• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.331-336
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• 1998

A systematic design method for PDC(Parallel Distributed Compensation)-type continuous time Takagi-Sugeno(T-S in short) fuzzy control systems which have inaccessible states is developed in this paper. Reduced-dimensional fuzzy state estimator is introduced from existing T-S fuzzy model using the PDC structure of Wang et al. [1] LMI(Linear Matrix Inequalities) problems which represent the stabililty of the reduced-dimensional fuzzy state estimator are derived. Pole placement constraints idea for each rules is adopted to determine the estimator gains and they are also revealed as LMI problems. these LMI problems are combined with Joh et al's [7][8] LMI problems for PDC -type continuous time T-S fuzzy controller design to yield a systematic design method for PDC -type continuous time T-S fuzzy control systems which have inaccessible states.

• Journal of Power Electronics
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• 제18권6호
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• pp.1634-1641
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• 2018

This study focuses on a high-performance direct active and reactive power controller design that is successfully applicable to three-phase pulse width modulation (PWM) AC/DC converters used in renewable distributed energy generation systems. The proposed controller can overcome the sluggish transient dynamic response of conventional controllers to rapid power command changes. Desired active and reactive powers can be thoroughly obtained at the end of each PWM period through a deadbeat solution. The proposed controller achieves an exact nonlinear cross-coupling decoupling of system power without using a predefined switching table or bang/bang hysteresis control. A graphical and analytical analysis that naturally leads to a control voltage vector selection is provided to confirm the finding. The proposed control strategy is evaluated on a 3 kW PWM AC/DC converter in the simulation and experiment.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.2278-2282
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• 2003

In this paper the structure of 2-DOF controller based on artificial immune network algorithms has been suggested for nonlinear system. Up to present time, a number of structures of the 2-DOF controllers are considered as 2-DOF (2-Degrees Of Freedom) control functions. However, a general view is provided that they are the special cases of either the state feedback or the modification of PID controllers. On the other hand, the immune network system possesses a self organizing and distributed memory, also it has an adaptive function by feed back law to its external environment and allows a PDP (parallel distributed processing) network to complete patterns against the environmental situation, since antibody recognizes specific antigens which are the foreign substances that invade living creatures. Therefore, it can provide optimal solution to external environment. Simulation results by immune based 2-DOF controller reveal that immune algorithm is an effective approach to search for 2-DOF controller.

• Smart Structures and Systems
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• 제25권4호
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• pp.401-408
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• 2020

This paper deals with the problem of global stabilization for a class of nonlinear control systems. An effective approach is proposed for controlling the system interaction of structures through a combination of parallel distributed compensation (PDC) intelligent controllers and fuzzy observers. An efficient approximate inference algorithm using expectation propagation and a Bayesian additive model is developed which allows us to predict the total number of control systems, thereby contributing to a more adaptive trajectory for the closed-loop system and that of its corresponding model. The closed-loop fuzzy system can be made as close as desired, so that the behavior of the closed-loop system can be rigorously predicted by establishing that of the closed-loop fuzzy system.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.1531-1536
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• 2003

In this paper the structure of 2-DOF controller based on artificial immune network algorithms has been suggested for nonlinear system. Up to present time, a number of structures of the 2-DOF controllers are considered as 2-DOF (2-Degrees Of Freedom) control functions. However, A general view is provided that they are the special cases of either the state feedback or the modification of PID controllers. On the other hand, The immune network system possesses a self organizing and distributed memory, also it has an adaptive function by feed back law to its external environment and allows a PDP (parallel distributed processing) network to complete patterns against the environmental situation, since antibody recognizes specific antigens which are the foreign substances that invade living creatures. Therefore, it can provide optimal solution to external environment. Simulation results by immune based 2-DOF controller reveal that immune algorithm is an effective approach to search for 2-DOF controller.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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• pp.147-150
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• 1998

The report presents basic functions of Time-delay System Toolbox (for MATLAB) -the general-purpose software package for Computer Aided Design of control systems with delays. The Toolbox is a collection of algorithms, expressed mostly in m-files for simulating and analysis of MIMO linear and nonlinear systems with discrete and distributed (time-varying) delays.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1997년도 추계학술대회 학술발표 논문집
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• pp.45-49
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• 1997

In this paper, we controlled a Rotary Inverted Pendulum System using Neuro-Fuzzy Controller(NFC). The inverted pendulum system is widely used as a typical example of an unstable nonlinear control system which is difficult to control. Fuzzy theory have been because membership functions and rules of a fuzzy controller are often given by experts or a fuzzy logic control system. This controller is a feedforward multilayered network which integrates the basic elements and functions of a tradtional fuzzy logic controller into a connectionist structure which has distributed learning abilities. Such NFC can be constructed from training examples by learning rule, and the structure can be trained to develop fuzzy logic rules and find optimal input/output membership functions. Using this controller, we presented the results that controlled a Rotary Inverted Pendulum System and the associated algorithms.

• 한국지능시스템학회논문지
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• 제12권3호
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• pp.239-245
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• 2002

본 논문에서는 입력에 제한이 있는 시간지연 비선형 시스템에 대한 퍼지 $H_2/H_{\infty}$ 제어기 설계 방법을 제시한다. 포화입력을 갖는 시간지연 비선형 시스템을 시간지연과 포화입력을 갖는 Takagi-Sugeno 퍼지 모델로 표현하고 병렬분산보상(PDC)의 개념을 이용하여 제어기를 설계한다. Lyapunov 함수를 이용하여 시간지연과 포화입력을 갖는 $H_2/H_{\infty}$ 퍼지모델에 대한 폐루프 시스템의 안정성 조건과 LQ 성능을 최소화하는 조건을 유도하고, 퍼지 $H_2/H_{\infty}$ 제어기가 존재할 충분조건을 선형행렬부등식(LMI: liner matrix inequality)을 이용하여 구한다. 제어기는 선형행렬부등식의 해를 구하므로써 바로 구할 수 있으며, 설계된 퍼지 $H_2/H_{\infty}$ 제어기는 $H_{\infty}$ 노옴 한계값을 만족하면서 LQ성능의 상한값을 최소화한다. 마지막으로 포화압력으로 포화압력을 가지는 시간지연 비선형 시스템에 대해 퍼지 $H_2/H_{\infty}$ 제어기 설계 사례를 보인다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.575-579
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• 2005

In this paper, the development of an IMM(Injection Molding Machine) controller is discussed. Presently, the Mold Close and Open Control Method of a toggle-type IMM is open-loop control. Through the development, a PC based control system was built instead of an existing controller and a closed-loop control replaced the previous control method by using PC based PLC. To control the nonlinear system of toggle type clamping unit, a fuzzy PI control algorithm was selected and it was programmed by an IL(Instruction List) and a LD(Ladder Diagram) on a PC based PLC. The application of fuzzy algorithm as the control method was also considered to change a control object like a mold replacement or an additional apparatus. For the development of an IMM controller, PC based PLC of PCI card type, distributed I/O modules with CANopen and Industrial PC and HMI (Human Machine Interface) software were used.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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• pp.460-463
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• 1995

The present paper studies a robot manipulator's contact tasks on the uncertain flexible objects. The flexible object's distributed parameter model is approximated into a lumped "position state-varying" model. By using the well-known nonlinear feedback compensation, the robot's control space is decomposed into the position control subspace and the object's torque control subspace. The optimal state feedback is designed for the position loop, and the robot's contact force is controlled through controlling the resultant torque on the object using model-reference simple adaptive control. Experiments of a PUMA robot interacting with an aluminum plate show the effectiveness of this control approach. approach.