• 소음진동
• /
• 제8권3호
• /
• pp.441-449
• /
• 1998

A self-tuning control scheme, incorporated with the simplified 1st-order ARMAX(Auto-Regressive Moving Average eXogenous) model, for single rod hydraulic cylinder which has varying dynamic characteristics is presented here. An adaptive controller is developed for the system that uses feedforward and optimal feedback control for simultaneous parameter identification and tracking control. Through experimental results, the performance comparison of the self-tuning controller with a fixed gain proportional controller clearly shows its superior ability in handling load changes in quiescent states.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
• /
• pp.229-229
• /
• 2000

Conventional gain-tuning methods such as Ziegler-Nickels methods, have many disadvantages that optimal control ler gain should be tuned manually. In this paper, modified PID controllers which include self-tuning characteristics are proposed. Proposed controllers automatically tune the PID gains in on-1ine using neural networks. A new learning scheme was proposed for improving learning speed in neural networks and satisfying the real time condition. In this paper, using a nonlinear mapping capability of neural networks, we derive a tuning method of PID controller based on a Back propagation(BP)method of multilayered neural networks. Simulated and experimental results show that the proposed method can give the appropriate parameters of PID controller when it is implemented to DC Motor.

• 한국철도학회:학술대회논문집
• /
• 한국철도학회 2011년도 정기총회 및 추계학술대회 논문집
• /
• pp.2609-2614
• /
• 2011

A proportional integral derivative (PID) controller is designed and applied to a magnetic levitation conveyor system to control the levitation gap length of the electromagnet constantly. The PID gain parameters are optimized by response surface methods (RSM). The controller is verified with the state-space model of electromagnetic suspension by MATLAB/SIMULINK program. And, the controller and the state-space model are also verified experimentally. Simulation and experimental results shows the effectiveness of the PID gain tuning by RSM as compared with the classical PID tuning.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제1권1호
• /
• pp.95-103
• /
• 2001

The purpose of Introducing a combined cycle with gas turbine in power plants is to reduce losses of energy, by effectively using exhaust gases from the gas turbine to produce additional electricity or process. The efficiency of a combined power plant with the gas turbine increases, exceeding 50%, while the efficiency of traditional steam turbine plants is approximately 35% to 40%. Up to the present time, the PID controller has been used to operate this system. However, it is very difficult to achieve an optimal PID gain without any experience, since the gain of the PID controller has to be manually tuned by trial and error procedures. This paper focuses on the neural network tuning of the 2-DOF PID controller with a combined 2-DOF parameter (NN-Tuning 2-DOF PID controller), for optimal control of the Gun-san gas turbine generating plant in Seoul, Korea. In order to attain optimal control, transfer function and operating data from start-up, running, and stop procedures of the Gun-san gas turbine have been acquired and a designed controller has been applied to this system. The results of the NN-Tuning 2-DOF PID are compared with the PID controller and the conventional 2-DOF PID controller tuned by the Ziegler-Nichols method through experimentation. The experimental results of the NN-Tuning 2-DOF PID controller represent a more satisfactory response than those of the previously-mentioned two controllers.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2001년도 하계학술대회 논문집 D
• /
• pp.2123-2125
• /
• 2001

In thermal power plant, the efficiency of a combined power plant with a gas turbine increases, exceeding 50%, while the efficiency of traditional steam turbine plants is approximately 35% to 40%. Up to the present time, the PID controller has been used to operate this system. However, it is very difficult to achieve an optimal PID gain without any experience, since the gain of the PID controller has to be manually tuned by trial and error procedures. This paper focuses on the neural network tuning of the 2-DOF PID controller with a separated 2-DOF parameter (NN-Tuning 2-DOF PID controller), for optimal control of the Gun-san gas turbine generating plant in Seoul. Korea. In order to attain optimal control, transfer function and operating data from start-up, running, and stop procedures of the Gun-san gas turbine have been acquired, and a designed controller has been applied to this system. The results of the NN-Tuning 2-DOF PID are compared with the PID controller and the conventional 2-DOF PID controller tuned by the Ziegler-Nichols method through experimentation. The experimental results of the NN-Tuning 2-DOF PID controller represent a more satisfactory response than those of the previously-mentioned two controller.

• 전자공학회논문지S
• /
• 제35S권12호
• /
• pp.36-45
• /
• 1998

본 논문은 브러시리스 직류 전동기의 속도제어를 위해 파라메타의 추정 없이 입력과 출력의 패턴을 관찰하여 PI 이득을 온라인(On-line)으로 설정하는 방법을 제안한다. 비례이득은 한계입력을 인가하여 가장 빠른 속도 상승을 유도하는 과정에서 설정되고, 적분이득은 비례제어 과정 중에 오버슈트 방지와 안정된 수렴이 적절히 이루어지도록 설정된다. 따라서 제안된 PI이득 조정은 온라인으로 제어와 동시에 수행됨으로써 시스템 파라메타 추정 등의 부가적인 작업이 필요 없다. 본 논문에서 제안하는 PI이득 조절기법은 직류전동기의 속도제어에 있어서 빠른 응답과 오버슈트 문제를 동시에 해결할 수 있고, 기존의 Auto-tuning 방법보다 간편하고 실용적이다. 컴퓨터 시뮬레이션과 실제 실험을 통하여 제안하는 방법의 유용성과 안정성을 보인다.

• 한국정밀공학회지
• /
• 제14권12호
• /
• pp.174-181
• /
• 1997

A proposed hybrid self-tuning control scheme for single rod hydraulic cylinder which has varying loads is presented here. An adaptive controller is developed for the system that use feedforward and P feedback control for simultaneous parameter identification and tracking control. Through experimental results, the performance comparison of the hybrid self-tuning controller with a constant gain P contro- ller clearly shows its superior ability in handling load changes in quiescent states.

• Journal of Power Electronics
• /
• 제14권5호
• /
• pp.980-988
• /
• 2014

This paper proposes an online gain tuning algorithm for a robust sliding mode speed controller of surface-mounted permanent magnet synchronous motor (SPMSM) drives. The proposed controller is constructed by a fuzzy neural network control (FNNC) term and a sliding mode control (SMC) term. Based on a fuzzy neural network, the first term is designed to approximate the nonlinear factors while the second term is used to stabilize the system dynamics by employing an online tuning rule. Therefore, unlike conventional speed controllers, the proposed control scheme does not require any knowledge of the system parameters. As a result, it is very robust to system parameter variations. The stability evaluation of the proposed control system is fully described based on the Lyapunov theory and related lemmas. For comparison purposes, a conventional sliding mode control (SMC) scheme is also tested under the same conditions as the proposed control method. It can be seen from the experimental results that the proposed SMC scheme exhibits better control performance (i.e., faster and more robust dynamic behavior, and a smaller steady-state error) than the conventional SMC method.

• 전력전자학회:학술대회논문집
• /
• 전력전자학회 2002년도 추계학술대회 논문집
• /
• pp.40-44
• /
• 2002

In this paper, robust control method using fuzzy PI parameter tuning is proposed to control constant thrust force on load variation. First, a structure and thrust force equations of the LPM are described. Second, an controller with PI parameter-tuning using a fuzzy theory is proposed to achieve high-precision position with constant thrust force of the LPM. Finally, the effectiveness of an fuzzy PI controller is demonstrated by some simulated and experimental results. Accurate tracking response and superior dynamic performance can be obtained due to the powerful on-line Fuzzy PI gain tuning method with regard parametric variations and load thrust force variations.

• 정보통신설비학회논문지
• /
• 제3권2호
• /
• pp.5-10
• /
• 2004

In this paper, the hybrid-type current controller for inverter TIG systems was implemented and it was shown that the low-current pulse wave forms with high dynamic performance could be obtained. It is not sri easy to obtain the optimum gain tuning of PID controllers in digital PWM control methods. Hybrid control methods which uses automatic tuning techniques after adding fuzzy control methods to traditional PID controllers are chosen to improve the dynamic performance of PID controller's. To demonstrate the practical significance and dynamic performance improvement of the results, some simulation and experimental results are presented.