• Title/Summary/Keyword: PI-PD 제어기

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Design and Analysis of Fuzzy PID Controller for Control of Nonlinear System (비선형 시스템 제어를 위한 퍼지 PID 제어기의 설계 및 해석)

  • Lee, Chul-Heui;Kim, Sung-Ho
    • Journal of Industrial Technology
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    • v.20 no.B
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    • pp.155-162
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    • 2000
  • Although Fuzzy Logic Controller(FLC) adopted three terms as input gives better performance, FLC is in general composed of two-term control because of the difficulty in the construction of fuzzy rule base. In this paper, a three-term FLC which is similar to PID control but acts as a nonlinear controller is proposed. To reduce the complexity of the rule base design and to increase efficiency. a simplified fuzzy PID control is induced from a hybrid velocity/position type PID algorithm by sharing a common rule base for both fuzzy PI and fuzzy PD parts. It is simple in structure, easy in implementation, and fast in calculation. The phase plane technique is applied to obtain the rule base for fuzzy two-term control and the resultant rule base is Macvicar-Whelan type. And the membership function is a Gaussian function. The frequency response information is used in tuning of the membership functions. Also a tuning strategy for the scaling factors is proposed based on the relationship between PID gain and the scaling factors. Simulation results show better performance and the effectiveness of the proposed method.

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Development of Autonomous Algorithm Using an Online Feedback-Error Learning Based Neural Network for Nonholonomic Mobile Robots (온라인 피드백 에러 학습을 이용한 이동 로봇의 자율주행 알고리즘 개발)

  • Lee, Hyun-Dong;Myung, Byung-Soo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.21 no.5
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    • pp.602-608
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    • 2011
  • In this study, a method of designing a neurointerface using neural network (NN) is proposed for controlling nonholonomic mobile robots. According to the concept of virtual master-slave robots, in particular, a partially stable inverse dynamic model of the master robot is acquired online through the NN by applying a feedback-error learning method, in which the feedback controller is assumed to be based on a PD compensator for such a nonholonomic robot. The NN for the online feedback-error learning can composed that the input layer consists of six units for the inputs $x_i$, i=1~6, the hidden layer consists of two hidden units for hidden outputs $o_j$, j=1~2, and the output layer consists of two units for the outputs ${\tau}_k$, k=1~2. A tracking control problem is demonstrated by some simulations for a nonholonomic mobile robot with two-independent driving wheels. The initial q value was set to [0, 5, ${\pi}$].

A Triple Nested PID Controller based on Sensor Fusion for Quadrotor Attitude Stabilization (쿼드로터 자세 안정화를 위한 센서융합 기반 3중 중첩 PID 제어기)

  • Cho, Youngwan
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.67 no.7
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    • pp.871-877
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    • 2018
  • In this paper, we propose a triple nested PID control scheme for stable hovering of a quadrotor and propose a complementary filter based sensor fusion technique to improve the performance of attitude, altitude and velocity measurement. The triple nested controller has a structure in which a double nested attitude controller that has the angular velocity PD controller in inner loop and the angular PI controller in outer loop, is nested in a velocity control loop to enable stable hovering even in the case of disturbance. We also propose a sensor fusion technique by applying a complementary filter in order to reduce the noise and drift error included in the acceleration and gyro sensor and to measure the velocity by fusing image, gyro, and acceleration sensor. In order to verity the performance, we applied the proposed control and measurement scheme to hovering control of quadrotor.

Fuzzy Algorithms to Generate Level Controllers for Nuclear Power Plant Steam Generators (원전 증기 발생기 수위제어용 퍼지 알고리즘)

  • Moon, Byung-Soo;Park, Jae-Chang;Kim, Dong-Hwa;Kim, Byung-Koo
    • Nuclear Engineering and Technology
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    • v.25 no.2
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    • pp.222-232
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    • 1993
  • In this paper, we present two sets of fuzzy algorithms for the steam generator level control ; one for the high power operations where the flow error is available and the other for the low power operations where the flow error is not available. These are converted to a PID type controller for the high power case and to a quadratic function form of a controller for the low power case. These controllers are implemented on the Compact Nuclear Simulator at Korea Atomic Energy Research Institute and tested by a set of four simulation experiments for each. For both cases, the results show that the total variation of the level error and of the flow error are about 50% of those by the PI controllers with about one half of the control action. For the high power case, this is mainly due to the fact that a combination of two PD type controllers in the velocity algorithm form rather than a combination of two PI type controllers in the position algorithm form is used. For the low power case, the controller is essentially a PID type with a very small integral component where the average values for the derivative component input and for the controller output are used.

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Phase-Shifting System Using Zero-Crossing Detection for use in Fiber-Optic ESPI (영점검출을 이용한 광섬유형 전자 스페클 패턴 간섭계의 위상이동)

  • Park, Hyoung-Jun;Song, Min-Ho;Lee, Jun-Ho
    • Korean Journal of Optics and Photonics
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    • v.16 no.6
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    • pp.516-520
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    • 2005
  • We proposed an efficient phase stepping method for the use in fiber-optic ESPI. To improve phase-stepping accuracy and efficiency, a fiber-optic Michelson interferometer was phase-modulated by a ramp-driven fiber stretcher, resulting in 4$\pi$ phase excursion in the PD interference signal. The zero-crossing points of the signal, which have consecutive $\pi$ phase difference, were carefully detected and used to generate trigger signals for the CCD camera. From the experimental results by using this algorithm, $\pi$/2 phase-stepping errors between the speckle patterns were measured to be less than 0.6 mrad with 100 Hz image capture speed. Also it has been shown that the error from the nonlinear phase modulation and environmental perturbations could be minimized without any feedback algorithm.

Auto-tunning of a FLC using Neural Networks (신경망을 이용한 서보제어기의 자동조정)

  • Yeon, Jae-Kuen;Yum, Jin-Ho;Nam, Hyun-Do
    • Proceedings of the KIEE Conference
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    • 1996.07b
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    • pp.1034-1036
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    • 1996
  • In this paper, an adaptive fuzzy logic controller is presented for auto-tunning of the scaling factors by using learning capability of neural networks. The proposed scheme consists of the FLC which includes the PI-type FLC and PD-type FLC in parallel form and the neural network which learns scale factors of FLC. Computer simulations were performed to illustrate the effectiveness of a proposed scheme. A proposed FLC controller was applied to the second order system and velocity control of the brushless DC motors. For the design of the FLC, tracking error, change of error, and acceleration error are selected as input variables of the FLC and three seal e factors were used in the parallel-type FLC. This scheme can be used to reduce the difficulty in the selection of the scale factors.

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Design and Analysis of Fuzzy PID Control for Nonlinear System (비선형 시스템을 위한 퍼지 PID 제어기의 설계 및 해석)

  • Kim, Sung-Ho;Lee, Cheul-Heui
    • Proceedings of the KIEE Conference
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    • 2000.11d
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    • pp.650-652
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    • 2000
  • Although Fuzzy Logic Controller(FLC) adopted three terms as input gives better performance. FLC is in general composed of two-term control because of the difficulty in the construction of fuzzy rule base. In this paper, a three-term FLC which is similar to PID control but acts as a nonlinear controller is proposed. To reduce the complexity of the rule base design and increase efficiency, a simplified fuzzy PID control is induced from a hybrid velocity/position type PID algorithm by sharing a common rule base for both fuzzy Pi and fuzzy PD parts. It is simple in structure, easy in implementation, and fast in calculation. The phase plane technique is applied to obtain the rule base for fuzzy two-term control and them. The resultant rule base is Macvicar-Whelan type. The frequency response information is used in tuning of membership functions. Also a tuning strategy for the scaling factors is Proposed based on the relationship between PID gain and them. Simulation results show better performance and the effectiveness of the proposed method.

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