• Journal of the Semiconductor & Display Technology
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• v.1 no.1
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• pp.21-28
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• 2002

This paper presents a dynamic modeling and a robust PID controller design process for the wire bonder head assembly. For modeling elements, the system is divided into electrical part, magnetic part, and mechanical part. Each part is modeled using the bond graph method. The PID controller is used for high speed/high accuracy position control of the wire bonder assembly. The Taguchi method is used to obtain the more robust PID gain combinations than conventional one. This study makes use of an L18 array with three parameters varied on three levels. Results of simulations and experimental show that the designed PID controller provides a improved ratio of signal to noise and a reduced sensitivity improved to the conventional PID controller.

• Journal of the Korea Institute of Military Science and Technology
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• v.3 no.2
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• pp.71-80
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• 2000

In Underwater Flight Vehicle depth control system, the followings must be required. Firstly, It need robust depth control performance which can get over parameter variation, modeling error and disturbance. Secondly, It need no oveshoot phenomenon to avoid colliding with ground surface and obstables. Thirdly, It need continuous control input to reduce the acoustic noise and propulsion energy consumption. Finally, It need effective interpolation method which can reduce the dependency of control parameters on speed. To solve these problems, we propose the Fuzzy-PID depth controller with the control parameter interpolators. Simulation results show the proposed control scheme has robust and accurate performance with continuous control input.

• Journal of information and communication convergence engineering
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• v.2 no.1
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• pp.46-51
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• 2004

The problem of reducing the effect of an unknown disturbance on a dynamical system is one of the most fundamental issues in control design. We propose a robust PID (Proportional Integral Derivative) control method with neural network for improving the performance due to the rejection of an unknown disturbance. The proposed system consists of a model of the plant, a conventional PID controller and a multi-layer neural network, and is composed of two loop; the first loop enables the system to achieve stability of system, the second loop rejects an unknown disturbance. Simulation and experiment results show that the proposed method improves considerably on the performance of the conventional PID control method and the typical IMC method using neural network.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.113-118
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• 2007

In this paper, a new method is proposed for robust proportional- integral - derivative (PID) control that is to ensure specified phase margin and iso - damping property using reduction model. This method is based on the second order plus dead time(SOPDT) reduction model of the high order model. Reduction model used to ensure iso-damping property in the feature frequency. Simulation results gives proof of effectiveness of proposed method.

• Journal of Advanced Marine Engineering and Technology
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• v.26 no.4
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• pp.415-424
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• 2002

In this paper, a robust fuzzy precompensated PID controller using immune algorithm for load frequency control of 2-area power system is proposed. Here, a fuzzy precompensated PID controller is designed as a fuzzy logic based precompensation approach for PID controller. This scheme is easily implemented by adding a fuzzy precompensator to an existing PID controller. We optimize the fuzzy precompensator with an immune algorithm for complementing the demerit such as the difficulty of the component selection of fuzzy controller, namely, scaling factor, membership function and fuzzy rules. Simulation results show that the proposed robust load frequency controller can achieve good performance even in the presence of generation rate constraints.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.1
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• pp.85-89
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• 2004

Robust control for feedback control system is needed according to the highest precision of industrial automation. However, when a neural network feedback control system has an effect of disturbance, it is very difficult to guarantee the robustness of control system. As a compensation method solving this problem, in this paper, hybrid control method of neural network controller and PID controller is presented. A neural network controller is operated as a main controller, a PID controller is a assistant controller which operates only when some undesirable phenomena occur, e.q., when the error hit the boundary of constraint set. The robust control function of neural network-PID hybrid controller is demonstrated by speed control of Motor.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.6
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• pp.1560-1564
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• 2008

Robust control for DC motor is needed according to the highest precision of industrial automation. However, when a motor control system with PID controller has an effect of load disturbance, it is very difficult to guarantee the robustness of control system. In this paper, PID-Self Tuning control method for motor control system as a compensation method solving this problem is presented. If the PID control system is stable in the sense that the error is inside the constraint set, the supervisory control is idle. If the error hits the boundary of the constraint, the supervisory controller begins operation to force the error back to the constraint set. We prove that the PID-Self Tuning control system is globally stable in the sense that the error is guaranteed to be within the tolerance limits specified by the system designer.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2799-2801
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• 2000

Robust control for DC motor is needed according to the highest precision of industrial automation. However, when a motor control system with PID controller has an effect of load disturbance, it is very difficult to guarantee the robustness of control system. In this paper, PID-Expert hybrid control method for motor control system as a compensation method solving this problem is presented. If PID control system is stable, the Expert controller is idle. if the error hits the boundary of the constraint. the Expert controller begins operation to force the error back to the constraint set. The disturbance effect decrease remarkably, robust speed control of DC motor using PID-Expert Hybrid controller is demonstrated by the simulation.

• Journal of IKEEE
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• v.27 no.4
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• pp.391-398
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• 2023

In this paper, we propose an alternative analysis to regulate DC motors using a PID controller with a gain scaling factor. We start by providing a systematic design method for selecting the PID gains of our proposed controller by seeing the effect of ϵ on damping ratio, overshoot and settling time from the frequency response analysis. With the help of matlab (simulink), We proceed to show that the proposed controller provides robust stability against system parameter uncertainty and the effect of the gain scaling factor on steady-state error. The validity of our control method along with the analysis is verified with the simulation results.

• Proceedings of the KAIS Fall Conference
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• 2008.05a
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• pp.192-195
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• 2008

Robust control for DC motor is needed according to the highest precision of industrial automation. However, when a motor control system with PID controller has an effect of load disturbance, it is very difficult to guarantee the robustness of control system. In this paper, PID-Expert hybrid control method for motor control system as a compensation method solving this problem is presented. If PID control system is stable, the Expert controller is idle. if the error hits the boundary of the constraint, the Expert controller begins operation to force the error back to the constraint set. The disturbance effect decrease remarkably, robust speed control of DC motor using PID-Expert Hybrid controller is demonstrated by the simulation.