• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.2
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• pp.146-156
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• 2003

Nonlinear dynamic system exist widely in many types of systems such as chemical processes, biomedical processes, and the main steam temperature control system of the thermal power plant. Up to the present time, PID Controllers have been used to operate these systems. However, it is very difficult to achieve an optimal PID gain with no experience, because of the interaction between loops and gain of the PID controller has to be manually tuned by trial and error. This paper suggests control approaches by immune fuzzy for the nonlinear control system inverted pendulum, through computer simulation. This paper defines relationship state variables $x,\dot{x},{\theta},\dot{\theta}$ using immune fuzzy and applied its results to stability.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.186-189
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• 2005

In a clinical setting, developing a reliable method for the automated drug infusion system would improve a drug therapy under the unexpected and acute changes of hemodynamics. The conventional proportional-integral-derivative (PID) controller might not be able to achieve maximum performance because of the unexpected change of the intra- and inter-patient variability. The fuzzy PID control and the conventional PID control were tested under the unexpected response of mean arterial blood pressure (MAP) to a vasopressor agent during acute hypotension. Compared with the conventional PID control, the fuzzy PID control performed the robust MAP regulation regardless of the unexpected MAP response (average absolute value of the error between target value and actual MAP: 0.98 vs. 2.93 mmHg in twice response of the expected MAP and 2.59 vs. 9.75 mmHg in three-times response of the expected MAP). The result was due to the adaptive change of the proportional gain in PID parameters.

• Journal of the Korea Convergence Society
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• v.11 no.11
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• pp.195-201
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• 2020

This paper implemented quadcopter-type drone system and proposed the heuristic method for obtaining the optimum gain coefficients in order to minimize the settling time. Control system for quadcopter posture stabilization reads the posture data from accelerator and gyro sensor, revises the original posture data using Mahony filter, and drives 4 DC motors using PID controller. The first step of the proposed method is to obtain the gain coefficients using the Ziegler-Nichols method, and then determine the optimum gain coefficients using the heuristic method at the next 3 steps. The experimental result shows that the maximum overshoot decreases from 44.3 to 29.8 degrees and the settling time decreases from 2.6 to 1.7 seconds compared to the Ziegler-Nichols method. Therefore, we proved that the proposed method works well in quadcopter flight system with high motor noise while reducing trial and error to obtain the optimal PID gain coefficients.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.45.1-45
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• 2001

This paper proposes a Mamdani fuzzy PID controller for controlling a process with small dead time. The controller composes of a parallel structure of fuzzy PI controller and fuzzy PD controller. Each controller has two inputs, error and change of error. Hence, the control signal of the proposed controller is the average value of the output of the fuzzy PI and PD controllers. The Mamdani fuzzy PID controller is easily to be adjusted to meet the desired control system performances both in transient state and steady state. The simulation results of the proposed Mamdani fuzzy PID controller by using the same parameters (proportional gain, integral time and derivative time) as the conventional PID controller are shown. The response of the Mamdani fuzzy PID control system is faster than the conventional PID control system. Both system responses have ...

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.2
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• pp.1-7
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• 2007

Active magnetic bearing has been adopted to support the rotor by electomagnetic force without mechanical contact and lubrication process. A property of the control system for magnetic bearing is improved in accordance with making higher system gain. If the control system has integral part, an excessive overshoot response is shown by making higher integral gain. Therefore, this paper suggests a PID control system in order to eliminate the overshoot at the first stage and improve response characteristics to an impact disturbance at the status of levitation. The control gain was obtained by LQR design method which has the structure of I-PD control system in the state space. The PID control system containing prefilter has the same structure as the I-PD control system. Therefore, the PID control system adopted is able to be tuned by LQR design method. Finally, this paper shows the effect of the prefilter on the active magnetic bearing system through response experiments for levitation responses.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.1
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• pp.70-78
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• 2004

This paper proposes non-linear control method using immune algorithm based fuzzy logic. Nonlinear dynamic system exist widely in many types of systems such as chemical processes, biomedical processes, and the main steam temperature control system of the thermal power plant. Up to the present time, PID Controllers have been used to operate these systems. However, it is very difficult to achieve an optimal PID gain with no experience, because gain of the PID controller has to be manually tuned by trial and error. An inverted pendulum control problem is selected to illustrate the efficiency of the proposed method and defines relationship state variables $\chi$, $\chi$, $\theta$, $\theta$ using immune fuzzy.

• International Journal of Aeronautical and Space Sciences
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• v.5 no.1
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• pp.30-38
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• 2004

This paper deals with a problem of automatic landing guidance and control ofthe longitudinal airplane motion under the wind shear turbulence. Adaptive gainscheduled PID control law is proposed in this paper. Fuzzy logic is the main part ofthe adaptive PID controller as gain scheduler. To illustrate the successful applicationof the proposed control law to the automatic landing control problem, numericalsimulation is carried out based on the longitudinal nonlinear airplane model excited bythe wind shear turbulence. The simulation results show that the automatic landingmaneuver is successfully achieved with the satisfactory performance and the gainadaptation of the control law is made adequately within the limited gains.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.3
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• pp.114-119
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• 2001

An automatic train operation(ATO) system executes the operation of constant speed travelling and fixed point parking by using microprocessors instead of driver's manual operation. This paper describes the mathematical model for the train considering unknown disturbances which consist of start resistance, travelling resistance, slope resistance, curve resistance, and so on. The speed controller of ATO system is designed by considering the disturbances. The simulation is executed to verify the speed control and fixed point parking performance and to compare its performance with that of a PID-type ATO control system under disturbances. Simulation results show that the control performance of gain scheduled control scheme for ATO system is better than that of the conventional PID controller.

• Proceedings of the KIEE Conference
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• 1999.07f
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• pp.2610-2612
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• 1999

In controlling vector of induction motor, PID controller is required much time as the expert should control manually a gain of controller according to plant or a change of circumstances. Accordingly, this paper has gotten a gain of PID controller used neural network by self-funning method in order to settle above problem. The neural network can describe an input/output features in spite of non-linear system which is hard to get mathematical model by controlling the strength of connection by learning. It has a strong character against a distortion and noise of input information, and is suitable modeling of diver-variable system which is composed of several input/output. This paper has represented the self-tunning method for gain of PID controller used neural network when using PID controller to control speed of induction motor, and has checked strong characters against distortion and noise of input information through simulation.

• Journal of the Semiconductor & Display Technology
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• v.21 no.4
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• pp.59-64
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• 2022

Vibration is one of the factors that degrades the performance of equipment and measurement equipment used in high-tech industries such as semiconductors and display. The vibration isolator is classified into passive type and active type. The passive vibration isolator has the weakness of insufficient vibration isolation performance in the low frequency band, so an active vibration control system that can overcome these problems is used recently. In this paper, PID controller is used to control the active vibration isolator. Methods for setting the gain of the PID controller include the Zeigler-Nichols method, the pole placement method. These methods have the disadvantage of requiring a lot of time or knowing the system model accurately. This paper proposes the gain auto tuning method of the active vibration isolator applied with the PSO algorithm, which is an optimization algorithm that is easy to implement and has stable convergence performance with low calculations. It is expected that it will be possible to improve vibration isolation performance and reduce the time required for gain tuning by applying the proposed PSO algorithm to the active vibration isolator.