proposed. It is constructed by a reduced-order state observer which predicts the output current in next sampling instant.

• ETRI Journal
• /
• v.6 no.2
• /
• pp.3-9
• /
• 1984

This paper proposes an optimal control scheme for shaft position control using microcomputer-based state-variable feedback. In this scheme a performance index was set up in order to ruduce the overshoot and improve the steady- state response speed, and the time-variant system parameters were identified in real time for optimal control. As a result of experiment, the over-shoot was not occured and the response speed was improved 2. 9 times about proportional control. This scheme improves the performance against the variation of load and sampling time, and adding the integral control in this scheme can reduce the steady-state error without any change in response time.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.1655-1658
• /
• 2004

In this paper, we design and implement remote servo motor control system with real-time micro embedded operating system. The system, where controller and camera image grabber are mounted, handles control commands transmitted from a remote PC web browser. A hard real-time servo motor driver running on the real-time micro embedded OS and then a digital control application which confirms precise sampling time intervals is constructed. Frame grabber images transmitted from camera are saved in a image data format to view on remote PC web browser.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.994-998
• /
• 2005

A new control method, called a simple model matching, has been recently developed by the author. This is very simple and be applied for linear and nonlinear discrete time systems with/without time lag. Based on this formulation, identification is examined in this paper using an interconnected neural network with the EBP-EWLS learning algorithm. With this result, a control method is also presented for a nonlinear discrete time system.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.8 no.2
• /
• pp.310-323
• /
• 2004

In this paper, we extend the multiple time scale control framework to window-based congestion control, in particular, TCP This is performed by interfacing TCP with a large tine scale control nodule which adjusts the aggressiveness of bandwidth consumption behavior exhibited by TCP as a function of "large time scale" network state. i.e., conformation that exceeds the horizon of the feedback loop as determined by RTT Our contribution is threefold. First, we define a modular extension of TCP-a function call with a simple interface-that applies to various flavors of TCP-e.g., Tahoe, Reno, Vegas and show that it significantly improves performance. Second, we show that multiple time scale TCP endows the underlying feedback control with preactivity by bridging the uncertainty gap associated with reactive controls which is exacerbated by the high delay-bandwidth product in broadband wide area networks. Third, we investigate the influence of three traffic control dimensions-tracking ability, connection duration, and fairness-on performance. Performance evaluation of multiple time scale TCP is facilitated by a simulation bench-mark environment which is based on physical modeling of self-similar traffic.

• Journal of Institute of Control, Robotics and Systems
• /
• v.6 no.9
• /
• pp.758-767
• /
• 2000

The properties of linear time-varying(LTV) systems vary because of the time-varying property of plant parameters. The generalized controller design method for linear time-varying systems does not exit because the analytic soultion of dynamic equation has not been found yet. Hence, to design a controller for LTV systems, the robust control methods for uncertain LTI systems which are the approximation of LTV systems have been generally ised omstead. However, these methods are not sufficient to reflect the fast dynamics of the original time-varying systems such as missiles and supersonic aircraft. In general, both the performance and the robustness of the control system which is designed with these are not satisfactory. In addition, since a better model will give the more robustness to the controlled system, a gain scheduling technique based on LTI controller design methods has been uesd to solve time problem. Therefore, we propose a new gain scheduled QFT method for LTV systems based on neural networks in this paper. The gain scheduled QFT involves gain dcheduling procedured which are the first trial for QFT and are well suited consideration of the properties of the existing QFT method. The proposed method is illustrated by a numerical example.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.12 no.3
• /
• pp.238-244
• /
• 2012

A modeling of vision based robot formation control system using fuzzy logic controller and extended Kalman filter is presented in this paper. The main problems affecting formation controls using fuzzy logic controller and vision based robots are: a robot's position in a formation need to be maintained, how to develop the membership function in order to obtain the optimal fuzzy system control that has the ability to do the formation control and the noise coming from camera process changes the position of references view. In order to handle these problems, we propose a fuzzy logic controller system equipped with a dynamic output membership function that controls the speed of the robot wheels to handle the maintenance position in formation. The output membership function changes over time based on changes in input at time t-1 to t. The noises appearing in image processing change the virtual target point positions are handled by Extended Kalman filter. The virtual target positions are established in order to define the formations. The virtual target point positions can be changed at any time in accordance with the desired formation. These algorithms have been validated through simulation. The simulations confirm that the follower robots reach their target point in a short time and are able to maintain their position in the formation although the noises change the target point positions.

• 제어로봇시스템학회:학술대회논문집
• /
• 1990.10a
• /
• pp.135-139
• /
• 1990

In general, the control of robot arms falls into two board categories (position control and force control). The joint interpolated trajectory schemes generally interpolate the desired joint path by a class of polynomial functions and generate a sequence of time based control set points for the control of a manipulator from a initial location to its destination. A digital position controller was designed and adapted to the industrial balancing manipulator. And also, the joint interpolated trajectory using 3rd order polynomial was generated in this study. The IBM PC used as the main controller and the trajectory planner had enough run-time capabilities. The 8097BH microcontroller is an integral pan of the joint controller which directly controls an axis of motion. The PI servo control system to treat each joint of the robot arm as a independent joint servo mechanism had satisfying performance, and a sequence of time-based intermediate configurations of the manipulator hand showed good continuity and smoothness on position and velocity of the manipulator's joint coordinates along the trajectory.

• Journal of the Korean Society of Industry Convergence
• /
• v.23 no.2_1
• /
• pp.149-161
• /
• 2020

We describe a new approach to implement of trajectory control and track record of articulated manipulator based on monitoring simulator for smart factory. The learning control algorithm was applied in implementation real-time control to provide enhanced motion control performance for robotic manipulators. The proposed control scheme is simple in structure, fast in computation, and suitable for real-time control. Moreover, this scheme does not require any accurate dynamic modeling, or values of manipulator parameters and payload. Performance of the proposed controller is illustrated by simulation and experimental results for robot manipulator consisting of six joints at the joint space and Cartesian space.by monitoring simulator.