• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.957-966
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• 2023

In this paper, we propose a new real-time adaptive PID temperature control technique. This is a technique that prevents overshoot by introducing a model that represents the control object. To prevent excessive integration that causes overshoot, integral control adjusts the integral gain to track the heat loss of the model in real time. In the conventional PID control, the integration was dependent on proportional control and the gain was fixed to a constant. As a result, applying two gains that mismatch each other could cause excessive overshoot. However, the proposed adaptive control actively eliminates overshoot so that the integral control amount does not always exceed the heat loss. The cause of overshoot in PID control is integration. Basically, proportional control does not cause overshoot. Therefore, according to the proposed technique, adaptive PID control without the need for tuning experiments can be realized.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.99-100
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• 2016

드론이나 이동형 촬영장비에 장착된 카메라로부터 깨끗하고 안정된 영상을 획득하기 위해서는 짐벌시스템의 안정화기 설계가 필요하다. 짐벌시스템은 카메라 모듈을 지지하는 구조와 외부로 부터의 진동을 차단하면서 정확한 각도를 추종하는 안정화기로 구성된다. 이동형 촬영장비나, 비행중인 드론에는 매우 다양한 주파수 성분의 진동이 발생되는데, 이러한 진동을 제어하기 위하여 6자유도 운동방정식을 유도하고, 이 중에서 본 논문에서는 일반적으로 rolling, pitching, yawing 운동에 대해서는 PID 제어기를 사용하여 안정화를 제어하기만, 카메라종류나 짐벌시스템 구조가 바뀔 때 마다 PID 파라미터를 변경해야 되는 경우가 빈번하다. 본 논문에서는 이런 문제점을 개선하기 새로이 제기된 제어 기법인 지적 PID(intelligent PID) 제어를 통하여 진동제어를 수행하여 짐벌시스템의 안정화를 위한 제어기법을 제안하고자 한다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.5
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• pp.823-829
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• 2006

In this paper presents approaches to the design of a hybrid fuzzy logic proportional plus conventional integral- derivative(fuzzy P+ID) controller in an incremental form. This controller is constructed by using an incremental fuzzy logic controller in place of the proportional term in a conventional PID controller. The PID type controller has been widely used in industrial application due to its simply control structure, easy of design, and inexpensive cost. However, control performance of the PID type controller suffers greatly from high uncertainty and nonlinearity of the system, large disturbances and so on. This paper presents a hybrid fuzzy logic proportional plus conventional integral derivative controller In comparison with a conventional PID controller, only one additional parameter has to be adjusted to tune the Fuzzy P+ID controller. In this case, the stability of a system remains unchanged after the PID controller is replaced by the Fuzzy P+ID controller without modifying the original controller parameters. Finally, the proposed hybrid Fuzzy P+ID controller is applied to BLDC motor drive. Simulation results demonstrated that the control performance of the proposed controller is better than that of the conventional controller.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.12
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• pp.1917-1923
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• 2010

This study focuses on model identification and a 2-DOF PID control algorithm for cooling processes; a pneumatic butterfly-type control valve is used for this purpose. The mathematical model is a transfer function composed of a time delay and a second-order delay system. The control valve is identified as a first-order delay system with a time delay and included in the controlled plant. From the experimental data sets for a demo plant, the model parameters are identified, and the 2-DOF PID control gains are analytically derived by Kitamori's method. We show via a computer simulation and an experimental test that the performance of the proposed 2-DOF PID control system is better than that of a conventional 1-DOF PID control system.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.9 no.1
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• pp.63-66
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• 1995

PID controller is being used in many servo control system. However, when a control system has variable load, it is difficult to guarantee the accurate control of the system. In the way of solving this problem, in this paper, a auto-tuning method of PID controller parameter using fuzzy rule in variable load is presented. The parameter of PID controller are decided by fuzzy rule according to load variation. The accurate control function of fuzzy auto-tuning is demonstrated by simulation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.457-460
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• 2004

본 논문에서는 새로운 방법의 Fuzzy PID 제어기를 제안한다 우선 절대형 디지털 PID 제어기에서 두 가지 문제점이 있다. 첫째는 매 제어 주기마다 많은 데이터의 합을 구해야 하므로 계산시간이 많이 소요되고, 둘째는 이 계산을 위해 이전의 모든 데이터를 보관하고 있어야 되기 때문에 메모리가 많이 필요한 문제점이 있다. 위의 문제점을 개선하기 위해 속도형 디지털 PID 제어기를 사용한다. 제안한 제어기에서는 PIB 제어기의 목표 값과 현재 출력 값의 차인 크리스퍼(crisp) 출력 오차를 그대로 사용하지 않고 퍼지추론의 단계는 가지면서 Rule Table은 갖지 않는 특징이 있으며 출력 소속 함수에 두 변수의 관계와 범위에 의해 도식화된 영역에서 삼각형 무게 중심법으로 비퍼지화된 비선형 출력 값을 PID 계수에 인가하는 새로운 Fuzzy PID 제어기를 제안한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1495-1504
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• 2021

An ultra-compact binary power generation plant converts thermal energy into electric power using temperature difference between heat source and cooling source. In the actual power generation environment, the characteristic value of the plant changes due to any negative effects such as environmental condition or corrosion of related equipment. If the characteristic value of the plant changes, it may lead to unstable output of the turbine in a conventional PID control system with fixed PID parameters. A Neuro PID control system based on Neural Network adaptively to adjust the PID parameters according to the change in the characteristic value of the plant is proposed in this paper. Discrete-time transfer function models to represent the dynamic characteristics near the operating point of the investigated plant are deduced, and a design strategy of the proposed control system is described. The proposed Neuro PID control system is compared with the conventional PID control system, and its effectiveness is demonstrated through the simulation results.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.12 no.1
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• pp.111-116
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• 1998

Robust control for DC servo 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. As a compensation method solving this problem, in this paper, PID-neural network hybrid control method for motor control system is presented. The output of neural network controller is determined by error and rate of error change occurring in load disturbance. The robust control of DC servo motor using neural network controller is demonstrated by computer simula tion.a tion.

• Journal of Advanced Navigation Technology
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• v.26 no.2
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• pp.105-112
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• 2022

In this paper, unmanned underwater glider was designed for high-depth operation and adopted a bladder-type buoyancy controller for improving battery efficiency, and the motion controller controls the pitch angle by moving the internal mass battery. To improve the energy efficiency of the unmanned underwater glider, a layered PID controller that performs control by section was designed. Simulation program including 6-DOF motion equations and hydrodynamics coefficients of an unmanned underwater glider is constructed using Matlab/Simulink program. Control methods such as PID controller, sliding mode controller and layered PID controller were applied to the simulator to compare the dynamics performance and energy efficiency. As a result, the layered PID controller showed improved control performance compared to other controllers and improved energy efficiency of approximately 7.2% compared to PID controller.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.2
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• pp.70-78
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• 1997

Proportional-integral-derivative(P1D) controllers have been still widely used in industrial processes due to their simplicity, effectiveness, robustness for a wide range of operating conditions, and the familiarity of control engineers. And a number of recent papers in fuzzy systems are showing that fuzzy systems are universal approximators. That is, fuzzy controllers are capable of approximating any real continuous function on a compact set of arbitrary accuracy. In this paper, we derive the linear PID control law from the fuzzy control algorithm where all fuzzy sets for representing plant state variables and a control variable use common triangular types. We first lead a linear PD control law from a fuzzy logic control with only two fuzzy sets for error and change-of-error. And then we derive the linear PID control law from a fuzzy controller. We here assumed that the intervals of error, change-of-error, and integral error could be partitioned into arbitrary numbers, respectively. As a result, a linear PID controller is only a sort of various fuzzy logic controls.