• Journal of Power Electronics
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• v.16 no.2
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• pp.610-620
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• 2016

The compound active clamp zero voltage soft switching (CACZVS) three-phase power factor correction (PFC) converter has many advantages, such as high efficiency, high power factor, bi-directional energy flow, and soft switching of all the switches. Triple closed-loop PI controllers are used for the three-phase power factor correction converter. The control objectives of the converter include a fast transient response, high accuracy, and unity power factor. There are six parameters of the controllers that need to be tuned in order to obtain multi-objective optimization. However, six of the parameters are mutually dependent for the objectives. This is beyond the scope of the traditional experience based PI parameters tuning method. In this paper, an improved chaotic particle swarm optimization (CPSO) method has been proposed to optimize the controller parameters. In the proposed method, multi-dimensional chaotic sequences generated by spatiotemporal chaos map are used as initial particles to get a better initial distribution and to avoid local minimums. Pareto optimal solutions are also used to avoid the weight selection difficulty of the multi-objectives. Simulation and experiment results show the effectiveness and superiority of the proposed method.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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• pp.287-292
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• 2003

The ability of robot is being various and complex. The robot is utilizing distance, image data and voice data for sensing its circumstance. This paper suggests the 2-layer fuzzy control as the algorithm that control robot with various sensor information. In a obstacle avoidance, it utilizes many range finders and classifies them into 3parts(front, left, right). In 3 sub-controllers, the controller executes fuzzy conference. And then it executes combined control with a combination of outputs of 3 sub-controllers in the second step. The text compares the 2-layer fuzzy controller with the hierarchical fuzzy controller that has analogous structure. And the performance of the 2-layer fuzzy controller is confirmed by application this controller to robot following, simulation to each other and real experiment.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.6
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• pp.477-486
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• 2001

In this paper , we study the problem of designing TS(Takagi-Sugeno) fuzzy controllers for the systems that can be approximated or represented by the TS fuzzy model. The main strategy used in this paper is the inverse optimal approach, in which the cost function is determined later than the Lyapunov function and its corresponding control input satisfying the design requirements such as stability, decay rate, and robustness against uncertainty. This approach is useful because it yields controllers satisfying the inherent robustness of optimal controllers as well as the considered design goals. The design procedures established in this paper are all in the from of solving LMIs(Iinear matrix inequalities). Since the LMIs arising in the design procedures can be solved within a given tolerance by the interior point methods. the design method of the paper are efficient in practice. The applicability of the proposed design procedures is demonstrated by design examples.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2266-2270
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• 2005

In this paper, an internet based control application for dynamical systems is implemented. This implementation is maily targeted for the part of advanced control education. Intelligent control algorithms are implemented in a PC so that a client can remotely access the PC to control a dynamical system through the internet. Neural network is used as an on-line intelligent controller. To have on-line learning and control capability, the reference compensation technique is implemented as intelligent control hardware of combining a DSP board and an FPGA chip. GUIs for a user are also developed for the user's convenience. Actual experiments of motion control of a DC motor have been conducted to show the performance of the intelligent control though the internet and the feasibility of advanced control education.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.969-974
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• 2004

For a maneuvering unmanned autonomous helicopter, it is necessary to design a proper controller of each flight mode. In this paper, overall helicopter dynamics is derived and hovering model is linearized and transformed into a state equation form. However, since it is difficult to obtain parameters of stability derivatives in the state equation directly, a linear control model is derived by time-domain parametric system identification method with real flight data of the model helicopter. Then, two different controllers - a linear feedback controller with proportional gains and a robust controller - are designed and their performance is compared. Both proposed controllers show outstanding results by computer simulation. These validated controllers can be used to autonomous flight controller of a real unmanned model helicopter.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.630-632
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• 1999

In this paper, we develop intelligent digitally redesigned PAM and PWM fuzzy controllers for nonlinear systems. Takagi-Sugeno fuzzy model is used to model the nonlinear systems and a continuous-time fuzzy-model-based controller is designed based on the extended parallel-distributed-compensation method. The digital controllers are determined from existing analogue controllers. The proposed method provides an accurate and effective method for digital control of continuous·time nonlinear systems and enables us to efficiently implement a digital controller via pre-determined continuous-time TS fuzzy-model-based controller. We have applied the proposed method to the balancing problem of the inverted pendulum to show the effectiveness and feasibility of the method.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2398-2400
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• 2000

In this paper, we consider multi-objective synthesis of fuzzy controllers for a widely used special class of the Takagi-Sugeno(TS) fuzzy systems. We propose a new fuzzy controller utilizing the strategy of rescaling and show that synthesis of the proposed controllers satisfying multiple design objectives can be reduced to a simple linear matrix inequality(LMI) problem. Finally, an application to an inverted pendulum on a cart is presented to illustrate the validity of the proposed method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.6
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• pp.927-934
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• 2017

This paper is concerned with applicability of two-degree-of-freedom controllers to the recently suggested i-PID controllers, in which unknown parts of the plant are taken into account without any modeling procedure. First, i-PID controller with two-degree-of-freedom is applied to a specific model, called Anisochronic model, to confirm the usefulness of this method. Second, using the original examples of i-PID controllers, it is confirmed that performance/robustness of system are to be improved due to two-degree-of-freedom, especially when the input changes suddenly. It is seen that as the desired robustness increases the optimal value of two-degree-of-freedom parameter ${\alpha}_A$ would be negative. It is checked and verified that if this value was limited to 1 or less as is generally known, performance would be degraded.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.8
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• pp.1383-1391
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• 2016

This paper is concerned with applicability of a new type of controllers, called i-PID and GPI in which unknown parts of the plant are taken into account without any modeling procedure, to automatic voltage regulator (AVR) system. First, the procedure for applying i-PID and GPI algorithms to AVR system is proposed, which uses model reduction technique based on the given information of AVR. Second, simulations are given to verify their effectiveness comparing to various PID algorithms including PIDD2 which is four-term controller, that is, consisting of PID and second order derivative terms. Superior response performances of i-PID and GPI in comparison to conventional PID controllers are shown. Moreover, i-PID can highly improve the system robustness with respect to model uncertainties, especially to load variations.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.2
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• pp.139-145
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• 2002

In this paper, we proposed an intelligent digital redesign method for a class of fuzzy-model-based controllers, effective fur stabilization of continuous-time nonlinear systems. The TS fuzzy model is used to expend the results of the digital redesign technique to nonlinear systems. The proposed method utilized the recently developed LMI technique to obtain a digitally redesigned fuzzy-model-based controller. The intelligent digital redesign problem is converted to equivalent problem, and the LMI method is used to find the digitally redesigned fuzzy-model-based controller. The stabilization conditions of TS fuzzy model are derived for stabilization in the sense of Laypunov stability. In order to demonstrates the effectiveness and feasibility of the proposed controller design methodology, we applied this method to the single link flexible-joint robot arm.