• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.11a
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• pp.282-286
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• 1999

This paper describes the implementation of a fuzzy temperature measuring & control system to control the water temperature in plant. This system consisted of mainly three parts; sensing part, control part that includes a control algorithms introduced the fuzzy theory, and actuating part. The control algorithms of control part are utilized a look-up table method and firmware technique using one-chip microprocessor(89C52). For evaluating the performance of a fuzzy control system, the experiment results of a fuzzy controller are compared with these of a conventional PID controller which provides an auto-tuning function. The experiment results show that the proposed controller has a good control performance and is robust to external disturbance.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2176-2179
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• 2002

This paper introduces a hybrid induction motor control using a genetically optimized pseudo-on-line method. Optimization results from the use of a look-up table based on genetic algorithms to find the global optimum of a un-constraint optimization problem. The approach to induction motor control includes a pseudo-on-line procedure that optimally estimates parameters of a fuzzy PID (FPID) controller. The proposed hybrid genetic fuzzy PID (GFPID) controller is applied to speed control of a 3-phase induction motor and its computer simulation is carried out. Simulation results show that the proposed controller is performs better than conventional FPID and PID controllers. The contribution of this paper is the introduction of a high performance hybrid form of induction motor control that makes on-line and real-time control of the drive system possible.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.1
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• pp.8-17
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• 2002

This paper suggests that the immune algorithm can effectively be used in tuning of a PID controller. The artificial immune network always has a new parallel decentralized processing mechanism for various situations, since antibodies communicate to each other among different species of antibodies/B-cells through the stimulation and suppression chains among antibodies that form a large-scaled network. In addition to that, the structure of the network is not fixed, but varies continuously. That is, the artificial immune network flexibly self-organizes according to dynamic changes of external environment (meta-dynamics function). However, up to the present time, models based on the conventional crisp approach have been used to describe dynamic model relationship between antibody and antigen. Therefore, there are some problems with a less flexible result to the external behavior. On the other hand, a number of tuning technologies have been considered for the tuning of a PID controller. As a less common method, the fuzzy and neural network or its combined techniques are applied. However, in the case of the latter, yet, it is not applied in the practical field, in the former, a higher experience and technology is required during tuning procedure. In addition to that, tuning performance cannot be guaranteed with regards to a plant with non-linear characteristics or many kinds of disturbances. Along with these, this paper used immune algorithm in order that a PID controller can be more adaptable controlled against the external condition, including moise or disturbance of plant. Parameters P, I, D encoded in antibody randomly are allocated during selection processes to obtain an optimal gain required for plant. The result of study shows the artificial immune can effectively be used to tune, since it can more fit modes or parameters of the PID controller than that of the conventional tuning methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.5
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• pp.67-76
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• 1997

In this paper, a theoretical study is presented for the force control of a miniature robotic manipulator which is driven by a pair of piezo-electric bimorph cells. In the theoretical analysis, one finger is modeled as a flexible cantilevers with a force sensor at the tip and the finger is a solid beam. The robotic finger is used to hold the objects with different stiffness such as an iron block and a living insect and a moving objcet. So it is very important to develop an adequate controller for the holding operation of the finger. The main problems in force controlling are overdamping, overshoot and unknown environment(such as the stiffness of object and unknown plant parameters). So, the main target is propose the new fuzzy compensation for unknown environment and incease the system performance. The fuzzy compensation is implemented by using PI-type fuzzy approach to identified unknown environment. And the result of proposed controller was compared with the conventaional PID and optimal controller.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.496-500
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• 1993

This paper presents an end-point position control of 1-link flexible robot arm by the PID self-tuning fuzzy algorithm. The governing equation is derived by the extended Hamilton's principle and based on the Bernoullie-Euler beam theory. The governing equation is solved by applying the Laplace transform and the numerical inversion method. The arm is mounted on the translational mechanism driven by a ballscrew whose rotation is controlled by dcservomotor. Tip position is controlled by the PID self-tuning fuzzy algorithm so that it follows a desired position. This paper shows the experimental and theoretical results of tip dispalcement, and also shows the good effects reducing the residual vibration of the end-point.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.165-165
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• 2000

The sunlight tracking and reflexing system can be divided into two parts. One is a sunlight tracking system and the other is a sunlight reflexing system. The sunlight tracking system detects an azimuth angie and an elevation angle of the sun using 2-axis sensor sun tracker. The sunlight reflexing system controls a reflection mirror to be reflected a sunlight at the target area after getting the azimuth angle and the elevation angle of the sun from the sunlight tracking system. We applied the fuzzy PID controller to control the reflexing mirror.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.2
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• pp.120-125
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• 2010

This paper proposes an intelligent PID/Fuzzy control system for two humanoid robots to transport objects stably. When a robot transports an object while walking, a whole body system of a robot may not be stable due to vibration or external factors from a different departure speed error and a body movement of walking robots. Therefore, it is necessary to measure the horizontal and vertical locations and speeds of object, then calibrate the difference of departure speed between robots with PID/Fuzzy control. The results of simulation with two robots indicated that a proposed controller makes robots to transport an object stably.

• Journal of Advanced Marine Engineering and Technology
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• v.36 no.8
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• pp.1104-1110
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• 2012

The inverted pendulum system is a common, interesting control problem that involves many basic elements of control theory. In the early, controls of stabilization for the inverted pendulum system were used classical methods like PD, PID controller. In recently, however, control methods based on modern and intelligent control theory are widely applied. The fuzzy logic controller which is often used in nonlinear control is a little too hard to design due to increasing fuzzy rules rapidly if the given system like inverted pendulum has many state variables. Also, in case the state variables are divided into two parts, two fuzzy controllers are needed in the control system. In this paper, the authors propose FCSC(Fuzzy Controller based on State variables Combination) that reorganized into two new signals depending on the physical meaning of the four state variables of the inverted pendulum system. The proposed method is applied to the inverted pendulum system and simulations are accomplished to illustrate the control performance.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.4
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• pp.309-314
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• 2009

This paper presents implementation of the adaptive neuro-fuzzy control method. Control performance of the adaptive neuro-fuzzy control method for a popular inverted pendulum system is evaluated. The inverted pendulum system is designed and built as an education kit for educational purpose for engineering students. The educational kit is specially used for intelligent control education. Control purpose is to satisfy balancing angle and desired trajectory tracking performance. The adaptive neuro-fuzzy controller has the Takagi-Sugeno(T-S) fuzzy structure. Back-propagation algorithm is used for updating weights in the fuzzy control. Control performances of the inverted pendulum system by PID control method and the adaptive neuro-fuzzy control method are compared. Control hardware of a DSP 2812 board is used to achieve the real-time control performance. Experimental studies are conducted to show successful control performances of the inverted pendulum system by the adaptive neuro-fuzzy control method.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.4
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• pp.281-287
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• 2002

This paper investigates on the feasibility of fuzzy logic control for networked control systems. In order to evaluate its feasibility, a networked control system for motor speed control is implemented on a Profibus-DP network. The NCS consists of several inde-pendent, but interacting processes running on two separate stations. By using this NCS, the network-induced delay is analyzed to find the cause and effect of the delay. Furthermore, in order to prove the feasibility, the fuzzy logic controller's performance is compared with those of conventional PID controllers. Based on the experimental results, the fuzzy logic controller can be a viable choice far NCS due to its robustness against parameter uncertainty.