Relevant bibliographies by topics / On-line tuning PID controller

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  2. Dissertations / Theses
  3. Books
  4. Book chapters
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Academic literature on the topic 'On-line tuning PID controller'

Author: Grafiati
Published: 5 June 2025
Last updated: 24 June 2025

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

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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 simulation results show that the fuzzy self-tuning PID controller not only has the advantages of fuzzy control such as fast, adaptability, etc, but also the characteristics of high accuracy PID control, which make the system has a good control effect.
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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 OPC communication protocol to analyze the transient response of the system. Methodology− The study is carried out in three main phases; it begins with a PD3 SMAR thermal process with connection via OPC; in this phase, the mathematical model of the process is built analytically based on fundamental laws. In the second phase, using an analytical tuning method, the PID control architecture is created on which the online experimentation is carried out. In the third phase, the genetic algorithms for automatic tuning are implemented, extracting performance measures from the PID controller through the transient response of the process and optimally determining the values for the proportional, derivative, and integral parameters. Results− The automatic tuning method was tested with two properly instrumented industrial processes. The potential for application can be seen due to its good result and because it does not require specific mathematical knowledge compared to conventional tuning methods. Conclusions− The automatic tuning method can be used remotely to calculate the optimal parameters of a PID controller. The parameters are calculated from the transient response and the definition of design criteria adaptable to any need for control, response, and process.
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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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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 direction of auto-tuning PID controller was also prospected.
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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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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 change in the speed error (speed error derivative). The output of the FLC, i.e. the parameters of the PID controller, are used to control the speed of the separately excited DC Motor. This study shows that the precisiom feature of the PID controllers and the flexibllity feature of the fuzzy controller are presented in the fuzzy self-tuning PID controller. The fuzzy self – tuning approach implemented on the conventional PID structure improved the dynamic and static response of the system. The salient features of both conventional and fuzzy self-tuning controller outputs are explored by simulation using MATLAB. The simulation results demonstrate that the proposed self-tuned PID controller i.plementd a good dynamic behavior of the DC motor i.e. perfect speed tracking with a settling time, minimum overshoot and minimum steady state errorws.
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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 to the system’s imperfection (i.e., unpredictable duty cycle) and influences the closed-loop performance. The methodology is executed offline; thus, it highlights the applicability of collected BDC motor measurements in time series analysis. The proposed method updates the PID controller gains based on the Simulink ™ controller tuning toolbox. The contribution of this approach is shown in a comparative study that indicates an opportunity to use time series analysis to forecast DC motor parameters, to re-tune PID controller gains, and to obtain similar performance under the same perturbation conditions. The research demonstrates the practical applicability of the proposed method for fine-tuning/re-tuning controllers in real-time. The results show the inclusion of the time series analysis to recalculate controller gains as an alternative for adaptive control.
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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 controller noise gain limits the amount of HO-PID output noise. Therefore, the method can be successfully applied in practice. The work shows that the HO-PID controllers can significantly improve the control performance of various process models compared to the standard PID controllers. Of course, the increased efficiency is limited by the selected noise gain. The proposed tuning method is illustrated on several process models and compared with two other tuning methods for higher-order controllers.
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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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Dissertations / Theses on the topic "On-line tuning PID controller"

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Ngo, Thanh Binh. "Design and creation of control board for drying equipment based on development of a soft self-tuning PID controller." Technische Universität Dresden, 2018. https://tud.qucosa.de/id/qucosa%3A32721.

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This article introduces a versatile control board design that can be used in many drying systems using direct heat transfer solutions in combination with static tray distribution based on development of a flexible self-tuning PID controller. The product is applied for a small oven drying solid waste samples or plant materials for further analysis of some parameters. The control board is built based on the Arduino embedded system using a flexible soft PID (Proportional–Integral–Derivative) controller that can automatically change its gains according to the required temperature thresholds to best meet the setpoint of temperatures. The system has a small steady-state error (SSE), fast response to the setpoints and keep stable with temperature deviation when reaching the required threshold around ± 0.5 0C. In addition, the controller board can operate in a variety of modes, including direct temperature operation, pre-set operation, and switching mode.<br>Bài báo này giới thiệu một thiết kế mạch điều khiển đa năng có thể áp dụng trong nhiều hệ thống sấy sử dụng các giải pháp truyền nhiệt trực tiếp kết hợp phân phối khí kiểu khay tĩnh trên cơ sở phát triển bộ điều khiển PID mềm tự chỉnh linh hoạt. Sản phẩm được ứng dụng cho một mô hình lò nhỏ sấy mẫu chất thải rắn hoặc mẫu thực vật phục vụ các nghiên cứu phân tích thành phần một số chất. Mạch điều khiển được chế tạo trên nền tảng hệ thống nhúng Arduino sử dụng bộ điều khiển PID mềm linh hoạt, có khả năng tự động thay đổi tham số theo ngưỡng nhiệt yêu cầu để đáp ứng nhiệt độ tốt nhất so với ngưỡng nhiệt độ đặt. Hệ thống có độ quá điều chỉnh nhỏ, nhanh đáp ứng tới các ngưỡng đặt và giữ ổn định với sai lệch nhiệt độ khi đạt ngưỡng yêu cầu trong khoảng ±10C. Ngoài ra, bộ điều khiển còn có thể hoạt động theo nhiều chế độ khác nhau, bao gồm hoạt động theo chế độ đặt nhiệt độ trực tiếp, hoạt động theo chu trình đặt trước, và chuyển chế độ hoàn toàn tự động.
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Gaber, Mark Rawi. "Off-line tuning of PID controllers for systems subjected to random disturbances." Thesis, McGill University, 1989. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=61239.

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An off-line method of tuning PID controllers used in process control applications is presented. The plant under consideration is of second order with delay and the loop is presumed to be operating at steady state under the influence of random disturbances. Tuning is performed by minimizing the cost function, namely the integral of squared error, with respect to the tuning parameters. To do this, a second order approximation of the cost function is obtained and minimized using the Newton-Raphson method. System identification is done without interrupting production by introducing test signals of low signal to noise ratio and using a Kalman filter to extract the response. The result is a model composed of Laguerre functions which emulates the frequency response of the system in question. The integral term is found to cause stability problems if left unconstrained because the lag it introduces is not beneficial in the case under consideration. On the other hand, the algorithm behaves well when tuning a PD controller if the Kalman filter yields accurate results because the model obtained is then very similar to the transfer function of interest. The Kalman filter presently used does not adequately model the noise, so its performance hampers proper tuning of the loop.
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Pektas, Seda. "On-line Controller Tuning By Matlab Using Real System Responses." Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/12605596/index.pdf.

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This thesis attempts to tune any controller without the mathematical model knowledge of the system it is controlling. For that purpose, the optimization algorithm of MATLAB&reg<br>6.5 / Nonlinear Control Design Blockset (NCD) is adapted for real-time executions and combined with a hardware-in-the-loop simulation provided by MATLAB&reg<br>6.5 / Real-Time Windows Target (RTWT). A noise-included model of a DC motor position control system is obtained in MATLAB&reg<br>/ SIMULINK first and simulated to test the modified algorithm in some aspects. Then the presented methodology is verified using the physical plant (DC motor position control system) where tuning algorithm is driven mainly by the real system data and the required performance parameters specified by a user defined constraint window are successfully satisfied. Resultant improvements on the step response behavior of DC motor position control system are shown for two case studies.
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Mustafa, Mohd Marzuki bin. "Pole-assignment high order controllers and applications to adaptive control with on-line supervision." Thesis, University of Salford, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.258358.

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Wang, Zimu. "A MODEL OF LINE FOLLOWING ROBOT USING PID CONTROLLER : An Educational Platform Based on LEGO Mindstorms NXT Kit." Thesis, Högskolan i Gävle, Avdelningen för elektronik, matematik och naturvetenskap, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-21428.

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PID controllers are widely used in industrial control systems since it could significantly improve the performance of the systems. It is a basic and important tool for an engineering student.An educational PID controller model using LEGO Mindstorms NXT kit as a line following robot was presented in this thesis. This robot could be controlled by a PC via Bluetooth. MATLAB was used for analyzing data and controlling the robot. A MATLAB Toolbox named “RWTH—Mindstorms NXT Toolbox” was utilized for remote controlling and gathering the feedback data from the robot in real-time via Bluetooth.The algorithm and tuning methods of PID controllers were studied in this thesis. Moreover, the effectiveness of each parameter would be studied by comparing the result of P, PI and PID control type.
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CONGIU, ANDREA. "Novel load identification techniques and a steady state self-tuning prototype for switching mode power supplies." Doctoral thesis, Università degli Studi di Cagliari, 2014. http://hdl.handle.net/11584/266433.

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Control of Switched Mode Power Supplies (SMPS) has been traditionally achieved through analog means with dedicated integrated circuits (ICs). However, as power systems are becoming increasingly complex, the classical concept of control has gradually evolved into the more general problem of power management, demanding functionalities that are hardly achievable in analog controllers. The high flexibility offered by digital controllers and their capability to implement sophisticated control strategies, together with the programmability of controller parameters, make digital control very attractive as an option for improving the features of dcdc converters. On the other side, digital controllers find their major weak point in the achievable dynamic performances of the closed loop system. Indeed, analogto-digital conversion times, computational delays and sampling-related delays strongly limit the small signal closed loop bandwidth of a digitally controlled SMPS. Quantization effects set other severe constraints not known to analog solutions. For these reasons, intensive scientific research activity is addressing the problem of making digital compensator stronger competitors against their analog counterparts in terms of achievable performances. In a wide range of applications, dcdc converters with high efficiency over the whole range of their load values are required. Integrated digital controllers for Switching Mode Power Supplies are gaining growing interest, since it has been shown the feasibility of digital controller ICs specifically developed for high frequency switching converters. One very interesting potential benefit is the use of autotuning of controller parameters (on-line controllers), so that the dynamic response can be set at the software level, independently of output capacitor filters, component variations and ageing. These kind of algorithms are able to identify the output filter configuration (system identification) and then automatically compute the best compensator gains to adjust system margins and bandwidth. In order to be an interesting solution, however, the self-tuning should satisfy two important requirements: it should not heavily affect converter operation under nominal condition and it should be based on a simple and robust algorithm whose complexity does not require a significant increase of the silicon area of the IC controller. The first issue is avoided performing the system identification (SI) with the system open loop configuration, where perturbations can be induced in the system before the start up. Much more challenging is to satisfy this requirement during steady state operations, where perturbations on the output voltage are limited by the regular operations of the converter. The main advantage of steady state SI methods, is the detection of possible non-idealities occurring during the converter operations. In this way, the system dynamics can be consequently adjusted with the compensator parameters tuning. The resource saving issue, requires the development of äd-hocßelf-tuning techniques specifically tailored for integrated digitally controlled converters. Considering the flexibility of digital control, self-tuning algorithms can be studied and easily integrated at hardware level into closed loop SMPS reducing development time and R & D costs. The work of this dissertation finds its origin in this context. Smart power management is accomplished by tuning the controller parameters accordingly to the identified converter configuration. Themain difficult for self-tuning techniques is the identification of the converter output filter configuration. Two novel system identification techniques have been validated in this dissertation. The open loop SI method is based on the system step response, while dithering amplification effects are exploited for the steady state SI method. The open loop method can be used as autotunig approach during or before the system start up, a step evolving reference voltage has been used as system perturbation and to obtain the output filter information with the Power Spectral Density (PSD) computation of the system step response. The use of ¢§ modulator is largely increasing in digital control feedback. During the steady state, the finite resolution introduces quantization effects on the signal path causing low frequency contributes of the digital control word. Through oversampling-dithering capabilities of ¢§ modulators, resolution improvements are obtained. The presented steady state identification techniques demonstrates that, amplifying the dithering effects on the signal path, the output filter information can be obtained on the digital side by processing with the PSD computation the perturbed output voltage. The amount of noise added on the output voltage does not affect the converter operations, mathematical considerations have been addressed and then justified both with a Matlab/Simulink fixed-point and a FPGA-based closed loop system. The load output filter identification of both algorithms, refer to the frequency domain. When the respective perturbations occurs, the system response is observed on the digital side and processed with the PSD computation. The extracted parameters are the resonant frequency ans the possible ESR (Effective Series Resistance) contributes,which can be detected as maximumin the PSD output. The SI methods have been validated for different configurations of buck converters on a fixed-point closed loop model, however, they can be easily applied to further converter configurations. The steady state method has been successfully integrated into a FPGA-based prototype for digitally controlled buck converters, that integrates a PSD computer needed for the load parameters identification. At this purpose, a novel VHDL-coded full-scalable hybrid processor for Constant Geometry FFT (CG-FFT) computation has been designed and integrated into the PSD computation system. The processor is based on a variation of the conventional algorithm used for FFT, which is the Constant-Geometry FFT (CG-FFT).Hybrid CORDIC-LUT scalable architectures, has been introduced as alternative approach for the twiddle factors (phase factors) computation needed during the FFT algorithms execution. The shared core architecture uses a single phase rotator to satisfy all TF requests. It can achieve improved logic saving by trading off with computational speed. The pipelined architecture is composed of a number of stages equal to the number of PEs and achieves the highest possible throughput, at the expense of more hardware usage.
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Chou, Chin Jui, and 周進瑞. "Studies of On-Line PID Controller Tuning Techniques." Thesis, 1993. http://ndltd.ncl.edu.tw/handle/46091694860149878984.

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碩士<br>東海大學<br>化學工程研究所<br>81<br>Three kinds of closed-loop PID tuning techniques including time domain, frequency domain, and cascade control approaches are proposed in this study. Under proportional control, a single dynamic test ( such as step or pulse change ) in the set point is introduced to the system. An identification technique for the underdamped second-order-plus-dead-time model from few data points of the step response curve is developed. The ultimate frequency and gain can then be ob- tained based on the model from the literature. The ultimate frequency and gain can also be obtained from the pulse (or step) transient by the Fourier integral transform without any parametric model. Thus, PID controller settings can be found from the ultimate frequency and gain by the Ziegler- Nichols rules. On the other hand, a procedure for tuning simultaneously the primary and secondary controllers of cascade control systems based on a single dynamic testing using the Ziegler-Nchols rules is also proposed. Simulation results have demonstrated that the proposed techniques can provide good values of PID controller settings despite unanticipated process noise or load disturbances and is insensitivity to the used control- ler gains.
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Chen, Ping-Lin, and 陳秉霖. "On-line Tuning PID Controller Based on Swarm Intelligence." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/03052568016266430530.

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碩士<br>國立東華大學<br>電機工程學系<br>99<br>The main focus of this thesis is to design the intelligent controller, and discuss the system tracking control problem with disturbance influence. This thesis presents a Particle Swarm Optimization (PSO) approach for online tuning Proportional Integral Derivative (PID) controller. There is a great deal of general literature on PID controller with ignoring the disturbance interference. However, in practical applications, the ability of interference avoidance of PID controller should be considered in evaluating the performance of system response. In this research, using PSO online tuning mechanism, PID controller can track the input signal effectively even though the setpoint changes and load disturbance influences. The simulation results describe that the proposed method is able to obtain the good performance and stability.
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Huang, Tien-Chih, and 黃天志. "On-Line Self-Tuning PID Controller Design Based on Neural Network Models." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/50358439153686754176.

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碩士<br>中原大學<br>化學工程研究所<br>90<br>The inherent time-varying nonlinearity and complexity usually exist in chemical processes. The design process would be significantly deviated from the normal operating condition when only a slight disturbance occurs. Accordingly, the design of control structure should be properly adapted based on the instantaneous state. In this research, an improved conventional PID control scheme using linearization through a specified neural network is developed to control nonlinear processes. An input-driven output neural network ARX model trained by Levenberg-Marquardt algorithm is introduced in the model design. The linearization of the neural network model will be proposed to extract the linear model for updating the controller parameters. In the scheme of the optimal tuning PID controller, the concept of general minimum variance is presented and a constrained criterion is also considered. Like gain scheduling, the control system of the proposed method at each time interval is chosen from a set of predefined linearized dynamic model. Unlike gain scheduling control, the control parameters based on the neural network model have an infinite scheduling resolution when using a neural network for updating parameters. To apply the proposed method to most of the practical application problems, several variations of the proposed method, including the momentum filter, the updating criterion and the step size of the control action, are presented to provide significant improvement and make the proposed algorithm more practical. The proposed method has two advantages. First, less computation of linear adaptive control scheme is used. Second, the nonlinear characteristics of neural networks can be incorporated into the control design. To demonstrate the potential applications of the proposed strategies, several problems, including batch reactors and pH neutralization processes, are applied.
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Chou, Yu-Wei, and 邱昱瑋. "On-line PID-Controller Parameter Tuning Using SPSA for Wind Turbine Yaw Control." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/39865824294741711926.

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碩士<br>中原大學<br>電機工程研究所<br>95<br>It’s a very important and worthy to discuss how to use active yaw control to position the maximum power point with a horizontal axis wind turbine which usually needs wind direction sensor to position. The mountain climbing method based on measurement of the voltage and current from wind-turbine generator system (WTGS) to calculate the power for the maximum power point without any wind direction sensors is proposed. It’s verified by computer simulations and experiments. An on-line parameter tuning PID controller for DC motor to position the wind turbine is also presented. The on-line parameter tuning policy is based on the Simultaneous Perturbation Stochastic Approximation (SPSA) technique. Three PID parameters can tuned consecutively until the optimal values are attained. The proposed approach has been confirmed by computer simulations and experiments. The PID controller is also combined with the mountain climbing method to increase system’s stability and locate the maximum power point effectively. Finally, the FPGA is used to realize the proposed method.
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Books on the topic "On-line tuning PID controller"

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United States. Army Aviation Research and Technology Activity. Propulsion Directorate. and United States. National Aeronautics and Space Administration., eds. An expert system to perform on-line controller tuning. National Aeronautics and Space Administration, 1990.

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Book chapters on the topic "On-line tuning PID controller"

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Arun, M. K., U. Biju, Neeraj Nair Rajagopal, and V. Bagyaveereswaran. "Optimal Tuning of Fractional-Order PID Controller." In Proceedings of the International Conference on Soft Computing Systems. Springer India, 2015. http://dx.doi.org/10.1007/978-81-322-2671-0_38.

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Adhikari, Nikhileshwar Prasad, and Amit Gupta. "PID Controller Tuning Using Soft Computing Techniques." In Proceedings of All India Seminar on Biomedical Engineering 2012 (AISOBE 2012). Springer India, 2012. http://dx.doi.org/10.1007/978-81-322-0970-6_31.

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Papadopoulos, Konstantinos G. "Changes on the Current State of the Art." In PID Controller Tuning Using the Magnitude Optimum Criterion. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07263-0_8.

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Yin, Jianchuan, Gexin Bi, and Fang Dong. "On-Line Tuning of a Neural PID Controller Based on Variable Structure RBF Network." In Advances in Neural Networks – ISNN 2009. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01510-6_124.

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Tello-Rdz, Heberi R., Luis M. Torres-Treviño, and Angel Rodríguez-Liñan. "Off-line Tuning of a PID Controller Using Type-2 Fuzzy Logic." In Advances in Computational Intelligence. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-62434-1_22.

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Chen, Le, Baoming Ge, and Aníbal T. de Almeida. "Self-tuning PID Temperature Controller Based on Flexible Neural Network." In Advances in Neural Networks – ISNN 2007. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-72383-7_18.

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Suguna, A., S. N. Deepa, and N. Rajasingam. "Modeling and Tuning of PID Controller for Continuous Stirred Tank Reactor." In International Conference on Artificial Intelligence for Smart Community. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-2183-3_77.

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Zhao, Jun, Tianpeng Li, and Jixin Qian. "Application of Particle Swarm Optimization Algorithm on Robust PID Controller Tuning." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11539902_118.

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Su, Kuifeng, Tianqing Chang, Bin Zhu, and Bin Han. "PID Tuning for LOS Stabilization System Controller Based on BBO Algorithm." In Proceedings of the 2015 Chinese Intelligent Automation Conference. Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-46463-2_54.

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Xu, Ping, Geng Li, and Kai Wang. "Self Tuning of PID Controller Based on Simultaneous Perturbation Stochastic Approximation." In Lecture Notes in Electrical Engineering. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27287-5_105.

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Conference papers on the topic "On-line tuning PID controller"

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Nam, Ngo Hong, Truong Nguyen Luan Vu, and Vo Lam Chuong. "PID Controller Tuning Rules for Feed Drive Systems." In 2024 7th International Conference on Green Technology and Sustainable Development (GTSD). IEEE, 2024. http://dx.doi.org/10.1109/gtsd62346.2024.10675245.

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Bhuvaneswary, N., B. Gowtham Reddy, K. Praveen Kumar Reddy, M. Vishnu Vardhan, K. Jagadeesh Kumar, and M. Anudeep Venkat Reddy. "Quadcopter with Fuzzy Logic based Self-Tuning PID Controller." In 2025 5th International Conference on Trends in Material Science and Inventive Materials (ICTMIM). IEEE, 2025. https://doi.org/10.1109/ictmim65579.2025.10988349.

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Shah, Udayan, Nitesh Kumar Soni, Mitram Pandey, Rajveer Singh Jadon, and Yash Bairagi. "Elevating BLDC Motor Performance with Precision PID Controller Tuning." In 2024 IEEE Third International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES). IEEE, 2024. http://dx.doi.org/10.1109/icpeices62430.2024.10719210.

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Doicin, Bogdan, Marian Popescu, and Cristian Patrascioiu. "PID Controller optimal tuning." In 2016 8th International Conference on Electronics, Computers and Artificial Intelligence (ECAI). IEEE, 2016. http://dx.doi.org/10.1109/ecai.2016.7861175.

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Koivo, H., and J. Sorvari. "On-line tuning of a multivariable PID-controller for robot manipulators." In 1985 24th IEEE Conference on Decision and Control. IEEE, 1985. http://dx.doi.org/10.1109/cdc.1985.268765.

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Gade, S. S., S. B. Shendage, and M. D. Uplane. "On Line Auto Tuning of PID Controller Using Successive Approximation Method." In 2010 International Conference on Recent Trends in Information, Telecommunication and Computing (ITC 2010). IEEE, 2010. http://dx.doi.org/10.1109/itc.2010.22.

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Paulusova, Jana, Lukas Orlicky, and Maria Dubravska. "Self-tuning fuzzy PID controller." In 2013 International Conference on Process Control (PC). IEEE, 2013. http://dx.doi.org/10.1109/pc.2013.6581427.

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Sukede, Abhijeet Kishorsingh, and Jasmineet Arora. "Auto tuning of PID controller." In 2015 International Conference on Industrial Instrumentation and Control (ICIC). IEEE, 2015. http://dx.doi.org/10.1109/iic.2015.7150979.

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Fabijanski, Pawel, and Ryszard Lagoda. "On-line PID controller tuning using genetic algorithm and DSP PC board." In 2008 13th International Power Electronics and Motion Control Conference (EPE/PEMC 2008). IEEE, 2008. http://dx.doi.org/10.1109/epepemc.2008.4635574.

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Jones, K. O. "On-line control of dissolved oxygen concentration using an automatic tuning PID controller." In International Conference on Control '94. IEE, 1994. http://dx.doi.org/10.1049/cp:19940279.

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Reports on the topic "On-line tuning PID controller"

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Lai, Chin-Ta, and Joel Conte. Dynamic Modeling of the UC San Diego NHERI Six-Degree-of-Freedom Large High-Performance Outdoor Shake Table. Pacific Earthquake Engineering Research Center, University of California, Berkeley, CA, 2024. http://dx.doi.org/10.55461/jsds5228.

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Abstract:
The UC San Diego Large High-Performance Outdoor Shake Table (LHPOST), which was commissioned on October 1, 2004 as a shared-use experimental facility of the National Science Foundation (NSF) Network for Earthquake Engineering Simulation (NEES) program, was upgraded from its original one degree-of-freedom (LHPOST) to a six degree-of-freedom configuration (LHPOST6) between October 2019 and April 2022. The LHPOST6 is a shared-use experimental facility of the NSF Natural Hazard Engineering Research Infrastructure (NHERI) program. A mechanics-based numerical model of the LHPOST6 able to capture the dynamics of the upgraded 6-DOF shake table system under bare table condition is presented in this report. The model includes: (i) a rigid body kinematic model that relates the platen motion to the motions of components attached to the platen, (ii) a hydraulic dynamic model that calculates the hydraulic actuator forces based on all fourth-stage servovalve spool positions, (iii) a hold-down strut model that determines the pull-down forces produced by the three hold-down struts, (iv) a 2-D and various 1-D Bouc-Wen models utilized to represent the dissipative forces in the shake table system, and (v) a 6-DOF rigid body dynamic model governing the translational and rotational motions of the platen subjected to the forces from the various components attached to the platen. In this report, the rigid body dynamics is studied utilizing the platen twist (combination of platen translational and rotational velocities) and wrench (combination of force and moment resultants acting on the platen) following principles from the robotic analysis literature. The numerical model of the LHPOST6 is validated extensively using experimental data from the acceptance tests performed following the shake table upgrade, and the model predictions of the shake table system response are found to be consistently in very good agreement with the experimental results for tri-axial and six-axial earthquake shake table tests. The validated mechanics-based numerical model of the LHPOST6 presented in this study can be coupled with finite element models of shake table test specimens installed on the rigid platen to study the dynamic interaction between the shake table system and the specimens. Another important potential use of the model is to improve the motion tracking performance of the LHPOST6 through either off-line tuning of the shake table controller and/or development of more advanced shake table controllers.
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