• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.12
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• pp.1903-1910
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• 2012

This paper presents a data based low-order controller design algorithm for a linear time-invariant process with a time delay. The algorithm is composed by combining an identification step based on open loop pulse test with a low-order controller design step to obtain the entire set of controllers achieving multiple performance specifications. The initial information necessary for this algorithm are merely the width and amplitude of a rectangular pulse, a controller of four types (PI, PD, PID, first-order), and design objectives. Various parametric approaches that have been developed are merged in the controller design algorithm. The resulting controller set satisfying the design objectives are displayed on the 2D and 3D graphics and thus it is very easy for us to pick a controller inside the admissible set because we can check the corresponding closed-loop performances visually.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.10
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• pp.1869-1875
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• 2008

Recently, a direct data-driven synthesis of a proportional integral derivative(PID) controller for a linear time-invariant(LTI) plant was presented in [1]. The authors showed that a complete set of PID controllers achieving robust performance and stability can be calculated directly from frequency response(FR) data without an identified transfer function model. However, it is not convenient to use this method because it requires complicated numerical algorithms to find specific frequencies which are solutions of an identical equation. The method also requires determination of the boundary of the controller's parameters from a finite set of FR data. In this paper, we present the development of a user-friendly Matlab toolbox based on the method in [1]. This toolbox allows us to obtain a complete three-dimensional(3-D) graphical solution of PID controllers that meet multiple design objectives. Several examples are given to demonstrate the use of the toolbox.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.922-927
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• 1991

This study is aimed to investigate a design problem of the fuzzy logic controller for the activated sludge process(ASP) in sewage treatment. The modeling technique proposed by Sugeno is used to express the ASP effectively and identification of a fuzzy model of the ASP is carried out utilizing actual operational data obtained from a metropolitan sewage plants. The model-based fuzzy controller is designed by rules generated from the identified ASP fuzzy model. Feasibility of the designed controller is tested through computer simulations.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.4
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• pp.275-279
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• 2011

In this paper, an observer-based sampled-data controller of linear system is proposed for the wave energy converter. Based on the sampled-data observer, the controller is design. In the closed-loop system with controller, it obtains the norm inequality between the continuous-time state variable and the discrete-time one. Using the norm inequality, sufficient condition is derived for the asymptotic stability of the closed-loop system and formulated in terms of linear matrix inequality. Finally, the wave energy converter simulation is provided to verify the effectiveness of the proposed technique.

• Proceedings of the KIEE Conference
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• 2004.10a
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• pp.182-184
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• 2004

This paper presents a PI controller tuning method for high performance permanent magnet synchronous motor (PMSM) drives under load variations using clustering fuzzy algorithm. In many speed tracking control systems PI controller has been used due to its simple structure and easy of design. PI controller, however, suffers from the electrical machine parameter variations and disturbances. In order to improve the tracking control performance under load variations, the PI controller parameters are modified during operation by clustering fuzzy method. This method based on optimal fuzzy logic system has simple structure and computational simplicity. It needs only sample data which is obtained by optimal controller off-line. As the sample data implemented in the adaptive fuzzy system can be modified or extended, a flexible control system can be obtained Simulation results show the usefulness of the proposed controller.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.2
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• pp.194-202
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• 1998

This paper describes a hardware implementation method of a Petri Net-based controller. A flexible and systematic implementation method, based on look-up tables, is suggested, which enables to build high speed Petri net-based controllers. The suggested method overcomes the inherent speed limit that arises from the microprocessors by using of matrix-based look-up tables. Based on the matrix framework, this paper suggests various specific data path structures as well as a basic data path structure, accompanied by evolution algorithms, for sub-class Petri nets. A new sub-class Petri net, named Biarced Petri Net, resolves memory explosion problem that usually comes with matrix-based look-up tables. The suggested matrix-based method based on the Biarced Petri net has as good efficiency and expendability as the list-based methods. This paper shows the usefulness of the suggested method, evaluating the size of the look-up tables and introducing an architecture of the signal processing unit of a programmable controller. The suggested implementation method is supported by an automatic design support program.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1168-1172
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• 2004

This paper presents a speed controller based on an adaptive fuzzy algorithm for high performance permanent magnet synchronous motor (PMSM) drives under parameter and load variations. In many speed tracking control systems PI controller has been used due to its simple structure and easy of design. PI controller, however, suffers from the electrical machine parameter variations and disturbances. In order to improve the tracking control performance under load variations, the PI controller parameters are modified during operation by adaptive fuzzy method. This method based on optimal fuzzy logic system has simple structure and computational simplicity. It needs only sample data which is obtained by optimal controller off-line. As the sample data implemented in the adaptive fuzzy system can be modified or extended, a flexible control system can be obtained. Simulation results show the usefulness of the proposed controller.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.345-347
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• 2006

In this paper, we study the robot controller design using the voice and data communication via CDMA(Code Division Multiple Access) mobile communication network. We design the robot remote controller using the three methods, telephone call speech recognition, DTMF (Dual Tone Multiple Frequency) realization, SMS(Short Message Service) transmission/reception way via CDMA mobile communication network. We investigate the validity and effectiveness of the proposed remote controller which applied to the mobile robot.

• Journal of Mechanical Science and Technology
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• v.17 no.12
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• pp.1855-1866
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• 2003

This paper discusses an entire procedure for a robust controller design and its implementation of an AMB (active magnetic bearing) spindle, which is part II of the papers presenting details of system modeling and robust control of an AMB spindle. Since there are various uncertainties in an AMB system and reliability is the most important factor for applications, robust control naturally gains attentions in this field. However, tight evaluations of various uncertainties based on experimental data and appropriate performance weightings for an AMB spindle are still ongoing research topics. In addition, there are few publications on experimental justification of a designed robust controller. In this paper, uncertainties for the AMB spindle are classified and described based on the measurement and identification results of part I, and an appropriate performance weighting scheme for the AMB spindle is developed. Then, a robust control is designed through the mixed ${\mu}$ synthesis based on the validated accurate nominal model of part I, and the robust controller is reduced considering its closed loop performance. The reduced robust controller is implemented and confirmed with measurements of closed-loop responses. The AMB spindle is operated up to 57,600 rpm and performance of the designed controller is compared with a benchmark PID controller through experiments. Experiments show that the robust controller offers higher stiffness and more efficient control of rigid modes than the benchmark PID controller.

• Proceedings of the KIEE Conference
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• 2003.07b
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• pp.1142-1144
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• 2003

This Paper presents a speed controller based on the adaptive fuzzy tuning method for brushless DC(BLDC) motor drives under load variations. Generally, the speed tracking control systems use PI controller due to its simple structure and easy of design. PI controller, however, suffers from the electrical machine parameter variations and disturbances. In order to improve the tracking control performance under load variations, PI controller of which the parameters are modified during operation by adaptive fuzzy tuning method. This method based on optimal fuzzy logic system has simple structure and computational simplicity. It needs only sample data which is obtained by optimal controller off-line. As the sample data implemented in the adaptive fuzzy system can be modified or extended, a flexible control system can be obtained. Simulation results show the usefulness of the proposed controller.