Optimal Control of Automatic Voltage Regulator System with Coronavirus Herd Immunity Optimizer Algorithm-Based PID plus Second Order Derivative Controller

Emiroğlu, Selçuk; Gümüş, Talha Enes

doi:10.21541/apjess.1149455

Cited by 4 publications

(3 citation statements)

References 23 publications

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“…A brief structural block diagram of an open-loop hydraulic synchronizer is shown in Figure 3 attached below, and a closed-loop hydraulic synchronizer is shown in Figure 4 attached. For the operating conditions of a twin cylinder hydraulic forging press, in the open-loop mode, there is no feedback compensation to solve the problems of hydraulic oil leakage in the hydraulic cylinder, hydraulic cylinder processing accuracy differences, uneven load, etc [5] . Therefore, for the reason of higher accuracy requirements, this project intends to solve this problem through hydraulic closed-loop.…”

Section: Figure 2 Reasons For Two Cylinders Not Synchronizedmentioning

confidence: 99%

“…The traditional PID controller is difficult to make secondary adjustment after its parameters are rectified, and it is difficult to make effective control when the system parameters are changed. The synchronous position control algorithm is the core of determining the control performance and is the focus of this chapter [9] . Therefore, in this paper, an immune neural network control method is proposed for the characteristics of this system.…”

Section: Immune Neural Network Principle and Controller Designmentioning

confidence: 99%

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The application of immune neural network in the synchronous PID control system of double-cylinder hydraulic press

Liu

2023

International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2023)

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Hydraulic technology has been widely used in machinery manufacturing, and synchronization control is an important issue in the field of hydraulics. With the continuous development of the aerospace industry, the application of double-cylinder hydraulic technology in modern machinery is becoming more and more widespread, metallurgical equipment, metallurgical equipment, machine tools and other high-precision actuators, as well as the application of double-cylinder electro-hydraulic servo systems, are subject to inconsistent movements. As a result of non-uniform load, leakage, friction, resistance, manufacturing precision, hydraulic coil difference, structural elastic deformation, and so on. Therefore, the study of hydraulic synchronization control technology is especially important. This paper presents an immune neural network based PID controller to improve the synchronization precision of a two-cylinder hydraulic system. On the basis of the above, a new design method for the valve control cylinder of a double-cylinder forging hydraulic press is presented. In order to overcome the drawback that the conventional PID controller cannot be adaptively adjusted, the immune algorithm is adopted to monitor the operation condition of the system, and the PID parameters are dynamically adjusted on this basis, so as to improve the timeliness and effectiveness of the PID control; in the immune algorithm, the accuracy of the adjustment function construction will have a great impact on the accuracy of its construction. The validity and validity of the proposed method have been verified by simulation experiments.

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Section: Figure 2 Reasons For Two Cylinders Not Synchronizedmentioning

confidence: 99%

Section: Immune Neural Network Principle and Controller Designmentioning

confidence: 99%

The application of immune neural network in the synchronous PID control system of double-cylinder hydraulic press

Liu

2023

International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2023)

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“…The controller is designed to strengthen transient and robustness performance, and simulation results showed better transient response characteristics than other controllers. Another PIDD 2 controller tuned with the coronavirus herd immunity optimiser algorithm is presented in [10] to achieve optimal system control. The practical implementation of this controller exhibited superior performance in ITAE and ISAE compared to PIDD 2 controllers tuned with other algorithms.…”

Section: Power System Applications 1avr Systemsmentioning

confidence: 99%

Design of PIDDα Controller for Robust Performance of Process Plants

Fawwaz,

Bingi,

Ibrahim

et al. 2023

Algorithms

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Managing industrial processes in real-time is challenging due to the nonlinearity and sensitivity of these processes. This unpredictability can cause delays in the regulation of these processes. The PID controller family is commonly used in these situations, but their performance is inadequate in systems and surroundings with varying set-points, longer dead times, external noises, and disturbances. Therefore, this research has developed a novel controller structure for PIDDα that incorporates the second derivative term from PIDD2 while exclusively using fractional order parameters for the second derivative term. The controllers’ robust performance has been evaluated on four simulation plants: first order, second order with time delay, third-order magnetic levitation systems, and fourth-order automatic voltage regulation systems. The controllers’ performance has also been evaluated on experimental models of pressure and flow processes. The proposed controller exhibits the least overshoot among all the systems tested. The overshoot for the first-order systems is 9.63%, for the third-order magnetic levitation system, it is 12.82%, and for the fourth-order automatic voltage regulation system, it is only 0.19%. In the pressure process plant, the overshoot is only 4.83%. All controllers for the second-order systems have a time delay, while the flow process plant has no overshoot. The proposed controller demonstrates superior settling times in various systems. For first-order systems, the settling time is 14.26 s, while in the pressure process plant, the settling time is 8.9543 s. Similarly, the proposed controllers for the second-order system with a time delay and the flow process plant have the same settling time of 46.0495 s. In addition, the proposed controller results in the lowest rise time for three different systems. The rise time is only 0.0075 s for the third-order magnetic levitation system, while the fourth-order automatic voltage regulation system has a rise time of 0.0232 s. Finally, for the flow process plant, the proposed controller has the least rise time of 25.7819 s. Thus, in all the cases, the proposed controller results in a more robust controller structure that provides the desired performance of a regular PIDD2 controller, offering better dynamic responses, shorter settling times, faster rise times, and reduced overshoot. Based on the analysis, it is evident that PIDDα outperforms both PID and FOPID control techniques due to its ability to produce a more robust control signal.

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Optimal Choice of Parameters for Coronavirus Herd Immunity Optimizer

Liu,

Qi,

et al. 2024

Lecture Notes in Electrical Engineering

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Optimal Control of Automatic Voltage Regulator System with Coronavirus Herd Immunity Optimizer Algorithm-Based PID plus Second Order Derivative Controller

Cited by 4 publications

References 23 publications

The application of immune neural network in the synchronous PID control system of double-cylinder hydraulic press

The application of immune neural network in the synchronous PID control system of double-cylinder hydraulic press

Design of PIDDα Controller for Robust Performance of Process Plants

Optimal Choice of Parameters for Coronavirus Herd Immunity Optimizer

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