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Journal articles on the topic 'On-line tuning PID controller'

Author: Grafiati

Published: 5 June 2025

Last updated: 1 August 2025

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1

Chen, Wen Wen, You Kuan Liu, Xiang Yu Tan, et al. "PID Parameter Optimization Based on Fuzzy Control." Advanced Materials Research 960-961 (June 2014): 1156–61. http://dx.doi.org/10.4028/www.scientific.net/amr.960-961.1156.

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PID controllers are widely used in industrial process control. The determination of the conventional PID controller parameter tuning is based on obtaining the mathematical model of controlled objects and according to certain rules, which is difficult to adapt to complex control systems. In this paper ,against its adverse effect parameter tuning, long time debugging, defects and poor adaptability of the controlled object,the fuzzy control and PID control are combined and the fuzzy PID controller is proposed. Then, I combine the examples of thermal power units using MATLAB to simulate. The simul

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2

Riaño Jaimes, Cristhian Ivan, Jorge Luis Diaz Rodriguez, and Diego Armando Mejía Bugallo. "On-line method for optimal tuning of PID controllers using standard OPC interface." Inge CuC 18, no. 2 (2022): 13–26. http://dx.doi.org/10.17981/ingecuc.18.2.2022.02.

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Introduction− The controlled PID is the most widely used mathematical algorithm as a regulatory control strategy in industrial environments. The applications are varied; however, its answer depends on the proper calculation of its three parameters: the proportional, the derivative, and the integral. Analytical tuning and experimental methods solve the problem, but new tuning possibilities are now enabled within the digital and process integration context. Objective− Automatically and remotely obtain the optimal parameters of the PID controller, taking advantage of an online connection via the

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3

Liu, Chan Yuan, and Guo Guang Chen. "Based on the MATLAB Self-Tuning Fuzzy PID Controller Design." Applied Mechanics and Materials 313-314 (March 2013): 443–47. http://dx.doi.org/10.4028/www.scientific.net/amm.313-314.443.

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Based on MATLAB self-tuning fuzzy PID controller design, the line parameter of the PID controller to adjust, to further improve the performance of the PID controller to adapt to changes in the control object parameters changes and working conditions.Introduction

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4

Chen, Yin Ping. "Study on Auto-Tuning PID Controller." Advanced Materials Research 1037 (October 2014): 225–27. http://dx.doi.org/10.4028/www.scientific.net/amr.1037.225.

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PID control is the most common control method used in process control. The PID control parameters tuning methods are develop constantly. At present, in numerous tuning methods, there are mainly two methods applied better in the practical industrial process. One is based on pattern identification (based on rules); the other is based on relay feedback (based on model). They are collectively referred to as intelligent PID parameter tuning method. This paper studies on the PID parameter auto-tuning methods and introduces the results of the latest research on this subject. Finally, the development

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5

Arvanitis, K. G., N. A. Sigrimis, G. D. Pasgianos, and G. Kalogeropoulos. "On-line PID controller tuning for open-loop unstable processes." IFAC Proceedings Volumes 33, no. 20 (2000): 25–32. http://dx.doi.org/10.1016/s1474-6670(17)38020-5.

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Tan, K. K., T. H. Lee, and X. Jiang. "On-line relay identification, assessment and tuning of PID controller." Journal of Process Control 11, no. 5 (2001): 483–96. http://dx.doi.org/10.1016/s0959-1524(00)00012-3.

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7

Sheet, Amer Farhan. "Optimization of DC motor speed control based on fuzzy logic-PID controller." Analysis and data processing systems, no. 3 (September 30, 2021): 143–53. http://dx.doi.org/10.17212/2782-2001-2021-3-143-153.

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In this paper the PID controller and the Fuzzy Logic Controller (FLC) are used to control the speed of separately excited DC motors. The proportional, integral and derivate (KP, KI, KD) gains of the PID controller are adjusted according to Fuzzy Logic rules. The FLC cotroller is designed according to fuzzy rules so that the system is fundamentally robust. Twenty-five fuzzy rules for self-tuning of each parameter of the PID controller are considered. The FLC has two inputs; the first one is the motor speed error (the difference between the reference and actual speed) and the second one is a cha

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8

Niembro-Ceceña, José A., Roberto A. Gómez-Loenzo, Juvenal Rodríguez-Reséndiz, Omar Rodríguez-Abreo, and Ákos Odry. "Auto-Regression Model-Based Off-Line PID Controller Tuning: An Adaptive Strategy for DC Motor Control." Micromachines 13, no. 8 (2022): 1264. http://dx.doi.org/10.3390/mi13081264.

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Brushed (B) and Brushless (BL) DC motors constitute the cornerstone of mechatronic systems regardless their sizes (including miniaturized), in which both position and speed control tasks require the application of sophisticated algorithms. This manuscript addresses the initial step using time series analysis to forecast Back EMF values, thereby enabling the elaboration of real-time adaptive fine-tuning strategies for PID controllers in such a control system design problem. An Auto-Regressive Moving Average (ARMA) model is developed to estimate the DC motor parameter, which evolves in time due

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9

Vrančić, Damir, and Mikuláš Huba. "High-Order Filtered PID Controller Tuning Based on Magnitude Optimum." Mathematics 9, no. 12 (2021): 1340. http://dx.doi.org/10.3390/math9121340.

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The paper presents a tuning method for PID controllers with higher-order derivatives and higher-order controller filters (HO-PID), where the controller and filter orders can be arbitrarily chosen by the user. The controller and filter parameters are tuned according to the magnitude optimum criteria and the specified noise gain of the controller. The advantages of the proposed approach are twofold. First, all parameters can be obtained from the process transfer function or from the measured input and output time responses of the process as the steady-state changes. Second, the a priori defined

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10

Huang, H. P., J. C. Jeng, and M. L. Roan. "On-line adaptive tuning for PID controllers." IEE Proceedings - Control Theory and Applications 149, no. 1 (2002): 60–67. http://dx.doi.org/10.1049/ip-cta:20020099.

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11

Kim, T. Yu, and R. A. Prakapovich. "Optimization of the PID coefficients for the line-follower mobile robot controller employing genetic algorithm." Informatics 18, no. 4 (2021): 53–68. http://dx.doi.org/10.37661/1816-0301-2021-18-4-53-68.

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O b j e c t i v e s. To develop a control system for the movement of a mobile robot along a color-contrast line, as well as to find the values of the coefficients of a proportional-integral-differentiating (PID) controller that allows the robot to move along the line at a given speed.M e t ho d s. To adjust the values of the coefficients of the PID controller, methods of enumeration, automatic tuning and a genetic algorithm are used.Re s u l t s. A software package for tuning the PID controller of the educational mobile robot RoboCake, designed to move along a closed color-contrast line at a g

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12

Laskawski, Michal, and Miroslaw Wcislik. "Sampling Rate Impact on the Tuning of PID Controller Parameters." International Journal of Electronics and Telecommunications 62, no. 1 (2016): 43–48. http://dx.doi.org/10.1515/eletel-2016-0005.

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Abstract The paper deals with an analysis of automatic control system with continuous and discrete PID controllers. A method of tuning the parameters of the continuous controller is presented, which is optimal according to the ITAE criterion. The behavior of control systems with discrete controllers whose parameters were tuned using the mentioned method are described. The impact of changes in the sampling period of controlled signal on the control quality is shown. Changes of the values of optimal parameters of discrete PID controllers in relation to changes of the sampling rate of controlled

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13

Mohammad, Amin Rashidifar1 and Abdolah abertavi2. "A NOVEL TECHNIQUE FOR CONTROLLER TUNING." International Journal of Applied Control, Electrical and Electronics Engineering (IJACEEE) 2, no. 2 (2018): 01–12. https://doi.org/10.5281/zenodo.1494946.

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Neural networks and genetic algorithms have been in the past successfully applied, separately, to controller tuning problems. In this paper we purpose to combine its joint use, by exploiting the nonlinear mapping capabilities of neural networks to model objective functions, and use them to supply their values to a genetic algorithm which performs on-line minimization. Simulation results show that this is a valid approach, offering desired properties for on-line use such as a dramatic reduction in computation time and avoiding the need of perturbing the closed-loop operation.

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14

Wang, Xue Song. "Research of Fuzzy PID Control Based on VHDL." Applied Mechanics and Materials 416-417 (September 2013): 885–89. http://dx.doi.org/10.4028/www.scientific.net/amm.416-417.885.

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This paper describes the use of VHDL and fuzzy controller design process.Compared with conventional PID control, fuzzy control is not dependent on the accurate mathematical model of the controlled object. The implementation of integrated practical operating experience and the operation is simple, fast response, anti-interference ability, strong robustness parameters of controlled object. In response to the limitations of the traditional PID control algorithm in the control field, the fuzzy control theory with the traditional PID control algorithm by combining the parameters self-tuning functio

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15

Alawan, Mazin Abdulelah, and Oday Jasim Mohammed Al-Furaiji. "Numerous speeds loads controller for DC shunt motor based on PID controller with online parameters tuning supported by genetic algorithm." Indonesian Journal of Electrical Engineering and Computer Science 21, no. 1 (2021): 64–73. https://doi.org/10.11591/ijeecs.v21.i1.pp64-73.

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Direct current (DC) motor is a commonly used motor; its speed is directly affected by applying mechanical load. This paper proposes the design of wide speed-load range controller for a direct current (DC) shunt motor based on proportional integral derivative (PID controller) with genetic system for controller parameters adjusting. The genetic based PID controller is simulated by using Matlab software package and tested with different sudden load values and different working speeds. A present control loop contains the suggested PID controller also pulse width modulation PWM generator and H-brid

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16

Chang, Wei-Der, Rey-Chue Hwang, and Jer-Guang Hsieh. "A multivariable on-line adaptive PID controller using auto-tuning neurons." Engineering Applications of Artificial Intelligence 16, no. 1 (2003): 57–63. http://dx.doi.org/10.1016/s0952-1976(03)00023-x.

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17

Lee, Jietae. "On-line PID controller tuning from a single, closed-loop test." AIChE Journal 35, no. 2 (1989): 329–31. http://dx.doi.org/10.1002/aic.690350221.

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18

Qian, Zheng Zai, Gong Cai Xin, and Jin Niu Tao. "Predictive Control Based on Fuzzy Expert PID Tuning Control." Advanced Materials Research 466-467 (February 2012): 1207–11. http://dx.doi.org/10.4028/www.scientific.net/amr.466-467.1207.

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In decade years, several simple methods for the automatic tuning of PID controllers have been proposed. There have been different approaches to the problem of deriving a PID-like adaptive controller. All of these can be classified into two broad categories: model-based; or expert systems. In this paper a new expert adaptive controller is proposed in which the underlying control law is a PID structure. The design is based on the fuzzy logic and the generalized predictive control theory. The proposed controller can be applied to a large class of systems which is model uncertainty or strong non-l

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19

Sambariya, D. K., and Seema Shrangi. "Optimal Design of PID Controller for Load Frequency Control using Harmony Search Algorithm." Indonesian Journal of Electrical Engineering and Computer Science 5, no. 1 (2017): 19. http://dx.doi.org/10.11591/ijeecs.v5.i1.pp19-32.

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This paper deals with soft computing technique, used for tuning PID controller. Controller tuned with a harmony search algorithm is used for controlling the frequency and Tie-line power responses of a non reheat two area power system. Step load perturbation has been given in both areas simultaneously. The dynamic results obtained by the proposed controller are compared with PID controller of recent published paper. The performance of the controllers is simulated using MATLAB/Simulation software. The results of tuned PID are compared with conventional controller on the basis of settling-time, p

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20

Xu, Gang. "Research on system simulation based on fuzzy self-tuning." Journal of Physics: Conference Series 2183, no. 1 (2022): 012027. http://dx.doi.org/10.1088/1742-6596/2183/1/012027.

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Abstract This paper introduces the principle of fuzzy control. On this basis, a fuzzy self-tuning PID controller is designed to the requirements of SRD system. The fuzzy self-tuning PID controller is introduced into the switched reluctance motor speed regulation system, the switched reluctance motor speed regulation system based on fuzzy self-tuning PID is simulated and compared with the conventional PID switched reluctance motor speed regulation system. The comparison results show that the application of fuzzy self-tuning PID controller in the switched reluctance motor speed regulation system

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21

WU, Q. H., and B. W. HOGG. "On-line evaluation of auto-tuning optimal PID controller on micromachine system." International Journal of Control 53, no. 4 (1991): 751–69. http://dx.doi.org/10.1080/00207179108953647.

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22

Kim, Seng Chia. "Ziegler-Nichols Based Proportional-Integral-Derivative Controller for a Line Tracking Robot." Indonesian Journal of Electrical Engineering and Computer 9, no. 1 (2018): 221–26. https://doi.org/10.11591/ijeecs.v9.i1.pp221-226.

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Line tracking robots have been widely implemented in various applications. Among various control strategies, a proportional-integral-derivative (PID) algorithm has been widely proposed to optimize the performance of a line tracking robot. However, the motivation of using a PID controller, instead of a proportional (P) or a proportional-integral (PI) controller, in a line tracking task has seldom been discussed. Particularly, the use of a systematic tuning approach e.g. closed loop Ziegler Nichols rule to optimize the parameters of a PID controller has rarely been investigated. Thus, this paper

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23

Gbadega, Peter Anuoluwapo, and Akshay Kumar Saha. "Dynamic Tuning of the Controller Parameters in a Two-Area Multi-Source Power System for Optimal Load Frequency Control Performance." International Journal of Engineering Research in Africa 51 (November 2020): 111–29. http://dx.doi.org/10.4028/www.scientific.net/jera.51.111.

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Frequency control is becoming increasingly critical today due to the growing size and changing structure of complex interconnected power networks. Scaling up economic pressures for efficiency and reliability of the power system has necessitated a requirement for maintaining system frequency, and tie-line power flows as close as possible to scheduled values. High-frequency deviations may degrade load performance, damage equipment, resulting in overloading of transmission lines, which may interfere with system protection schemes, and, finally, may also result in an unstable condition of the powe

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24

Ding, Ye, Xiaoguang Ren, Xiaochuan Zhang, Xin Liu, and Xu Wang. "Multi-Phase Focused PID Adaptive Tuning with Reinforcement Learning." Electronics 12, no. 18 (2023): 3925. http://dx.doi.org/10.3390/electronics12183925.

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The Proportional-Integral-Derivative (PID) controller, a fundamental element in industrial control systems, plays a pivotal role in regulating an extensive array of controlled objects. Accurate and rapid adaptive tuning of PID controllers holds significant practical value in fields such as mechatronics, robotics, and automatic control. The three parameters of the PID controller exert a substantial influence on control performance, rendering the tuning of these parameters an area of significant interest within related research fields. Numerous tuning techniques are widely employed to optimize i

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25

Gan, Xu Sheng, Xue Qin Tang, and Jian Guo Gao. "Missile Autopilot Design Based on Fuzzy Self-Tuning Immune PID Control." Advanced Materials Research 739 (August 2013): 550–54. http://dx.doi.org/10.4028/www.scientific.net/amr.739.550.

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A design of the fuzzy self-tuning immune PID controller is proposed. The controller, which combines immune feedback mechanism and fuzzy PID control, executes the self-tuning of PID parameters in the control system. A simulation experiment is presented in light of a tactical missile autopilot transfer function. Simulation result shows that the performance of fuzzy self-tuning immune PID controller is better than that of fuzzy PID controller, especially in its robust performance for variable parameter system.

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26

Chaisaward, Adithep, Kittipong Ardhan, Jagraphon Obma, and Worawat Sa-ngiamvibool. "Designing PID controller using SSA for interconnected thermal power systems." EUREKA: Physics and Engineering, no. 3 (May 27, 2024): 73–80. http://dx.doi.org/10.21303/2461-4262.2024.003321.

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This article presents a method of designing an optimal Proportional-Integral-Derivative (PID) controller for Automatic Generation Control (AGC) of a two-area interconnected thermal system. In addition, an application of Salp Swarm Algirithm (SSA) in order to design PID controllers is proposed. A method inspired by salp foraging behavior. The journey of the Salp group in the sea, by random the population of the salp and separated into leader salp and follower salp. The leader moves towards the food source and the rest of the followers follow the salp positioned in front of themselves. The param

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27

Chen, Jian Wen, Lei Li, Jin Chun Song, and Zhan Jun He. "Simulation of Fuzzy Auto-Tuning PID Control Based on MATLAB." Advanced Materials Research 308-310 (August 2011): 579–83. http://dx.doi.org/10.4028/www.scientific.net/amr.308-310.579.

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In CNC machine tools servo feed system, there are many uncertain parameters, it is difficult to establish accurate mathematical model of the Servo feed system. The parameters of conventional PID controller can’t adjust immediately to the controlled object. Fuzzy PID controller [1], which has the advantages of conventional PID control and fuzzy control, can solve these problems. We apply it in numerical control machine servo feed system. The simulation in MATLAB shows that the fuzzy auto-tuning PID controller improve the dynamic performance of the servo feed system and has better robustness.

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28

Tang, Jing, Yun An Hu, and Jing Li. "PID Controller Parameter Tuning Based on Iterative Learning Control." Advanced Materials Research 129-131 (August 2010): 511–15. http://dx.doi.org/10.4028/www.scientific.net/amr.129-131.511.

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On the basis of sufficient analysis to the characteristic of iterative learning control and PID controller parameter tuning, an idea of applying iterative learning control to PID controller parameter tuning was aroused in this paper, we choose the linear model around the character point of Roll Attitude controller as the research plant, transforming the problem of PID controller parameter tuning into the problem of open-close loop iterative learning control problem. The stability of PID controller parameter iterative learning control system and the astringency of controller parameters were ver

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29

Martínez Sarmiento, Fredy Hernán, and Diego Mauricio Acero Soto. "PID controller tuning using bacterial Quorum Sensing (QS)." Tecnura 24, no. 64 (2020): 13–22. http://dx.doi.org/10.14483/22487638.16530.

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Objective: PID controllers are widely used to operate AC motors due to their simplicity and easy implementation. However, adjusting its parameters in search of an optimal scheme can be complex because it requires manual tuning by trial and error. This research aims to implement an optimized tuning scheme through a search based on the idealized behavior of a community of bacteria and its Quorum Sensing (QS). Methodology: A closed-loop system model with PID control considering disturbances is proposed in order to tune a disturbance-resistant controller. The response of the model is calcula

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30

Kim, Dong Hwa, and Jae Hoon Cho. "Robust Tuning of PID Controller Using Bacterial-Foraging-Based Optimization." Journal of Advanced Computational Intelligence and Intelligent Informatics 9, no. 6 (2005): 669–76. http://dx.doi.org/10.20965/jaciii.2005.p0669.

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We propose a design approach to PID controllers with resistance to external disturbance in motor-controlled systems using a bacterial foraging-based optimal algorithm. PID controllers are used to operate AC motor drives because of their practical implementation and simple structure. Inexperienced personnel find it difficult, however, to achieve optimal PID gain because this is manually tuned by trial and error in industrial environments full of disturbances. To design disturbance-resistance tuning, we use disturbance-resistance conditions based on H∞ and calculcate response the performance bas

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31

Zhu, Yin Fa, and Bing Bing Chen. "Research of Control Strategy Based on the Electro-Hydraulic Proportion Position Control System." Advanced Materials Research 819 (September 2013): 238–43. http://dx.doi.org/10.4028/www.scientific.net/amr.819.238.

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The self-tuning fuzzy PID controller of the electro-hydraulic proportion position control system is designed and researched. Compared the self-tuning fuzzy PID control with the traditional PID control through experiments for the track effect on sinusoidal signals, the results show that the self-tuning fuzzy PID controller has higher accuracy and better stability. It is a more excellent performance controller.

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32

Zhang, Xue Ming, Gui Xiang Zhang, Feng Shao, and Qing Jie Yang. "Design of Compound Fuzzy Controller for Multivariable Systems." Applied Mechanics and Materials 16-19 (October 2009): 150–54. http://dx.doi.org/10.4028/www.scientific.net/amm.16-19.150.

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The PID controllers can be seen in lots of fields, but some complex control system cannot be controlled to achieve a desired performance index. A design method of the fuzzy PID controller that is based on the fuzzy tuning rules and formed by integrating two above control ideas is proposed in this paper. The design procedure about fuzzy PID control can be divided two steps: the first step is to build the fuzzy tuning rules by analysis, and to obtain the parameters of PID controller by reasoning, and then the control action can be determined by the PID control law. The simulation results and the

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33

Abdulelah Alawan, Mazin, and Oday Jasim Mohammed Al-Furaiji. "Numerous speeds-loads controller for DC-shunt motor based on PID controller with on-line parameters tuning supported by genetic algorithm." Indonesian Journal of Electrical Engineering and Computer Science 21, no. 1 (2021): 64. http://dx.doi.org/10.11591/ijeecs.v21.i1.pp64-73.

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<p><span>Direct-current (DC) motor is a commonly used motor; its speed is directly affected by applying mechanical load. This paper proposes the design of wide speed-load range controller for a direct-current (DC) shunt motor based on proportional–integral–derivative (PID controller) with genetic system for controller parameters adjusting. The genetic based PID controller is simulated by using Matlab software package and tested with different sudden load values and different working speeds. A present control loop contains the suggested PID controller also Pulse-Width-Modulation PWM

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34

Bai, Zekun. "Advances and Prospects of PID Controller in Mechanical Field: From Traditional Tuning to Intelligent Optimization." Applied and Computational Engineering 104, no. 1 (2024): 53–58. http://dx.doi.org/10.54254/2755-2721/104/20241105.

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Abstract. The extensive use of PID controllers in the mechanical fieldparticularly in robots and other mechanical systemsis covered in this study. In these sectors, PID controllers have become the most popular control technology due to their straightforward design and simplicity of use. PID controller performance in nonlinear complex systems is explored, along with stability and adaptive adjustment, by comparing the conventional and intelligent PID tuning methods. According to the research, control performance can be greatly enhanced by merging PID controller with intelligent technologies like

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35

Pelc, Mariusz. "Self-tuning run-time reconfigurable PID controller." Archives of Control Sciences 21, no. 2 (2011): 189–205. http://dx.doi.org/10.2478/v10170-010-0039-y.

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Self-tuning run-time reconfigurable PID controller Digital PID control algorithm is one of the most commonly used algorithms in the control systems area. This algorithm is very well known, it is simple, easily implementable in the computer control systems and most of all its operation is very predictable. Thus PID control has got well known impact on the control system behavior. However, in its simple form the controller have no reconfiguration support. In a case of the controlled system substantial changes (or the whole control environment, in the wider aspect, for example if the disturbances

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Chen, Xiu Jia, and Hong Di Qiu. "Research on Single Neuron Adaptive PID Controller." Applied Mechanics and Materials 651-653 (September 2014): 826–30. http://dx.doi.org/10.4028/www.scientific.net/amm.651-653.826.

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The paper focuses on single neuron adaptive PID controller based on unsupervised Hebb algorithm, and simulation research on the controller is carried out for a second-order pure lag process system. Simulation results show that through learning and adjusting weights of single neuron adaptive PID controller, its online self-tuning ability can make timely adjustment of PID controller parameters according to controlled object changes and external disturbances in order to ensure that the stability and robustness of the system and, ultimately, more satisfactory actual control effect is obtained. At

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37

Tanawat, Chalardsakul, Piliyasilpa Chotnarin, and Sukontanakarn Viroch. "TMS320F28379D microcontroller for speed control of permanent magnet direct current motor." IAES International Journal of Artificial Intelligence (IJ-AI) 13, no. 3 (2024): 2816–28. https://doi.org/10.11591/ijai.v13.i3.pp2816-2828.

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This paper aims to study the behavior of the proportional integral derivative (PID) and the fuzzy-based tuning PI-D controller for speed control of a permanent magnet direct current (PMDC) motor. The proposed method used a fuzzy-based tuning PI-D controller with a MATLAB/Simulink program to design and real-time implement a TMS320F28379D microcontroller for speed control of a PMDC motor. The performance of the study designed fuzzy-based tuning PI-D and PID controllers is compared and investigated. The fuzzy logic controller applies the controlling voltage based on motor speed errors. Finally, t

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38

Pessen, David W. "A New Look at PID-Controller Tuning." Journal of Dynamic Systems, Measurement, and Control 116, no. 3 (1994): 553–57. http://dx.doi.org/10.1115/1.2899252.

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The well-known Ziegler-Nichols method for tuning controllers has been used for 50 years. Since it is still popular, the time is ripe for a reappraisal. It is shown that the Ziegler-Nichols settings for PID-controllers have been misapplied by being used indiscriminately with different PID-controller configurations. Computer simulation made on 15 representative processes indicates how these settings should be modified to obtain good response for load step changes. The results are presented in three different forms, for different controller configurations.

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39

Chia, Kim Seng. "Ziegler-Nichols Based Proportional-Integral-Derivative Controller for a Line Tracking Robot." Indonesian Journal of Electrical Engineering and Computer Science 9, no. 1 (2018): 221. http://dx.doi.org/10.11591/ijeecs.v9.i1.pp221-226.

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<p>Line tracking robots have been widely implemented in various applications. Among various control strategies, a proportional-integral-derivative (PID) algorithm has been widely proposed to optimize the performance of a line tracking robot. However, the motivation of using a PID controller, instead of a proportional (P) or a proportional-integral (PI) controller, in a line tracking task has seldom been discussed. Particularly, the use of a systematic tuning approach e.g. closed loop Ziegler Nichols rule to optimize the parameters of a PID controller has rarely been investigated. Thus, t

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40

Andrášik, A., A. Mészáros, and S. F. de Azevedo. "On-line tuning of a neural PID controller based on plant hybrid modeling." Computers & Chemical Engineering 28, no. 8 (2004): 1499–509. http://dx.doi.org/10.1016/j.compchemeng.2003.12.002.

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41

Raza, Wasim, Dieky Adzikya, Saba Mehmood, et al. "Fuzzy Logic Speed Regulator for D.C. Motor Tuning." JTAM (Jurnal Teori dan Aplikasi Matematika) 8, no. 1 (2024): 36. http://dx.doi.org/10.31764/jtam.v8i1.16919.

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A D.C. motor's rotational speed is regulated in this study using a PID controller and a fuzzy logic controller. In contrast to the fuzzy logic controller, which uses rules based on knowledge and experience, the proportional-integral-derivative (PID) controller requires a mathematical system model. This study investigates the regulation of a DC motor's velocity using PID and fuzzy logic controllers. The PID controller utilizes a mathematical model and parameter tuning by trial and error. Still, the fuzzy logic controller (FLC) operates on rule-based knowledge, enabling it to handle the nonlinea

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Chu, Pengzi, Yi Yu, Danyang Dong, Hui Lin, and Jianjun Yuan. "NSGA-II-Based Parameter Tuning Method and GM(1,1)-Based Development of Fuzzy Immune PID Controller for Automatic Train Operation System." Mathematical Problems in Engineering 2020 (March 24, 2020): 1–20. http://dx.doi.org/10.1155/2020/3731749.

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Automatic train operation (ATO) system is one of the important components in advanced train operation control systems. Ideal controllers are expected for the automatic driving function of ATO systems. Aiming at the intelligence requirements of the systems, an NSGA-II-based parameter tuning method for the fuzzy immune PID (FI-PID) controller and a grey model GM(1,1)-based fuzzy grey immune PID (FGI-PID) controller were proposed. Taking a maglev train’s model as the control object and a velocity-time curve as the input, the feasibility of the parameter tuning method for the FI-PID controller and

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Song, Yinglei. "A Fractional PID Controller Based on Particle Swarm Optimization Algorithm." Journal of Autonomous Intelligence 3, no. 1 (2020): 1. http://dx.doi.org/10.32629/jai.v3i1.94.

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Fractional PID controller is a convenient fractional structure that has been used to solve many problems in automatic control. The fractional scale proportional-integral-differential controller is a generalization of the integer order PID controller in the complex domain. By introducing two adjustable parameters and , the controller parameter tuning range becomes larger, but the parameter design becomes more complex. This paper presents a new method for the design of fractional PID controllers. Specifically, the parameters of a fractional PID controller are optimized by a particle swarm optimi

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Arrieta, Orlando, Ramon Vilanova, and Pedro Balaguer. "Procedure for Cascade Control Systems Design: Choice of Suitable PID Tunings." International Journal of Computers Communications & Control 3, no. 3 (2008): 235. http://dx.doi.org/10.15837/ijccc.2008.3.2392.

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This paper provides an approach for the application of PID controllers within a cascade control system configuration. Based on considerations about the expected operating modes of both controllers, the tuning of both inner and outer loop controllers are selected accordingly. This fact motivates the use of a tuning that, for the secondary controller, provides a balanced set-point / load-disturbance performance. A new approach is also provided for the assimilation of the inner closed-loop transfer function to a suitable form for tuning of the outer controller. Due to the fact that this inevitabl

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Chalardsakul, Tanawat, Chotnarin Piliyasilpa, and Viroch Sukontanakarn. "TMS320F28379D microcontroller for speed control of permanent magnet direct current motor." IAES International Journal of Artificial Intelligence (IJ-AI) 13, no. 3 (2024): 2816. http://dx.doi.org/10.11591/ijai.v13.i3.pp2816-2828.

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<p><span>This paper aims to study the behavior of the <a name="_Hlk169245133"></a>proportional integral derivative (PID) and the fuzzy-based tuning PI-D controller for speed control of a permanent magnet direct current (PMDC) motor. The proposed method used a fuzzy-based tuning PI-D controller with a MATLAB/Simulink program to design and real-time implement a TMS320F28379D microcontroller for speed control of a PMDC motor. The performance of the study designed fuzzy-based tuning PI-D and PID controllers is compared and investigated. The fuzzy logic controller applies th

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Ibrahim, Oladimeji, Sulyman A. Y. Amuda, Olatunji O. Mohammed, and Ganiyu A. Kareem. "Performance Evaluation of Three PID Controller Tuning Algorithm on a Process Plant." International Journal of Electrical and Computer Engineering (IJECE) 5, no. 5 (2015): 1075. http://dx.doi.org/10.11591/ijece.v5i5.pp1075-1082.

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Accurate tuning of controller in industrial process operation is prerequisite to system smooth operation which directly reduce process variability, improved efficiency, reduced energy costs, and increased production rates. Performance evaluation of a model based PID controller tuning algorithm on a chemical process plant is presented in this paper. The control action of three different PID controller tuning algorithms namely; Hagglund-Astrom, Cohen and Coon, and Ziegler-Nichols on the process plant was examined in a closed loop control configuration under normal operating condition and in the

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Gong, Qing Hui, and An Min Zhang. "Construction and Simulation of Fuzzy-PID Controller on Stepping Motor." Applied Mechanics and Materials 401-403 (September 2013): 1670–73. http://dx.doi.org/10.4028/www.scientific.net/amm.401-403.1670.

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In order to improve the performance of stepping motor system, the modern theory of fuzzy control and classical PID control theory are organically combined, the structure of fuzzy PID controller has built,which is suitable for the stepper motor control requirements, and corresponding control rules have designed that have realized the control of stepping motor. MATLAB software is applied for simulation. Comparing the fuzzy self-tuning PID controller with the conventional PID controller, the simulation results that fuzzy parameter self-tuning PID control system has less overshoot response, shorte

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Liu, Bin, Gang Yao, Xiao Bing Xiao, and Xu Sheng Yin. "The Research on Self-Adaptive Fuzzy PID Controller." Applied Mechanics and Materials 373-375 (August 2013): 1462–65. http://dx.doi.org/10.4028/www.scientific.net/amm.373-375.1462.

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The parameters of the traditional proportional-integral-derivative (PID) controller are hard to automatically adjust when the controlled object changes, which controls ineffective for time-varying, nonlinear system. Combine the fuzzy control and PID control, and use self-adaptive fuzzy control to achieve self-tuning PID parameters online. Using matlab simulation system, the results show that the self-adaptive fuzzy PID control effects have been improved than the conventional PID control.

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Al-Araji, Ahmed Sabah. "Applying Cognitive Methodology in Designing On-Line Auto-Tuning Robust PID Controller for the Real Heating System." Journal of Engineering 20, no. 09 (2023): 43–61. http://dx.doi.org/10.31026/j.eng.2014.09.04.

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A novel design and implementation of a cognitive methodology for the on-line auto-tuning robust PID controller in a real heating system is presented in this paper. The aim of the proposed work is to construct a cognitive control methodology that gives optimal control signal to the heating system, which achieve the following objectives: fast and precise search efficiency in finding the on- line optimal PID controller parameters in order to find the optimal output temperature response for the heating system. The cognitive methodology (CM) consists of three engines: breeding engine based Routh-Hu

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Chen, Hao, and Zhuo Qi Li. "Research on Fuzzy Mathematics in PID Control." Applied Mechanics and Materials 608-609 (October 2014): 875–79. http://dx.doi.org/10.4028/www.scientific.net/amm.608-609.875.

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Aiming at the limitation of traditional PID algorithm in the field of control, the fuzzy control theory and traditional PID control algorithm are combined to realize parameter self-tuning function, a fuzzy self-tuning PID controller, and this algorithm is analyzed in-depth study. It provides a new solution of modern industrial control problem that combining with fuzzy control technology and PID control technology. The FPGA has high integration, short development cycle, the characteristics of strong reusability; fuzzy PID controller has a good practical value and optimistic application prospect

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