Design and Implementation of Fuzzy-based Fine-tuning PID Controller for Programmable Logic Controller

Desalination plants have an important concern regarding controlling the permeate flow rate and pH during operability. This paper proposes the proportional integral derivative (PID) control design using modified Particle Swarm Optimization (PSO) techniques called autonomous groups PSO (AGPSO) in the two-input two-output (TITO) RO desalination plant to control the permeate flow rate and pH. Here, three different versions (AGPSO1, AGPSO2, and AGPSO3) of the AGPSO algorithm are utilized to design PID control for the same TITO plant. In addition, an integral time absolute error (<inline-formula> <tex-math notation="LaTeX">$J_{\mathrm {ITAE}}$ </tex-math></inline-formula>) based objective function is utilized to design a PID controller. The simulation results suggest that the proposed controller designs are flexible, self-tuning, and have stable characteristics, while the AGPSO3-PID control design attained a robust design for optimum tuning compared to existing improved grey wolf optimization PID (IGWO-PID) and other versions of AGPSO based PIDs (AGPSO1-PID, AGPSO2-PID). The design of AGPSO-PID achieved a minimum objective function than existing IGWO-PID and other versions of AGPSO based PIDs &#x007B;AGPSO1-PID, AGPSO2-PID&#x007D;. Finally, the proposed controller designs outperform the existing IGWO-PID design in literature in terms of control performance, demonstrating a precise control for and the improvement of plant performance.

This study presents the development of dead-time compensator with Proportional Integral-Derivative (PID) controller and their implementation in real-time using the Programmable Logic Controller (PLC) on a heater-furnace system that constitute the temperature process. Though PID controller is effective to most of the processes, it has draw backs when used to control the processes with significant dead time. Therefore to eliminate the effects of long dead time, the dead-time compensator combined with PID is proposed. The control equation for the proposed dead time compensator is developed using the mathematical model of heater-furnace system and ladder logic program is created in GE Fanuc Versamax PLC. The PID controller is tuned using process reaction curve method and programmed in PLC. The proposed controller has an outer loop control mechanism with dead time compensator which feeds the inner loop PID controller. The effects of dead time on the performance of PID controller are eliminated through the outer loop control mechanism whose output does not contain modelling errors. The results of the proposed dead-time compensator with PID are compared with the results of the conventional PID controller without dead time compensation for both steady state response and servo-regulatory response. The results of the proposed controller show better improvement in the time domain specifications compared to conventional PID controller.

HVDC power transmission systems can overcome some limitations inherent with AC power transmission systems such as transmission over long distance and transmission with cable. One aspect of importance is the improvement in stability achieved with AC-DC power transmission. In this paper a methodology for the optimal proportional integral derivative (PID) controller design using the modified genetic algorithm (MGA) is proposed to improve the transient stability of AC-DC power systems after faults. This study consists of the formulation of load-flow calculation, basic controls on HVDC transmission system, mathematical model selection for stability analysis, and supplementary signal control by an optimal PID controller using the MGA. The proposed method is verified using computer simulation. The results show the application of the MGA-PID controller in AC-DC power systems has improved the transient stability. The PID controller design using MGA method has been shown to be advantageous when applied for the AC-DC power systems.

This paper presents the effect of Variable Damping Ratio on design of Proportional Integral Derivative (PID) Controller. This novel method is very useful because of their successful practical application, robustness and simplicity. The most popular and widely used controllers in industries are PID controllers. To find appropriate parameters, many design methods have been proposed for PID controller with having its own merits and demerits. However, it is still not easy to find appropriate parameters for the PID controllers. In this paper, PID having variable Damping ratio is developed to improve the performance of the controller. By using this method there is a 60% saving in settling time as compared to the method proposed by Ziegler Nicholas and 84.6% saving settling time as compared to technique proposed by Salem. Our method is independent of maximum overshoot which is distinguishable advantage which increases the performance of system. Based on the mathematical model of the system, controller is designed and is estimated by the MATLAB version 2013. Data for model estimation is taken from an experimental works, the performance has improved significantly of the PID controller having variable damping ratio compare to conventional PID controller.

This chapter examines the proportional integral derivative (PID) controller design. It introduces the idea of disturbance estimation that leads to an equivalent PI control system. The mathematical model used in the chapter is a first order model. For systems with higher order transfer functions, approximation is required. To design a PID controller using the estimation based approach, a second order transfer function is considered. The chapter presents the MATLAB tutorial for the implementation of disturbance observer‐based PID controller. This implementation contains the anti‐windup mechanism when the control signal reaches its maximum or minimum values. The embedded PID controller via estimation is used in the simulation studies within the Simulink environment. The chapter also explains resonant controller design and implementation with anti‐windup mechanism using the disturbance estimation approach. It presents an example to illustrate the disturbance observer‐based resonant controller design.

A fractional-order fuzzy proportional integral derivative (PID) controller is a controller that combines the benefits of fractional calculus and fuzzy logic with the conventional PID controller. In this paper, a four-stage optimization algorithm is proposed for the design of a Type-2 Fuzzy fractional-order PID controller based on the Fourier Series Method (FSM). Three distinct control structures are introduced: Type-2 fuzzy fractional PD + fractional PI controller, Type-2 fuzzy fractional PID, and Type-2 fuzzy fractional PD + Type-2 fuzzy fractional PI controller. In addition to a modified multi-performance criterion cost function, four integral performance criteria are employed as cost functions for each stage. The suggested algorithm avoids the utilization of the approximation equivalent for the fractional-order system and instead employs FSM. Furthermore, the approach optimizes the nonlinearity within the upper membership function (UMF) and the uncertainty range through the lower membership function, as opposed to arbitrary selection. By considering variations in the membership functions, the outcomes exhibit a superior response compared to previous investigations. The results of the three control structures are compared with the traditional PID controller, and simulation results demonstrate the feasibility of this technique. The findings suggest that by optimizing different integral performance criteria using this design technique, controllers for both integer and fractional-order plants can yield favorable step responses. The proposed algorithm is validated by comparing its step response performance with that of previous research, followed by a discussion on sensitivity analysis and computational requirements.

PID controller has been widely used in many different areas such as power systems, drives control, automotive mechatronics, aerospace, process control, and robotics. Recently, FPGA (field programmable gate array) has become an alternative solution for the realization of digital control algorithm systems. In this paper FPGA-based incremental PID (Proportional, Integral, Derivative) controller is designed and simulated. After the analysis of PID control algorithm, VerilogHDL language is used to design the software programs. Simulation results show the effectiveness and feasibility of the proposed method.

Landing gear systems are an essential component of any aircraft, requiring precision and reliability to ensure safe operation. This research advances previous work on landing gear automation that utilized hydraulic systems with an electrical interface. It introduces an improved landing gear design by integrating Programmable Logic Controller (PLC) technology. Automation ensures smooth, efficient, and reliable retraction and deployment, enhancing overall performance, safety, and reliability. At the heart of the research is a PLC-based framework that controls landing gear actuation with exceptional precision. The modular, scalable design allows adaptation to different aircraft sizes and configurations, making it versatile for various applications. This flexibility supports both educational demonstrations and potential integration into more advanced aerospace projects. The research incorporates a Proportional-Integral-Derivative (PID) controller alongside PLC technology to enhance system performance. The PID controller refines actuator movement by dynamically adjusting hydraulic pressure and control signals based on real-time feedback. This integration ensures smoother transitions, minimizes mechanical stress, and enhances stability under varying conditions. By leveraging PLC and PID control, the system achieves optimal responsiveness and precision, improving safety and efficiency. The primary objective of this research is to serve as an educational tool, bridging the gap between theoretical concepts and practical engineering applications. It provides researchers with hands-on experience in advanced automation technology. Experimentation with this system deepens understanding of automated control systems and their role in modern aerospace engineering. The demonstration model offers an accessible platform to explore automation principles and their impact on traditional mechanical systems in aviation. This research also emphasizes simplicity, efficiency, and reliability. By focusing on core landing gear functions, it demonstrates how automation can streamline processes. PLC technology improves operational efficiency, reduces manual input, and ensures consistent performance. The PID controller further enhances adaptability by fine-tuning system responses for precise actuation under different loads and environmental conditions. While primarily educational, this research sets the stage for advancements in intelligent landing gear systems. Its modular design ensures compatibility with future technological innovations, making it a valuable foundation for ongoing aerospace automation research. Integrating PLC with PID control also creates opportunities for advanced fault detection, predictive maintenance, and adaptive control algorithms in future implementations. In conclusion, this research represents a forward-thinking approach to aerospace engineering, emphasizing automation’s role in improving safety, reliability, and efficiency. By combining cutting-edge technology with practical application, it addresses current challenges and inspires future aviation innovations. This study contributes to the development of smarter, safer, and more efficient aircraft systems, offering significant value for education, research, and technological advancement.

An adaptive Fuzzy logic-based approach to PID control of steam turbines in solar applications

In this paper, digital proportional-integral-derivative (PID)-type and fuzzy-type controllers are compared for application to the buck and boost dc-dc converters. Comparison between the two controllers is made with regard to design methodology, implementation issues, and experimentally measured performance. Design of fuzzy controllers is based on heuristic knowledge of converter behavior, and tuning requires some expertise to minimize unproductive trial and error. The design of PID control is based on the frequency response of the dc-dc converter. Implementation of linear controllers on a digital signal processor is straightforward, but realization of fuzzy controllers increases computational burden and memory requirements. For the boost converter, the performance of the fuzzy controller was superior in some respects to that of the PID controllers. The fuzzy controller was able to achieve faster transient response in most tests, had a more stable steady-state response, and was more robust under some operating conditions. In the case of the buck converter, the fuzzy controller and PID controller yielded comparable performances.

The most widely used control strategy in industry is proportional integral derivative (PID) controller. The popularity of PID controllers can be attributed partly to their robust performance in a wide range of operating conditions and partly to their functional simplicity. One of the application is to control arm robot manipulator model by using DC servo motor as actuator. This paper presents design of PID controller of DC servo motor using automated PID tuning by sisotool for higher order system and implement to the Arduino Mega 2560 via potentiometer by using Simulink Support Package for Arduino Hardware in MATLAB/Simulink. A better design of controller using fuzzy logic controller (FLC) is proposed. Simulation results are demonstrated. Performance analysis shows the effectiveness of the proposed Fuzzy logic controller as compared to the PID controller.

Design of Optimal PID Control with a Sensitivity Function for Resonance Phenomenon-involved Second-order Plus Dead-time System

The increasing use of battery-powered electronic devices necessitates efficient and fast charging solutions. This research aims to optimize battery charging at a charging station using the Maximum Power Point Tracking (MPPT) method integrated with Proportional Integral Derivative (PID) control. This method is chosen to address overshoot issues and speed up the stabilization process. The study begins with a literature review to understand the basic theory of MPPT optimization and PID control. Subsequently, hardware and software for the battery charging station were designed and developed. An Arduino ATMega328 microcontroller was used as the main controller, with an LCD to display charging information. Tests were conducted on 12V batteries with capacities of 5Ah and 9Ah. The results showed that using PID control in MPPT optimization successfully increased battery charging efficiency. The fastest charging duration was achieved for a 12V 5Ah battery with parameters Kp=6, Ki=9, and Kd=4, where the battery was fully charged in 19 minutes, and for a 12V 9Ah battery with parameters Kp=5, Ki=3, Kd=1, where the battery was fully charged in 27 minutes. Conversely, the longest charging duration occurred for a 12V 5Ah battery with parameters Kp=5, Ki=3, Kd=1, where the battery was fully charged in 34 minutes, and for a 12V 9Ah battery with parameters Kp=2, Ki=5, Kd=1, with a charging time of 38 minutes. The designed system was able to reduce input current and increase input voltage to reach the 14.5V set point, ensuring that there was no excessive voltage and current that could prolong battery life. This research demonstrates that the PID method in MPPT optimization is effective in accelerating and optimizing battery charging. Future research is expected to further develop this method to improve battery charging efficiency and duration. Keywords: MPPT, PID, Optimization, Battery Charger, Optimal, PWM ABSTRAK Penggunaan perangkat elektronik yang bertenaga baterai semakin meningkat memerlukan solusi pengisian yang efisien dan cepat. Penelitian ini bertujuan untuk mengoptimalkan pengisian baterai pada stasiun pengisian dengan menggunakan metode Maximum Power Point Tracking (MPPT) yang diintegrasikan dengan kontrol Proportional Integral Derivative (PID). Metode ini dipilih untuk mengatasi masalah overshoot dan mempercepat waktu menuju keadaan stabil. Penelitian dimulai dengan studi literatur untuk memahami teori dasar optimasi MPPT dan kontrol PID. Selanjutnya dirancang dan dibuat perangkat keras serta perangkat lunak untuk stasiun pengisian baterai. Mikrokontroler Arduino ATMega328 digunakan sebagai pengendali utama dengan LCD untuk menampilkan informasi pengisian. Pengujian dilakukan pada baterai aki 12V dengan kapasitas 5Ah dan 9Ah. Hasil pengujian menunjukkan bahwa penggunaan kontrol PID pada optimasi MPPT berhasil meningkatkan efisiensi pengisian baterai. Durasi pengisian yang paling cepat dicapai baterai 12V 5ah dengan parameter Kp=6 Ki=9 dan Kd=4 dimana baterai terisi penuh dalam waktu 19 menit dan baterai 12V 9ah dengan parameter Kp=5, Ki=3, Kd=1 dimana baterai terisi penuh dalam waktu 27 menit. Sebaliknya durasi pengisian terlama terjadi pada baterai 12V 5ah dengan parameter Kp=5, Ki=3, Kd=1 baterai terisi penuh dalam waktu 34 menit dan baterai 12V 9ah dengan parameter Kp=2 Ki=5, Kd=1 dengan waktu pengisian 38 menit. Sistem yang dirancang mampu mengurangi arus input dan meningkatkan tegangan input untuk mencapai set point 14.5V menjaga agar tidak terjadi tegangan dan arus berlebih yang dapat memperpanjang umur baterai. Penelitian ini menunjukkan bahwa metode PID pada optimasi MPPT efektif dalam mempercepat dan mengoptimalkan pengisian baterai. Penelitian selanjutnya diharapkan dapat mengembangkan lebih lanjut metode ini untuk meningkatkan efisiensi dan durasi pengisian baterai. Kata kunci: MPPT, PID, Optimasi, Charger Baterai, Optimal, PWM

This paper demonstrates the design and analysis of automatic generation control using intelligent genetic algorithm tuned fuzzy based controller. A two area thermal power system simulated for four different scenarios considers a reheat steam turbine in each area with Generator rate constraints. The Integral Time Squared Error (ITSE) employed to get an objective function for the optimization of controller gains. The simulation results compared with the conventional Proportional Integral Derivative (PID) controller, Genetic Algorithm (GA) tuned PID controller and GA tuned Fuzzy PID controller. The proposed GA tuned Fuzzy based PID Controller can generate the best performance for peak overshoot, undershoot and settling time with step load disturbances. Robustness of the performance of the proposed controller provided with system parametric uncertainties.

The development of modern technology has made automation an important part of life. Proportion Integral Derivative (PID) control is a basic control theory of automation which has many applications because of its simple construction and great performance. This article introduces the application of PID control technology in the automotive field. This paper mainly introduces the following aspects: the basic principles and theories of PID control, the challenges of automotive systems and their control, some solutions for PID control in automotive systems, and the improvement and optimization of control. The limitation of the application of traditional control theory in new automotive control have led to the emergence of more optimization algorithms, which can improve the system in more ways. In the future, automotive control systems will continue to be based on PID control as the framework and combined with some optimized new algorithms for practical application. Therefore, understanding PID control is of great significance to clarify the future development of automotive control technology.