PID Control Design for Second Order Systems

Alla, RamaKoteswara Rao; Lekyasri, N; Rajani, Kandipati

doi:10.5815/ijem.2019.04.04

Cited by 10 publications

(3 citation statements)

References 14 publications

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“…There are several techniques that have been proposed for tuning the gain of a PID controller, including the Ziegler and Nicholas (ZN) method [65], [66], [67], [68], the Modified ZN (MZN) method [69], [70], [71], the Tyreus-Luyben (TL) method [72], [73], [74], and the CHR tuning method [75], [76]. These techniques can be applied in both open-loop and closed-loop control modes and can be used to find the gain values for a system by substituting known values into preestimated equations or tables.…”

Section: Introductionmentioning

confidence: 99%

Dual Design PID Controller for Robotic Manipulator Application

Chotikunnan

2023

Journal of Robotics and Control

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This research introduces a dual design proportional–integral–derivative (PID) controller architecture process that aims to improve system performance by reducing overshoot and conserving electrical energy. The dual design PID controller uses real-time error and one-time step delay to adjust the confidence weights of the controller, leading to improved performance in reducing overshoot and saving electrical energy. To evaluate the effectiveness of the dual design PID controller, experiments were conducted to compare it with the PID controller using least overshoot tuning by Chien–Hrones–Reswick (CHR) technique. The results showed that the dual design PID controller was more effective at reducing overshoot and saving electrical energy. A case study was also conducted as part of this research, and it demonstrated that the system performed better when using the dual design PID controller. Overshoot and electrical energy consumption are common issues in systems that can impact performance, and the dual design PID controller architecture process provides a solution to these issues by reducing overshoot and saving electrical energy. The dual design PID controller offers a new technique for addressing these issues and improving system performance. In summary, this research presents a new technique for addressing overshoot and electrical energy consumption in systems through the use of a dual design PID controller. The dual design PID controller architecture process was found to be an effective solution for reducing overshoot and saving electrical energy in systems, as demonstrated by the experiments and case study conducted as part of this research. The dual design PID controller presents a promising solution for improving system performance by addressing the issues of overshoot and electrical energy consumption.

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Section: Introductionmentioning

confidence: 99%

Dual Design PID Controller for Robotic Manipulator Application

Chotikunnan

2023

Journal of Robotics and Control

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“…The most popular control method in these systems is the PID control system [32], [33], [34], [35], [36], [37]. Other techniques that have been proposed include the Arte Ziegler and Nicholas (ZN) method [38], [39], [40], [41], the modified ZN (MZN) method [42], [43], [44], the Tyreus-Luyben (TL) method [45], [46], [47], and the CHR tuning method [48], [49]. These techniques can be used in both open-loop and closed-loop control modes and can be used to find the gain values for a system by substituting known values into preestimated equations or tables.…”

Section: Introductionmentioning

confidence: 99%

Adaptive P Control and Adaptive Fuzzy Logic Controller with Expert System Implementation for Robotic Manipulator Application

Chotikunnan

Pititheeraphab

2023

Journal of Robotics and Control

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This study aims to develop an expert system implementation of P controller and fuzzy logic controller to address issues related to improper control input estimation, which can arise from incorrect gain values or unsuitable rule-based designs. The research focuses on improving the control input adaptation by using an expert system to resolve the adjustment issues of the P controller and fuzzy logic controller. The methodology involves designing an expert system that captures error signals within the system and adjusts the gain to enhance the control input estimation from the main controller. In this study, the P controller and fuzzy logic controller were regulated, and the system was tested using step input signals with small values and larger than the saturation limit defined in the design. The PID controller used CHR tuning to least overshoot, determining the system's gain. The tests were conducted using different step input values and saturation limits, providing a comprehensive analysis of the controller's performance. The results demonstrated that the adaptive fuzzy logic controller performed well in terms of %OS and settling time values in system control, followed by the fuzzy logic controller, adaptive P controller, and P controller. The adaptive P controller showed similar control capabilities during input saturation, as long as it did not exceed 100% of the designed rule base. The study emphasizes the importance of incorporating expert systems into control input estimation in the main controller to enhance the system efficiency compared to the original system, and further improvements can be achieved if the main processing system already possesses adequate control ability. This research contributes to the development of more intelligent control systems by integrating expert systems with P controllers and fuzzy logic controllers, addressing the limitations of traditional control systems and improving their overall performance.

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“…For such a system, it is better to have a model based on system identification or empirical modeling [9]. The PID controller is the most common control algorithm [10,11,12]. A survey has shown that 90% of control loops are PI and PID structures [13,14].…”

Section: Introductionmentioning

confidence: 99%

PID Temperature Controller Design for Shell and Tube Heat Exchanger

Olana¹,

Abose²

2021

IJEM

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Heat exchangers are one of the most important thermal devices. Shell and tube heat exchangers are the common types of heat exchangers and sustained a wide range of operating temperature and pressure. Modeling and controlling heat exchanger system is a difficult assignment because of its nonlinearity. As the flow rates changes, the gain, time delay and time constant varies, hence causing system nonlinearity. The solution for such problems is finding acceptable mathematical model and design a controller which provides better performance indices. In this paper mathematical model (experimental or empirical based) to represent the real system and design suitable controller which remove the offset and settle fast with minimum steady state error has been proposed. To this end, system model design the Proportional-Integral-Derivative controller for shell and tube heat exchanger using Ziegler Nichols method, Cohen-coon method and Chein et al. method. Since two opposing dynamic effects are existing in the system and has a problem of dynamics of inverse response and large overshoot. Therefore, Chein et al. tuning method have better performance than that of the others. In case of Chein et al. the overshoot of 2.577 % and settling time of 63.1 s.

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PID Control Design for Second Order Systems

Cited by 10 publications

References 14 publications

Dual Design PID Controller for Robotic Manipulator Application

Dual Design PID Controller for Robotic Manipulator Application

Adaptive P Control and Adaptive Fuzzy Logic Controller with Expert System Implementation for Robotic Manipulator Application

PID Temperature Controller Design for Shell and Tube Heat Exchanger

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