• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.105-108
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• 2000

Many control techniques have been proposed in order to improve the control performance of discrete-time domain control system. In the position control system using a DC servo motor as a driver, the response-characteristic of system is controlled by the PID controller. In the PID control system, the transient response characteristic is more increased and settling time gets longer if gains of PID controller are unsuitable. In this paper, therefore, a expended PID control system is constructed by inserting a pre-compensator at output terminal of PID controller. It is implemented by using the double layers neural network. Form the results of computer simulation in the proposed control algorithm, its usefulness is verified.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.40 no.1
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• pp.1-10
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• 2003

This paper is concerned with the fuzzy control scheme and PID controller for the vibration suppression control of a cantilever beam equipped with a laser sensor and an electromagnetic actuator. The PID controller is being widely used in industrial applications. However, it is difficult to determine the appropriate PID gains in nonlinear systems and systems with time variant characteristic and so on. In this paper, we design the fuzzy based PID controller of which output gains are adjusted automatically and the designed controller is applied to active vibration control of a cantilever beam using electromagnetic actuator with strong nonlinearity. The tuning PID parameters of proposed controller are determined by using Fuzzy algorithm. Effectiveness and performance of the designed controller are verified by both simulation and experiment results. Experimental results demonstrate that better control performance can be achieved in comparison with the PID cotroller.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.12 no.4
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• pp.70-74
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• 1998

Robust control for DC motor is needed according to the highest precision of industrial automation. However, when a motor control system with PID contoller has an effect of load disturbance, it is very difficult to guarantee the robustness of control system. In this paper, PID-supervision hybrid control methods for motor control system (without the supervisory controller) 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 beings operation to force the error back to the constraint set. We prove that the PID-supervision hybrid control system is globally stable in the sense that the error is guaranteed to be within the tolerance limits specified by the system designer.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.62-62
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• 2000

An auto-tuning PID controller which is adequate for temperature control is developed based on relay-control and pole-placement Using the critical frequency which is obtained from relay-control parameters of assumed model are identified. Pole/zero-placement PID controller is designed for the identified model. The desired pole/zeros are determined so that the closed-loop has overshoot free step response. The developed auto-tuning PID controller was successfully applied to the temperature control of RTP.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1371-1376
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• 2003

In the thermal power plant, the main steam temperature is typically regulated by the fuel flow rate and the spray flow rate, and the reheater steam temperature is regulated by the gas recirculation flow rate. However, Strictly maintaining the steam temperature can be difficult due to heating value variation to the fuel source, time delay changes in the main steam temperature, the change of the dynamic characteristics in the reheater. Up to the present time, PID Controller has been used to operate this system. However, it is very difficult to achieve an optimal PID gain with no experience, since the gain of the PID controller has to be manually tuned by trial and error. This paper focuses on tuning of the 2-DOF PID Controller on the DCS for steam temperature control using immune based multiobjective approach. The stable range of a 2-DOF parameter for only this system could be found for the start-up procedure and this parameter could be used for the tuning problem. Therefore tuning technique of multiobjective based on immune network algorithms in this paper can be used effectively in tuning 2-DOF PID controllers.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.901-904
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• 1998

In this paper, we describes PID-neural network controller for the rotary inverted pendulum. PID control is applied to many fields but has some problems in nonlinear system due to a variation of parameter. So, we should desing the controller which is adjusted PI parameters by the neural network which is learned by backpropagation algorithm. And we show that on-line control is possible through the PID-neural network controller. The angle of the pendulum is controlled and then the position of the rotating arm is also controlled to maintain with in the set point. Measurement of the pendulum angle is obtained using a potentionmeter. The objective of the experiment is to design a PID-neural network control system that positions the arm as well as maintains the ivnerted pendulum vertical. Finally, we describe the actual experiment system and confirm the experimental results.

• Journal of Drive and Control
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• v.14 no.4
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• pp.23-28
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• 2017

Time-delay control with internal model (TDCIM) is the controller for robot manipulators that applies the time-delay estimation and the concept of internal model control (IMC). TDCIM is robust against unknown dynamics and non-linear friction like coulomb friction and static friction. It is simple and computationally efficient. This study presents the relationship between the discrete TDCIM and the discrete PID controller. The PID controller is the most popular control law in the real application. But often the PID controller can be difficult to achieve the desired level of control performance. The result in this study provides a good candidate solution to these situations.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.3
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• pp.518-526
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• 2008

The fuzzy self-tuning PID controller is a PID controller with a fuzzy logic mechanism for tuning its gains on-line. In this structure, the proportional, integral and derivative gains are tuned on-line with respect to the change of the output of system under control. This paper deals with two types of fuzzy self-tuning PID controllers, rule-based fuzzy PID controller and learning fuzzy PID controller. As a medical application of fuzzy PID controller, the proposed controllers were implemented and evaluated in a laparoscopic surgery robot system. The proposed fuzzy PID structures maintain similar performance as conventional PID controller, and enhance the position tracking performance over wide range of varying input. For precise approximation, the fuzzy PID controller was realized using the linear reasoning method, a type of product-sum-gravity method. The proposed controllers were compared with conventional PID controller without fuzzy gain tuning and was proved to have better performance in the experiment.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.51 no.4
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• pp.187-194
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• 2002

Recently, the application of the linear machine far industrial field is remarkable increased, especially for the gantry machine, machine tool system and CNC. In these application fields, high dynamics position control performance Is essentially required in both the steady and the transient state. This pacer presents simple but powerful position control loop based on traditional PID controller. The presented position control algorithm, named 'Unified PID Position Controller'has great features for the linear machine drives such as no over-shoot phenomena and simple gain tuning strategy. Through the experimental results with commercial linear motors, it is shown that the proposed algorithm has excellent dynamics suitable fur linear motions.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.2 s.245
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• pp.105-111
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• 2006

This paper describes a Neural Network based PID control scheme for pneumatic NC axes. Pneumatic systems have inherent nonlinearities such as compressibility of air and nonlinear frictions present in cylinder. The conventional PID controller is limited in some applications where the affection of nonlinear factor is dominant. A self-excited oscillation method is applied to derive the dynamic design parameters of linear model. The gains of PID controller are determined using a self tuning scheme. The experiments of a trajectory tracking control using the proposed control scheme are performed and a significant reduction in tracking error is achieved by comparing with those of a PID control.