• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.213-217
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• 2008

In this paper, a new design method for IMC-PID that adds a phase scaling factor of system identifications to the standard IMC-PID controller as a control parameter is proposed. Based on analytically derived frequency properties such as gain, phase margin and maximum magnitude of sensitivity function, this tuning rule is an optimal control method determining the optimum values of controlling factors to minimize the cost function, integral error criterion of the step response in time domain, in the constraints of design parameters to guarantee qualified frequency design specifications. The proposed controller improves existing single-parameter design methods of IMC-PID in the inflexibility problem to be able to consider various design specifications. Its effectiveness is examined by a simulation example, where a comparison of the performances obtained with the proposed tuning rule and with other common tuning rules is shown.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1539-1544
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• 2005

The gauge control of the fishing mill is very important because more and more accurately sized hot rolled coils are demanded by customers recently. Because the mill constant and the plasticity coefficient vary with the specifications of the mill, the classification of steel, the strip width, the strip thickness and the slab temperature, the variation of these parameters should be considered in the automatic gauge control system(AGC). Generally, the AGC gain is used to minimize the effect of the uncertain parameters. In a practical field, operators set the AGC gain as a constant value calculated by FSU (Finishing-mill Set-Up model) and it is not changed during the operating time. In this paper, the thickness data signals that occupy different frequency bands are respectively extracted by adaptive filters and then the main cause of the thickness variation is analyzed. Additionally, the AGC gain is adaptively tuned to reduce this variation using the online tuning model. Especially ANFIS(Adaptive-Neuro-based Fuzzy Interface System) which unifies both fuzzy logics and neural networks, is used for this gain adjustment system because fuzzy logics use the professionals' experiences about the uncertainty and the nonlinearity of the system. Simulation is performed by using POSCO's data and the results show that proposed on-line gain adjustment algorithm has a good performance.

• Proceedings of the KIEE Conference
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• 1994.11a
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• pp.338-341
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• 1994

This paper presents a Fuzzy-PID controller based on Fuzzy logic. Up to now PID controller has had the difficulty of obtaining the optimal gain, and Fuzzy controller has had the difficulty of determining scale factor affecting the performance of control. So that a Fuzzy-PID controller is presented here self tuning of the scale factor and optimal gain. The results of simulation show a good performance in comparison with Ziegler-Nichols controller, having the generality of determining the components of scale factor in Fuzzy rule.

• Proceedings of the KIEE Conference
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• 2002.07b
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• pp.1137-1139
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• 2002

In this paper, recurrent artificial neural network (RNN) based self tuning speed controller is proposed for the high performance drives of induction motor. RNN provides a nonlinear modeling of motor drive system and could give the information of the load variation, system noise and parameter variation of induction motor to the controller through the on-line estimated weights of corresponding RNN. Thus, proposed self tuning controller can change gains of the controller according to system conditions. The gain is composed with the weights of RNN. For the on-line estimation of the weights of RNN, extended kalman filter (EKF) algorithm is used. Self tuning controller that is adequate for the speed control of induction motor is designed. The availability of the proposed controller is verified through the MATLAB simulation with the comparison of conventional PI controller.

• Proceedings of the KIPE Conference
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• 2007.07a
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• pp.98-100
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• 2007

This paper proposes a robust digital controller for PWM voltage source inverter using CRA method. The usual inverter controller for the operation of constant voltage and constant frequency consists of a double looped PI controller for the outer voltage controller and the inner current controller, of which the order of characteristic polynomial is high and so the gain tuning is difficult. Considering the limited switching frequency of the devices and sampling frequency of the digital controller, the gain tuning is usually based on the engineering experiences with the try and error method. In this paper, the error-space approach is used to get the system model including the controller with low order, and the characteristic ratio assignment (CRA) method is proposed for the design of robust controller which has the advantage to design the optimal gain to meet the referenced response and overshoot within the limit range. The PSiM simulation and experience results are shown to verify the validity of the proposed controller.

• The Transactions of the Korean Institute of Power Electronics
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• v.22 no.1
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• pp.1-8
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• 2017

The optimal gain design method of a three-phase boost converter is proposed in this study. The control system has a two-loop configuration, in which each controller is coupled closely; thus, the optimal design is difficult to achieve using conventional gain-tuning method. The proposed method is adopted to the MATLAB SISO TOOL software and is based on the controller requirements, which are phase margin and cut-off frequency of the open-loop system. The optimal proportional -integral gains can be designed easily using the proposed interactive method of the SISO TOOL. The performance of the proposed system is verified through simulation and experiments.

• The Transactions of the Korean Institute of Power Electronics
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• v.16 no.5
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• pp.503-510
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• 2011

This paper presents a method of optimizing the blade pitch and generator torque controllers which have been already designed for an existing wind turbine generator system. Since the highly nonlinear and uncertain characteristics of the wind turbine generator can not be fully considered in the controller design phase, some parameters such as control gains must be tuned during the field implementation phase. In this paper, nonlinear simulation software, which is based high fidelity wind turbine model, and optimization technique are effectively combined and used to tune a set of gains for the blade pitch and the generator torque controllers. Simulation results show that the baseline controllers can be effectively optimized to reduce the errors in wind turbine rotor speed and generator power output controls as well as twisting of the high and low speed shafts.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.4
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• pp.509-518
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• 2014

Though various techniques have been studied as a way of adjusting parameters of PID controllers, no perfect method of determining parameters is available to date. Especially the deign of PID controller for unstable processes with dead time(UPWDT) is even more difficult due to various reasons. Generally the existing design procedures for UPWDT involve deriving formulas to meet gain and phase margin specifications, or using inner loop to stabilize UPWDT before applying PID controller. In this paper, the dual-input describing function(DIDF) method is proposed, by which the performance and robustness of the closed-loop system can be improved. The method is based on moving the critical point (-1+j0) of Nyquist stability to a new position arbitrarily selected on the complex plane. This can be done by determining appropriate coefficients of the DIDF. As a result, we can easily determine parameters of PID-type controller by using existing conventional tuning methods for stable or unstable systems. Simulation results are included to show the effectiveness of the proposed method.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.8
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• pp.15-23
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• 1992

Neural network control has many innovative potentials for fast, accurate and intelligent adaptive control. In this paper, two kinds of neurocontrol architectures for the dynamic control of robot manipulators are developed. One is based on a System Identification and Control scheme and the other is based on the Feedback-Error leaming scheme. Both of the proposed architectures use an inverse dynamic neurocontroller in parallel with a linear neurocontroller. The difference is that the first architecture uses the system identifier to get the signals used for training neurocontrollers, while the second architecture uses a properly defined energy function. Compared with the previous types of neurocontrollers which are using an inverse dynamic neurocontroller and a fixed PD gain controller, the proposed architectures not only eliminate the painful process of the fixed gain tuning but also exhibit superior peformances because the linear neurocontroller can adapt its gains according to the applied task. This superior performance is tested and verified through computer simulation of the dynamic control of the PUMA 560 arm.

• Journal of Power Electronics
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• v.17 no.2
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• pp.464-475
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• 2017

This study examines a P+multi resonant-based voltage control for voltage harmonics compensation under the islanded mode of a microgrid. In islanded mode, the inverter is defined as a voltage source to supply the full local load demand without the connection to the grid. On the other hand, the output voltage waveform is distorted by the negative and zero sequence components and current harmonics due to the unbalanced and nonlinear loads. In this paper, the P+multi resonant controller is used to compensate for the voltage harmonics. The gain tuning method is assessed by the tendency analysis of the controller as the variation of gain. In addition, this study analyzes the slight voltage magnitude drop due to the practical form of the P+multi resonant and proposes a counter method to solve this problem by adding the PI-based voltage restoration method. The proposed P+multi resonant controller to compensate for the voltage harmonics is verified through the PSIM simulation and experimental results.