• 제목/요약/키워드: and conventional PID Controller

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Position Control of Shape Memory Alloy Actuators Using Self Tuning Fuzzy PID Controller

  • Ahn Kyoung-Kwan;Nguyen Bao Kha
    • International Journal of Control, Automation, and Systems
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    • 제4권6호
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    • pp.756-762
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    • 2006
  • Shape Memory Alloy(SMA) actuators, which have the ability to return to a predetermined shape when heated, have many potential applications such as aeronautics, surgical tools, robotics and so on. Although the conventional PID controller can be used with slow response systems, there has been limited success in precise motion control of SMA actuators, since the systems are disturbed by unknown factors beside their inherent nonlinear hysteresis and changes in the surrounding environment of the systems. This paper presents a new development of a SMA position control system by using a self-tuning fuzzy PID controller. This control algorithm is used by tuning the parameters of the PID controller thereby integrating fuzzy inference and producing a fuzzy adaptive PID controller, which can then be used to improve the control performance of nonlinear systems. The experimental results of position control of SMA actuators using conventional and self-tuning fuzzy PID controllers are both included in this paper.

Stability Analysis and Proposal of a Simple Form of a Fuzzy PID Controller

  • Lee, Byung-Kyul;Kim, In-Hwan;Kim, Jong-Hwa
    • Journal of Advanced Marine Engineering and Technology
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    • 제28권8호
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    • pp.1299-1312
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    • 2004
  • This paper suggests the simple form of a fuzzy PID controller and describes the design principle, tracking performance, stability analysis and changes of parameters of a suggested fuzzy PID controller. A fuzzy PID controller is derived from the design procedure of fuzzy control. It is well known that a fuzzy PID controller has a simple structure of the conventional PID controller but posses its self-tuning control capability and the gains of a fuzzy PID controller become nonlinear functions of the inputs. Nonlinear calculation during fuzzification, defuzzification and the fuzzy inference require more time in computation. To increase the applicability of a fuzzy PID controller to digital computer, a simple form of a fuzzy PID controller is introduced by the backward difference mapping and the analysis of the fuzzy input space. To guarantee the BIBO stability of a suggested fuzzy PID controller, ‘small gain theorem’ which proves the BIBO stability of a fuzzy PI and a fuzzy PD controller is used. After a detailed stability analysis using ‘small gain theorem’, from which a simple and practical method to decide the parameters of a fuzzy PID controller is derived. Through the computer simulations for the linear and nonlinear plants, the performance of a suggested fuzzy PID controller will be assured and the variation of the gains of a fuzzy PID controller will be investigated.

A Design of PID controller in Two-Mass System Using Optimal Pole Assignment (최적 극배치를 이용한 2관성 공진계의 PID 제어기 설계)

  • Jeon, Don-Su;Kim, Dong-Hwa
    • Proceedings of the KIEE Conference
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    • 대한전기학회 1999년도 하계학술대회 논문집 B
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    • pp.815-817
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    • 1999
  • In the two-mass system driving a load through a flexible shaft or transmission system, a shaft torsional vibration is often generated. In this case, it's difficult to control only by conventional PI controller. To solve this problem. the two-mass speed control system with PID controller is designed by using pole assignment method, and an optimum PID parameters are derived by evaluating ITAE(Integral of time multiplied by the absolute error) performance index. Simulation results show the validity of the proposed PID controller and this controller is compared with the conventional PID controller.

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Speed Control of BLDC Motor Drive Using an Adaptive Fuzzy P+ID Controller (적응 퍼지 P+ID 제어기를 이용한 BLDC 전동기의 속도제어)

  • Kwon, Chung-Jin;Han, Woo-Yang;Sin, Dong-Yang;Kim, Sung-Joong
    • Proceedings of the KIEE Conference
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    • 대한전기학회 2002년도 하계학술대회 논문집 B
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    • pp.1172-1174
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    • 2002
  • An adaptive fuzzy P + ID controller for variable speed operation of BLDC motor drives is presented in this paper. Generally, a conventional PID controller is most widely used in industry due to its simple control structure and ease of design. However, the PID controller suffers from the electrical machine parameter variations and disturbances. To improve the tracking performance for parameter and load variations, the controller proposed in this paper is constructed by using an adaptive fuzzy logic controller in place of the proportional term in a conventional PID controller. For implementing this controller, only one additional parameter has to be adjusted in comparison with the PID controller. An adaptive fuzzy controller applied to proportional term to achieve robustness against parameter variations has simple structure and computational simplicity. The controller based on optimal fuzzy logic controller has an self-tuning characteristics with clustering. Computer simulation results show the usefulness of the proposed controller.

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The Design of Auto Tuning Neuro-Fuzzy PID Controller Based Neural Network (신경회로망 기반 자동 동조 뉴로-퍼지 PID 제어기 설계)

  • Kim, Young-Sik;Lee, Chang-Goo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • 제7권5호
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    • pp.830-836
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    • 2006
  • In this paper described an auto tuning neuro-fuzzy PID controller based neural network. 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. In this paper will design to take advantage of neural network fuzzy theory and pid controller auto toning technique. The value of initial scaling factors of the proposed controller were determined on the basis of the conventional PID controller parameters tuning methods and then they were adjusted by using neural network control techniques. This controller simple structure and computational complexity are less, and also application is easy and performance is excellent in system that is strong and has nonlinearity to system dynamic behaviour change or disturbance. Finally, the proposed auto tuning neuro-fuzzy controller is applied to magnetic levitation. Simulation results demonstrated that the control performance of the proposed controller is better than that of the conventional controller.

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Disturbance Observer based PID Controller for robustness enhancement of UAVs under the presence of wind disturbance (무인항공기의 내풍성 강화를 위한 제어기의 외란관측기 연구)

  • Oh, Seungjo;Lee, Dongjin
    • Journal of the Korean Society for Aviation and Aeronautics
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    • 제26권2호
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    • pp.61-67
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    • 2018
  • This paper presents a method to apply disturbance observer to PID controller for robustness enhancement of UAVs. The system uncertainties and disturbances bring adverse effects on performance and stability of UAVs. In this paper, we estimate the acceleration disturbances using nonlinear disturbance observer, then compensate disturbances with composite controller. By employing nonlinear disturbance observer and composite controller, we have better performance and robustness than conventional PID controller. The asymptotical stability of nonlinear disturbance observer is presented through theoretical analysis. The estimation performance of nonlinear disturbance observer is evaluated by numerical simulation. And performance of disturbance observer based PID controller is evaluated by comparing the performance with conventional PID controller.

Nonlinear PID Controller with Neural Network based Compensator (신경회로망 보상기를 갖는 비선형 PID 제어기)

  • Lee, Chang-Gu
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • 제49권5호
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    • pp.225-234
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    • 2000
  • In this paper, we present an nonlinear PID controller with network based compensator which consists of a conventional PID controller that controls the linear components and neuro-compensator that controls the output errors and nonlinear components. This controller is based on the Harris's concept where he explained that the adaptive controller consists of the PID control term and the disturbance compensating term. The resulting controller's architecture is also found to be very similar to that of Wang's controller. This controller adds a self-tuning ability to the existing PID controller without replacing it by compensating the output errors through the neuro-compensator. Various simulations and comparative studies have proven that the proposed nonlinear PID controller produces superior results to other existing PID controllers. When applied to an actual magnetic levitation system which is known to be very nonlinear, it has also produced an excellent results.

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Design of a Auto-Tuning Digital PID Controller using Relay feedback and Time Delay (시간 지연 릴레이 피드백을 이용한 자동동조 디지털 PID 제어기의 설계)

  • 류경모;박정일
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.109-109
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    • 2000
  • In process industries, more than 90% of the control loops have PID controller. Futhermore, the most control systems are using classical PID controllers for their process control. Various auto-tuning methods of PID gains using relay-feedback are presented recently. In order to get the desired control performance, the correct tuning of PID controller is very important. This paper suggests how to tune of digital PID gains using information for both the Nyquist critical point by conventional method and another point by the relay feedback and hidden time-delay term. Simulation results show that the proposed controller has better performance than the conventional method.

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Controller Design of Two Wheeled Inverted Pendulum Type Mobile Robot Using Neural Network (신경회로망을 이용한 이륜 역진자형 이동로봇의 제어기 설계)

  • An, Tae-Hee;Kim, Yong-Baek;Kim, Young-Doo;Choi, Young-Kiu
    • Journal of the Korea Institute of Information and Communication Engineering
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    • 제15권3호
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    • pp.536-544
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    • 2011
  • In this paper, a controller for two wheeled inverted pendulum type robot is designed to have more stable balancing capability than conventional controllers. Traditional PID control structure is chosen for the two wheeled inverted pendulum type robot, and proper gains for the controller are obtained for specified user's weights using trial-and-error methods. Next a neural network is employed to generate PID controller gains for more stable control performance when the user's weight is arbitrarily selected. Through simulation studies we find that the designed controller using the neural network is superior to the conventional PID controller.

A PID learning controller for DC motors (DC 전동기를 위한 PID 학습제어기)

  • 백승민;이동훈;국태용
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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    • pp.347-350
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    • 1996
  • With only the classical PID controller applied to control of a DC motor, a good (target) performance characteristic of the controller can be obtained, if all the model parameters of DC motor and operating conditions such as external load torque, disturbance, etc. are exactly known. However, in case when some of system parameters or operating conditions are uncertain or unknown, the fixed PID controller does not guarantee the good performance which is assumed with precisely known system parameters and operating conditions. In view of this and robustness enhancement of DC motor control system, we propose a PID learning controller which consists of a set of learning rules for PID gain tuning and learning of an auxiliary input. The proposed PID learning controller is shown to drive the state of uncertain DC motor system with unknown system parameters and external load torque to the desired one globally asymptotically. Computer simulation results are given to demonstrate the effectiveness of the proposed PID learning controller, thereby showing whose superiority to the conventional fixed PID controller.

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