• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.7
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• pp.1158-1168
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• 1994

A variable structure control scheme(VSCS) with sliding mode that can be applied to the process with input/output(I/O) delay is proposed and its control performances is evaluated. The proposed VSCS with and output feedback scheme comprises a variable structure controller, a servo dynamic for tracking the set-poing, and a Smith predictor for compensating the effects of time delay. The robustness against the parameter variations and external disturbances can be achieved by the proposed VSCS even when the controlled process includes I/O delay. And the desired transient response is obtained by simple adjustment of the coefficients of the switching surface equation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.3
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• pp.619-625
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• 2000

A many control techniques have been proposed in order to improve the control performance of the discrete-time domain control system. In the position control system, the output of a controller is generally used as the input of a plant but the undesired noise is included in the output of a controller. Therefore there is a need to used a precompensator for rejecting the undesired noise. In this paper, The expanded I-PD control system with a precompensator is constructed. The precompensator and I-PD controller are designed by a neural network and these coefficients are changed automatically to be a desired response of system when the response characteristic of system is changed under a condition.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.407-412
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• 1998

A design technique based on the root locus approach for the SISO (Single-Input Single-Output) systems using PID (Proportional-Integral-Derivative) ${\times}$ (n-1) stage PD as a controller for the n$\^$th/ order plant is presented. The controller is designed based on transient and steady state response specifications. This controller can be used instead of a conventional PID controller. The overall system is approximated as a stable and robust second order system. The desired performances are achieved by increase the gain of the controller. In addition, the controller gain can be adjusted to obtain faster response with a little overshoot. The simulation results show the merits of this approach.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.26 no.5
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• pp.71-78
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• 2012

This paper presents a digital control solution to process capacitor current feedback of high performance single-phase UPS for non-linear loads. In all UPS the goal is to maintain the desired output voltage waveform and RMS value over all unknown load conditions and transient response. The proposed UPS uses instantaneous load voltage and filter capacitor current feedback, which is based on the double regulation loop such as the outer voltage control loop and inner current control loop. The proposed DSP-based digital-controlled PWM inverter system has fast dynamic response and low total harmonic distortion (THD) for nonlinear load. The control system was implemented on a 32bit Floating-point DSP controller TMS320C32 and tested on a 5[KVA] IGBT based inverter switching at 11[Khz]. The validity of the proposed scheme is investigated through simulation and experimental results.

• The Magazine of the Society of Air-Conditioning and Refrigerating Engineers of Korea
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• v.17 no.4
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• pp.357-368
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• 1988

An application of thermal response coefficient method for obtaining thermal load on stud-frame walls in a typical house is presented. A set of stud-frame walls is two-dimensional heat conduction transients with composite structure. The ambient temperature on the right-hand face of the stud-frame walls is a typical day-cycle input and the room temperature on the left-hand face is a constant input. The desired output is thermal load at the left-hand face. The time-dependent ambient temperature is approximated by a continuous, piecewise-linear function each having one hour interval. The conduction problem is spatially discretized as 8 computer modelings by finite elements to obtain thermal response coefficients. The discretization and round-off errors can be neglected in the range of adequate number of nodes. A 60-node discretization is recommended as the optimum model among 8 computer modelings. Several sets of response coefficients of the stud-frame walls are generated by which the rate of heat transfer through the walls or some temperature in the walls can be calculated for different input histories.

• Proceedings of the KIPE Conference
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• 2005.07a
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• pp.134-136
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• 2005

The author present a modified multi-loop algorithm Including feedforward for controlling a 55kW stepdown chopper in the power supply of Maglev The gains of the control algorithm were selected based on pole locations formulated from a prototype Bessel transfer function model. The design incorporate tradeoffs in DC-to-DC converter hard-ware para-meters and pole locations. This perturvation is derived by subtracting the desired output voltage from the actual output voltage. The proportional and integral action stabilizes the system and minimizes output voltage error. In order to verify the validity of the proposed multi-loop controller, simulation study was tried using Matlab simulink.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.12
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• pp.575-583
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• 2001

It is hard to obtain good robust performance and robust stability for uncertain and time-varying system. The robust 2-DOF controller is frequently used to obtain the desired response and the good robustness. Two controllers can be independently designed. Generally, one controller reduces sensitivity to parameter variations, nonlinear effects, and other disturbances. On the other hand, the other controller reduces the error between the desired command and output. In this paper, the various robust perfect MFCs(model-following controllers) combined with TDC(Time Delay Control) are designed, and the imperfect stable MFC combined with TDC and SMC(Sliding Mode Control) is proposed. These controllers are based on the method of designing robust 2-DOF controllers for dynamic system with uncertainty. The performance of the proposed imperfect sable MFC has been evaluated through computer simulations. The simulation results indicate that the proposed controller shows the excellent performance characteristics for an overhead crane with uncertain and time-varying parameters.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2002.10a
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• pp.313-320
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• 2002

A new semi-active control strategy for seismic response reduction using a neuro-controller and a magnetorheological (MR) fluid damper is proposed. The proposed control system consists of the improved neuro-controller and the bang-bang-type controller. The improved neuro-controller, which was developed by employing the training algorithm based on a cost function and the sensitivity evaluation algorithm replacing an emulator neural network, produces the desired active control force, and then the bang-bang-type controller causes the MR fluid damper to generate the desired control force, so long as this force is dissipative. In numerical simulation, a three-story building structure is semi-actively controlled by the trained neural network under the historical earthquake records. The simulation results show that the proposed semi-active neuro-control algorithm is quite effective to reduce seismic responses. In addition, the semi-active control system using MR fluid dampers has many attractive features, such as the bounded-input, bounded-output stability and small energy requirements. The results of this investigation, therefore, indicate that the proposed semi-active neuro-control strategy using MR fluid dampers could be effectively used for control of seismically excited structures.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.1
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• pp.15-20
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• 2016

The existing multiple modulus-based self-recovering equalization type has not been applied to initial equalization. Instead, it was used for steady-state performance improvement. In this paper, for the self-recovering equalization type that considers the multiple modulus as a desired response, the initial convergence performance was improved by extending the dynamics of the errors using error boosting and their characteristics were analyzed. Error boosting in the proposed method was carried out in proportion to a symbol decision for the equalizer output. Furthermore, having the initial convergence capability by extending the dynamics of errors, it showed excellent performance in the initial convergence rate and steady-state error level. In particular, the proposed method can be applied to the entire process of equalization through a single algorithm; the existing methods of switching over or the selection of other operation modes, such as concurrent operating with other algorithms, are not necessary. The usefulness of the proposed method was verified by simulations performed under the channel conditions with multipath propagation and additional noise, and for performance analysis of self-recovering equalization for high-order signal constellations.

• Structural Engineering and Mechanics
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• v.83 no.3
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• pp.327-340
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• 2022

The Collapse Margin Ratio (CMR) is a notable index used for seismic assessment of the structures. As proposed by FEMA P695, a set of analyses including the Nonlinear Static Analysis (NSA), Incremental Dynamic Analysis (IDA), together with Fragility Analysis, which are typically time-taking and computationally unaffordable, need to be conducted, so that the CMR could be obtained. To address this issue and to achieve a quick and efficient method to estimate the CMR, the Artificial Neural Network (ANN), Response Surface Method (RSM), and Adaptive Neuro-Fuzzy Inference System (ANFIS) will be introduced in the current research. Accordingly, using the NSA results, an attempt was made to find a fast and efficient approach to derive the CMR. To this end, 5016 IDA analyses based on FEMA P695 methodology on 114 various Reinforced Concrete (RC) frames with 1 to 12 stories have been carried out. In this respect, five parameters have been used as the independent and desired inputs of the systems. On the other hand, the CMR is regarded as the output of the systems. Accordingly, a double hidden layer neural network with Levenberg-Marquardt training and learning algorithm was taken into account. Moreover, in the RSM approach, the quadratic system incorporating 20 parameters was implemented. Correspondingly, the Analysis of Variance (ANOVA) has been employed to discuss the results taken from the developed model. Additionally, the essential parameters and interactions are extracted, and input parameters are sorted according to their importance. Moreover, the ANFIS using Takagi-Sugeno fuzzy system was employed. Finally, all methods were compared, and the effective parameters and associated relationships were extracted. In contrast to the other approaches, the ANFIS provided the best efficiency and high accuracy with the minimum desired errors. Comparatively, it was obtained that the ANN method is more effective than the RSM and has a higher regression coefficient and lower statistical errors.