• Journal of Institute of Control, Robotics and Systems
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• v.7 no.6
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• pp.477-486
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• 2001

Many physical systems can be modeled by incorporating continuous and discrete event nature together. Such hybrid systems contain both continuous and discrete states that influence the dynamic be-havior of the systems. There has been an increasing interest in thers types of systems during the last dec-ade, mostly due to the growing usage of computers in the control of physical plants but also as a result of the hybrid nature of physical processes. The stability theory for hybrid systems is considered as extension of Lyapunov theory where the existence of an abstract energy function satisfying certain properties verifies stability, called multiple Lyapunov theory. In this paper, a hybrid stabilizing controller is proposed using the control Lyapunov function method and multiple Lyapunov theory, and the proposed method is applied to lon-gitudinal spacing control in a vehicle platoon for intelligent transportation systems(ITS).

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.146-149
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• 2000

In this paper, Computer Colour Matching and Kitchen System (CCMKS) is developed on the basis of delphi package and one-chip processor with fuzzy-PID control. CCMKS will be widely used in the colour dyeing industry as an integrated colour matching and dispensing system which have more advantages than the conventional matching or dispensing system, when controlling the real dyeing processes. Delphi is utilized in making database and search/matching routes. The developed matching function reduces the search and matching time to about one third. One-chip processor is designed and manufactured for the distributed control of three-phase induction motors. Fuzzy-PID control is applied to the speed control of three-phase induction motors for a very precise weight of colour at CCMKS. The developed kitchen function decreases the dispensing time to about one twentieth. The experimental results show CCMKS has more excellent search time, more precise weight and much high fidelity than conventional colour matching or dispensing system, in the performance.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.276-279
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• 2005

A review of how the functions of two or more independent variables can be approximated by using fuzzy systems is provided in this paper. We start with an exact represention of a linear interpolation function of two independent variables by using a fuzzy system. Next, we describe how this function can be approximated by another fuzzy system with a lesser number or with a desired number of output fuzzy sets. Thus, a reduction of the storage needed is achieved by storing the fuzzy rules or equivalently the output fuzzy set numbers instead of storing the whole discrete function values. A description on how the cubic spl me interpolation function can be represented exactly by using the fuzzy system method is provided, along with a few examples where fuzzy rule tables with a size of 7$\times$7 provide a representation of the functions with relative errors of the order of $10^{2}$ or less.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.532-538
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• 1998

In this paper, a new adaptive fuzzy inference method using neural network based fuzzy reasoning is proposed to make a fuzzy logic control system more adaptive and more effective. In most cases, the design of a fuzzy inference system rely on the method in which an expert or a skilled human operator would operate in that special domain. However, if he has not expert knowledge for any nonlinear environment, it is difficult to control in order to optimize. Thus, using the proposed adaptive structure for the fuzzy reasoning system can controled more adaptive and more effective in nonlinear environment for changing input membership functions and output membership functions. The proposed fuzzy inference algorithm is called adaptive neuro-fuzzy control(ANFC). ANFC can adapt a proper membership function for nonlinear plant, based upon a minimum number of rules and an initial approximate membership function. Nonlinear function approximation and rotary inverted pendulum control system ar employed to demonstrate the viability of the proposed ANFC.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.1
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• pp.93-99
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• 2003

One of the methods to simplify the design process for a fuzzy logic controller (FLC) is to reduce the number of variables representing the rule antecedent. This in turn decreases the number of control rules, membership functions, and scaling factors. For this purpose, we designed a single-input FLC that uses a sole fuzzy input variable. However, it is still deficient in the capability of adapting some varying operating conditions although it provides a simple method for the design of FLC's. We here design two simple-structured adaptive fuzzy logic controllers (SAFLC's) using the concept of the single-input FLC. Linguistic fuzzy control rules are directly incorporated into the controller by a fuzzy basis function. Thus some parameters of the membership functions characterizing the linguistic terms of the fuzzy control rules can be adjusted by an adaptive law. In our controllers, center values of fuzzy sets are directly adjusted by an adaptive law. Two SAFLC's are designed. One of them uses a Hurwitz error dynamics and the other a switching function of the sliding mode control (SMC). We also prove that 1） their closed-loop systems are globally stable in the sense that all signals involved are bounded and 2） their tracking errors converge to zero asymptotically. We perform computer simulations using a nonlinear plant.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.15-20
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• 2004

In this paper, design approach of PID controller with rejection function against external disturbance in motor control system is proposed using bacterial foraging based optimal algorithm. Up to the present time, PID Controller has been used to operate for AC motor drive because of its implementational advantages in practice and simple structure. However, it is not easy to achieve an optimal PID gain with no experience, since the gain of the PID controller has to be manually tuned by trial and error in the industrial system with disturbance. To design disturbance rejection tuning, disturbance rejection conditions based on H$\_$$\infty$/ are illustrated and the performance of response based on the bacterial foraging is computed for the designed PID controller as ITSE (Integral of time weighted squared error). Hence, parameters of PID controller are selected by bacterial foraging based optimal algorithm to obtain the required response.

• International Journal of Precision Engineering and Manufacturing
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• v.5 no.3
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• pp.26-34
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• 2004

This paper examines the usefulness of a Brake Steer System(BSS), which uses differential brake forces for steering intervention in the context of Intelligent Transportation Systems(ITS). In order to help the car to turn, a yaw moment control was achieved by altering the left/right and front/rear brake distribution. This resulting yaw moment on the vehicle affects lateral position thereby providing a limited steering function. The steering function achieved through BSS was used to control lateral position in an unintended road departure system. A 8-DOF nonlinear vehicle model including STI tire model was validated using the equations of motion of the vehicle. Then a controller was developed. This controller, which is a PID controller tuned by Ziegler-Nichols, is designed to explore BSS feasibility by modifying the brake distribution through the control of the yaw rate of the vehicle.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.9
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• pp.95-103
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• 1995

Recently the trends toward reduction in size of industrial products have increased the application of micro drilling. But micro drilling has still much difficulty so that the needs for active control which give adaptation to controller are expanding. In this paper initial cutting condition was determined for some sorkpieces by experiment and GA-based Fuzzy controller was devised by genetic algorithms and fuzzy inference. The fuzzy inference has been applied to the various prob- lems. However the determination of the membership function is one of the difficult problem. So we introduce a genetic algorithms and propose a self-tuning method of fuzzy membership function. Based on this intelligent control, automation of micro drilling was carried out like the cutting process of skilled machinist.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.4
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• pp.546-552
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• 2020

The remote control system, in which the remote control server and the actuator are connected and operated through a wireless network, has a great potential risk as well as its convenience. The control commands can be lost because of unreliable wireless channels. The intelligent remote control system is a system that adds a function to infer a control command to the actuator to operate even if the control command is not received. In this paper, we implemented an intelligent remote control system testbed and confirmed the problems that could occur in the remote control system through experiments and verified that the intelligent remote control system solves the problem. The intelligent remote control system can achieve the performance that can be achieved when general remote control system has high communication overhead with less communication overhead.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.9
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• pp.755-762
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• 2004

In this research, EOG(Electrooculogram) signal was analyzed to predict the subject's intention using a fuzzy classifier. The fuzzy classifier is built automatically using the EOG data and evolutionary algorithms. An assistant robot manipulator in redundant configuration has been developed, which operates according to the EOG signal classification results. For automatic fuzzy model construction without any experts' knowledge, an evolutionary algorithm with the new representation scheme, design of adequate fitness function and evolutionary operators, is proposed. The proposed evolutionary algorithm can optimize the number of fuzzy rules, the number of fuzzy membership functions, parameter values for the each membership functions, and parameter values for the consequent parts. It is shown that the fuzzy classifier built by the proposed algorithm can classify the EOG data efficiently. Intelligent motion planner that consists of several neural networks are used for control of robot manipulator based upon EOG classification results.