New tuning strategy for series cascade control structure

Kalim, Md. Imran; Ali, Ahmad

doi:10.1016/j.ifacol.2020.06.033

Cited by 12 publications

(8 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Here, V x PI and V y PI are given by equations ( 30) and (31). Finally, the required procedures for applying the ACCSR method to calculate the tuning parameters of the PI-PD controller for controlling the IFOPDT processes can be summarized as follows:…”

Section: The Analytical Centroid Of Convex Stability Boundary Locus A...mentioning

confidence: 99%

“…6. Find the vertex point (V x PI , V y PI ) using by equations (30) and (31), then obtain the centroid point ( x PI ACCSR , y ACCSR PI ) using equations ( 34) and (35). 7.…”

Section: The Analytical Centroid Of Convex Stability Boundary Locus A...mentioning

confidence: 99%

“…Computations of equations ( 28) and ( 29) also require v PD which can be calculated from equation (24) or (25), depending on the value of t. Calculation of the outer loop centroid point ( x PI , y PI ) from equations ( 34) and ( 35) needs values of V x PI , V y PI , and v PI . Outer loop vertex points V x PI and V y PI can be obtained from equations ( 30) and (31), and v PI value can be evaluated using equation (32) or (33), depending on the value of t. Now, changing t value by a step of 0.1 in the range t 2 ½0:1, 2, one can draw the plot of t versus M s as shown in Figure 11. Then, the nonlinear least-square method is used to fit the raw data in Figure 11 into an equation given by M S ACCSR = 39:31t 2 + 42:64t + 105:5 t 3 + 7:248t 2 + 35:41t + 23:34…”

Section: Performance Analysismentioning

confidence: 99%

“…[28][29][30] Also, it has been reported that the controller calibrated by the centroid point might yield better setpoint tracking, faster disturbance rejection, and robustness against parameter variations. 31 To compute the centroid point of the stability region for tuning the parameters of a PI-PD controller, the WGC approach 28,29 and the CCSR approach 30 have been recently proposed. However, both WGC and CCSR methods have their own shortcomings.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Proportional–integral and proportional–derivative controller design based on analytically computed centroid point for controlling integrating processes

Alyoussef

Kaya

2023

Proceedings of the Institution of Mechanical Engineers, Part I:

View full text Add to dashboard Cite

The proportional–integral and proportional–derivative controller is characterized by its capability to effectively control integrating processes compared with proportional–integral/proportional–integral–derivative controllers. Recently, several graphical methods have been proposed for tuning the PI-PD controller parameters by computing the centroid point of the stability boundary locus. However, these approaches are time-consuming because they entail plotting the stability boundary locus for finding the centroid point. Another disadvantage of those design methods is that the design procedure has to be redone as the transfer function changes. In this article, a generalized stability boundary locus is constructed in terms of the controller and assumed plant transfer function model parameters to enable the designer to avoid replotting the stability boundary locus as the process transfer function changes. More importantly, two analytical approaches, which simplify the design of the proportional–integral and proportional–derivative controller very much, are proposed to compute the centroid point of the generalized stability boundary locus. Analytical expressions for computing the performance measures of the designed closed-loop system have also been provided so that one can predict the performance of the designed closed-loop system. It has been shown by simulation examples that the analytical centroid of convex stability region method provides quicker responses with faster disturbance rejections compared to other reported design methods. Also, the simulation results have displayed that analytical weighted geometrical center gives more robust closed-loop responses in terms of gain margin, phase margins, and maximum sensitivity than analytical centroid of convex stability region. Finally, the feasibility of the proposed methods is tested using a real-time application based on an aerodynamical system. Real-time results have demonstrated that the analytical centroid of convex stability region and analytical weighted geometrical center methods give quicker responses with small overshoots compared to other reported methods.

show abstract

Section: The Analytical Centroid Of Convex Stability Boundary Locus A...mentioning

confidence: 99%

“…6. Find the vertex point (V x PI , V y PI ) using by equations (30) and (31), then obtain the centroid point ( x PI ACCSR , y ACCSR PI ) using equations ( 34) and (35). 7.…”

Section: The Analytical Centroid Of Convex Stability Boundary Locus A...mentioning

confidence: 99%

Section: Performance Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Proportional–integral and proportional–derivative controller design based on analytically computed centroid point for controlling integrating processes

Alyoussef

Kaya

2023

Proceedings of the Institution of Mechanical Engineers, Part I:

View full text Add to dashboard Cite

show abstract

“…Then, the primary controller is tuned while considering the action of the secondary controller in the inner loop. This two-stage tuning procedure can be time-consuming since two tests on the plant are generally necessary, such as in the works of Hang et al (1994) and Kalim and Ali (2020).…”

Section: Introductionmentioning

confidence: 99%

Simultaneous tuning of cascade controllers based on nonlinear optimization

Torga¹,

Silva

Reis

et al. 2022

Transactions of the Institute of Measurement and Control

View full text Add to dashboard Cite

Cascade control is widely used in the process industry, especially to reject disturbances. Typically, the controller parameters in the inner and outer loops of the cascade controller structure are defined in a strict sequence. In this paper, simultaneous tuning of cascade controllers is proposed to improve the performance of the system under load disturbance. For this purpose, the cost function of a nonlinear optimization problem is formulated to minimize the effect of disturbances on the system output. In addition, robustness constraints are defined for the maximum sensitivity function to independently guarantee a robust system for inner and outer loops. In this sense, the designer can explicitly and independently address the trade-off between performance and robustness for both loops. Simulation studies illustrate the performance and effectiveness of the proposed controller design method compared to well-known methods in the literature. These results indicate that the proposed method reduces the integrated absolute error (IAE) under load disturbance by up to [Formula: see text]. In addition, experimental results from a tank-level control application in the mineral process industry illustrate the practical applicability of the proposed method. In this case, the proposed method reduces the IAE under load disturbance by [Formula: see text].

show abstract

Optimizing the series cascade control structure for nonminimum phase system regulation

Singhal,

Yadav,

Yadav

et al. 2024

Applied Research

View full text Add to dashboard Cite

This work elucidates the control of integrating a non‐minimum phase system via a series cascade scheme with fractional‐order P.I. (Proportional–Integral) plus D (Derivative) controller. The traditional Internal Model Control (IMC) is adopted for inner loop controller design. The feedback D controller is synthesized with the outer loop process model, showing the proposed work's universality. The outer loop controller is suggested in the IMC framework after the accountability of fractional‐filter and inverse response compensator. This combination is revealed to enhance performance without compromising robustness. The Riemann sheet principle is explored to compute the stability of the suggested controller. The sensitivity analysis has asserted the robustness. More importantly, the optimal value of controller settings is achieved via the Teaching Learning Based Optimization (TLBO) algorithm. This TLBO algorithm uses an objective function that minimizes Integral Square Error (ISE). Two illustrative problems are utilized to examine the recommended control structure's virtue.This article is protected by copyright. All rights reserved.

show abstract

New tuning strategy for series cascade control structure

Cited by 12 publications

References 18 publications

Proportional–integral and proportional–derivative controller design based on analytically computed centroid point for controlling integrating processes

Proportional–integral and proportional–derivative controller design based on analytically computed centroid point for controlling integrating processes

Simultaneous tuning of cascade controllers based on nonlinear optimization

Optimizing the series cascade control structure for nonminimum phase system regulation

Contact Info

Product

Resources

About