• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.136-138
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• 2006

Recently, network systems are widely used in several areas, and some considerable attentions have been directed to the Networked Control System(NCS). In NCS, network-induced delays are inevitable, and they sometimes degrade the performance of networked control systems to be a source of potential instability. In this paper, We proposes a compensation method for networked control system subject to network-induced delays by using a simple method, which is based on a sort of predictive strategy. To evaluate its feasibility and effectiveness, a real-time NCS for a rotary inverted pendulum is implemented via an Ethernet. Based on the experimental results. we show that the proposed simple method can be a practical and feasible solution to NCS design.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.103.1-103
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• 2002

In variable structure control algorithms, The control law used to realized the desired sliding mode dynamics is discontinuous on the switching manifold. However, due to imperfections in switching, such as time delays, the system trajectory chatters instead of sliding along the switching manifold. This chattering is undesirable because it may excite unmodeled high frequency dynamics in the physical system. In this paper, to overcome this drawback a self-organizing fuzzy sliding mode control algorithm using gradient descent method is proposed. The proposed method has the characteristics which are viewed in conventional VSC, e.g. insensitivity to a class of disturbance, parameter variations and uncertainties ill the sliding mode. To demonstrate its performance, the proposed control algorithm is applied to an inverted pendulum system. The results show that both alleviation of chattering and performance are achieved.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.2
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• pp.146-156
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• 2003

Nonlinear dynamic system exist widely in many types of systems such as chemical processes, biomedical processes, and the main steam temperature control system of the thermal power plant. Up to the present time, PID Controllers have been used to operate these systems. However, it is very difficult to achieve an optimal PID gain with no experience, because of the interaction between loops and gain of the PID controller has to be manually tuned by trial and error. This paper suggests control approaches by immune fuzzy for the nonlinear control system inverted pendulum, through computer simulation. This paper defines relationship state variables $x,\dot{x},{\theta},\dot{\theta}$ using immune fuzzy and applied its results to stability.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.2
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• pp.154-161
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• 2012

This article presents experimental studies of fuzzy logic application to control a two-wheel mobile robot(TWMR) system. The TWMR system is composed of two systems, an inverted pendulum system and a mobile robot system. Although linear controllers can stabilize the TWMR, fuzzy controllers are expected to have robustness to uncertainties so that the resulting performances are expected to be better. Nominal fuzzy rules are used to control balance and position of TWMR. Fuzzy logic is embedded on a DSP chip to control the TWMR. Balancing performances of the PID controller and the fuzzy controller under disturbances are compared through extensive experimental studies.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.10
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• pp.922-929
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• 2004

In this paper, we develop control hardware such as an FPGA based general purposed intelligent controller with a DSP board to solve nonlinear system control problems. PID control algorithms are implemented in an FPGA and neural network control algorithms are implemented in a BSP board. An FPGA was programmed with VHDL to achieve high performance and flexibility. The additional hardware such as an encoder counter and a PWM generator can be implemented in a single FPGA device. As a result, the noise and power dissipation problems can be minimized and the cost effectiveness can be achieved. To show the performance of the developed controller, it was tested fur nonlinear systems such as a robot hand and an inverted pendulum.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.5
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• pp.43-54
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• 1997

The objective of this paper is to present a controller-design method that can guarantee the global stability for nonlinear systems described by takagi-sugeno fuzzy models, and to apply the method to a typical nonlinear control problem. The presented method gives us a compensated fuzzy controller through the following major steps: First, if each local linear model of a given takagi-sugeno fuzzy system does not have the same input matrix, the method expands the system into the one with a method finds a takagi-sugeno fuzzy controller guaranteeing the global stability of the closed loop via solving relevant linear matrix inequalities. Compared to the conventional PDC (paralled distributed compensation) technique, the presented method has an advantage that trial-and-errors to check the global stability are not necessary. An illustrative simulation on the control of inverted pendulum is performed to demonstrate the applicability of the presented method, and its results show that a controller satisfying the global stability and robustness can be obtained by the method.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.4
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• pp.228-234
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• 2005

In this paper, we proposed a self tuning adaptive fuzzy sliding control algorithms using gadient descent method to reduce chattering phenomenon which is viewed in variable control system. In design of FLC, fuzzy control rules are obtained from expert's experience and intuition and it is very difficult to obtain them. We proposed an adaptive algorithm which is automatically updated by consequence part parameter of control rules in order to reduce chattering phenomenon and simultaneously to satisfy the sliding mode condition. The proposed algorithm has the characteristics which are viewed in conventional VSC, e.g. insensitivity to a class of disturbance, parameter variations and uncertainties in the sliding mode. To demonstrate its performance, the proposed control algorithm is applied to an inverted pendulum system. The results show that both alleviation of chattering and performance are achieved.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.5
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• pp.60-66
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• 1997

This paper presents a fuzzy inference-based reinforcement learning algorithm of dynamci recurrent neural networks, which is very similar to the psychological learning method of higher animals. By useing the fuzzy inference technique the linguistic and concetional expressions have an effect on the controller's action indirectly, which is shown in human's behavior. The intervlas of fuzzy membership functions are found optimally by genetic algorithms. And using recurrent neural networks composed of dynamic neurons as action-generation networks, past state as well as current state is considered to make an action in dynamical environment. We show the validity of the proposed learning algorithm by applying it to the inverted pendulum control problem.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.6
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• pp.578-584
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• 2015

In this study a moving platform for a mobile robot that can be traveling with a full automatic standing arm was developed. Conventional mobile robots generally may equip 4 wheels or 3 wheels with a caster wheel or independent driven wheels and have good statistic stability. When a mobile robot travels on a sharply perpendicular and narrow crossroad, it may need a special steering scheme such as going forward and backward repeatedly or it is sometimes physically impossible for the robot to go through the crossroad because of the size limit. The upright running mobile robot changes its posture to the upright posture which has a small planar area and is able to go through the crossroad. The upright control which was manually performed step by step before such as sequences of uprighting (returning), checking, and balancing, is now automated.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.181-184
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• 1997

This paper propose the systematic procedure of the fuzzy model based controller for the continuous nonlinear system. Fuzzy controller have been successfully applied to many uncertain and complex industrial plants. The design of the fuzzy controller mainly depends on the knowledge from the expert who are familiar with the plant by trial and error. Therefore we need more systematic approach to the design of the fuzzy controller. In this paper, we design fuzzy model based controller applied to the nonlinear system. Unlike the design procedures reported in[8] and[9], we use the nonlinear process directly in designing the controller. This controller has been successfully applied to an inverted pendulum.