Research on Improved Auto-Tuning of a PID Controller Based on Phase Angle Margin

Zeng, Deliang; Zheng, Yadan; Luo, Wenxin; Hu, Yong; Cui, Qingru; Li, Qing; Chen, Peng

doi:10.3390/en12091704

Cited by 28 publications

(10 citation statements)

References 12 publications

(9 reference statements)

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“…It relies on describing nonlinear function analysis, and so frequency limit cycles are common. The accuracy of its identified critical frequency point of oscillation is still a subject of active research [47], [48]. Also, notable in the model-free category, are design methods which explicitly minimize a cost function for real-time optimization, such as the unfalsified method, iterative feedback tuning (IFT) [49], iterative learning control (ILC) [50], and extremum-seeking method summarized in [32].…”

Section: Related Workmentioning

confidence: 99%

"Closed Proportional-Integral-Derivative-Loop Model" Following Control

Somefun,

Akingbade,

Dahunsi

2020

Preprint

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The proportional-integral-derivative (PID) control law is often overlooked as a computational imitation of the critic control in human decision. This paper provides a formulation to remedy this problem. Further, based on the characteristic settling-behaviour of dynamical systems, the "closed PID-loop model" following control (CPLMFC) method is introduced for automatic PID design. Also, a method for closed-loop settlingtime identification is provided. The CPLMFC algorithm and some recommended guidelines are given for setting the critic weights of the PID. Finally, two representative case-studies are simulated. Both the theoretical results and simulation results (via performance indices) illustrate that the CPLMFC can guarantee both accurate and stable closed-loop adaptive PID control performance in real-time.

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Section: Related Workmentioning

confidence: 99%

"Closed Proportional-Integral-Derivative-Loop Model" Following Control

Somefun,

Akingbade,

Dahunsi

2020

Preprint

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“…Recently, several closed-loop test experiment based controller tuning approaches have been proposed to alleviate the shortcoming of the Z-N method (Shamsuzzoha, 2013;Jeng & Ge, 2016;Zeng et al, 2019). The aforementioned literature has addressed the closed-loop test experiment based tuning of the controller for unity feedback systems, but using closed-loop test experiment based design methods for the cascade control system (CCS) has received less attention.…”

Section: Introductionmentioning

confidence: 99%

Closed Loop Tuning of Cascade Controllers Based on Setpoint Experiment

Siddiqui

Anwar

Laskar

et al. 2020

Journal of Engineering Research is an international, peer-revie

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This study presents online PI/PID controller tuning rules for cascade control configuration. The necessary process data are determined with the help of a simple setpoint experiment in a single closed-loop mode with the proportional controller only. The obtained process data is recorded in terms of the overshoot, controller gain, peak time, and relative output change. The data is then utilized to establish a correlation with PI/PID settings through simulations. Further, the proposed PI/PID controller tuning rule for a single loop has been extended to the cascade control configuration. The inner loop controller is tuned first, and then the primary loop is tuned by considering a well-tuned inner loop as a part of the primary plant. Finally, simulation examples demonstrate that the proposed method delivers significant disturbance rejection and better setpoint response when compared to the recently reported methods from the literature. The proposed method is also able to deliver stable closed-loop performances when subjected to large parametric uncertainties and measurement noise.

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“…The control system for the driving pressure of the F/H is currently operated by a PI controller and is presented in section 4.1. The PI control method is used in many types of power plants, such as nuclear (Zarei, 2018;Lamba, Singla & Sondhi, 2017), solar (Beschi, Padula & Visioli, 2016;Rahman, Saikia & Sinha, 2016), and thermal power plants (Zeng et al, 2019) because it involves a simple structure which is easy to implement and provides stable control.…”

Section: Introductionmentioning

confidence: 99%

Development of PINN Controller for Fuel Handling System of Pressurized Heavy Water Reactors

Lim¹,

Park²,

Chong³

2020

STUD INFORM CONTROL

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The required operating pressure of the Wolsong nuclear power plant is currently controlled by a proportional integral (PI) controller. The PI controller has a simple structure and was designed to meet requirements through gain setting. However, these control requirements can be difficult to meet without properly adjusting the gain when certain parameters change, such as the wear and tear in the valves or pipes. To solve these problems, it is important to dynamically change the PI controller gain or compensate for the PI controller output. The purpose of this study is to help design a controller that is capable of providing stable control in order to reduce errors regardless of parameter changes. The proposed PI neural network (PINN) control technique involves a PI controller and a neural network controller combined in parallel. The neural network component which is designed to be robust compensates the output of the controller for changes in the above-mentioned parameters. Because assessing the controller performance straightforwardly in real-time processes can be difficult, a simulator model was developed based on real-time processes, and it showed changes in the parameters involved. The results confirmed that the proposed PINN controller reduced the instability of the fuel supply machine and, hence the aforementioned problem could be properly controlled.

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Research on Improved Auto-Tuning of a PID Controller Based on Phase Angle Margin

Cited by 28 publications

References 12 publications

"Closed Proportional-Integral-Derivative-Loop Model" Following Control

"Closed Proportional-Integral-Derivative-Loop Model" Following Control

Closed Loop Tuning of Cascade Controllers Based on Setpoint Experiment

Development of PINN Controller for Fuel Handling System of Pressurized Heavy Water Reactors

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