Optimal Robust PID Control for First- and Second-Order Plus Dead-Time Processes

Satô, Takao; Hayashi, Itaru; Horibe, Yohei; Vilanova, Ramón; Konishi, Yasuo

doi:10.3390/app9091934

Cited by 13 publications

(8 citation statements)

References 17 publications

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“…To simplify the derivation of the PID b controller parameters, in the next step, all closed-loop transfer function parameters, represented by Expressions (15) and 16, are divided by A 0 K I . Consequently, the following closed-loop transfer function Parameters (5) are obtained:…”

Section: Extension To Integrating Processesmentioning

confidence: 99%

“…In addition to these typical tuning rules, more advanced methods have also been proposed. The latter usually use complex algorithms for the process identification [9,[11][12][13][14][15][16][17][18][19]. According to the literature, the number of tuning rules for stable overdamped processes is much larger than that for integrating processes.…”

Section: Introductionmentioning

confidence: 99%

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Parametric and Nonparametric PID Controller Tuning Method for Integrating Processes Based on Magnitude Optimum

2020

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Integrating systems are frequently encountered in power plants, paper-production plants, storage tanks, distillation columns, chemical reactors, and the oil industry. Due to the open-loop instability that leads to an unbounded output from a bounded input, the efficient control of integrating systems remains a challenging task. Many researchers have addressed the control of integrating processes: Some solutions are based on a single closed-loop controller, while others employ more complex control structures. However, it is difficult to find one solution requiring only a simple tuning procedure for the process. This is the advantage of the magnitude optimum multiple integration (MOMI) tuning method. In this paper, we propose an extension of the MOMI tuning method for integrating processes, controlled with a two-degrees-of-freedom (2-DOF) proportional–integral–derivative (PID) controller. This extension allows for calculations of the controller parameters from either time domain measurements or from a process transfer function of an arbitrary order with a time-delay, when both approaches are exactly equivalent. The user has the option to emphasise disturbance-rejection or tracking with the reference weighting factor b or apply two different reference filters for the best overall response. The proposed extension was also compared to other tuning methods for the control of integrating processes and tested on a charge-amplifier drift-compensation system. All closed-loop responses were relatively fast and stable, all in accordance with the magnitude optimum criteria.

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Section: Extension To Integrating Processesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Parametric and Nonparametric PID Controller Tuning Method for Integrating Processes Based on Magnitude Optimum

2020

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“…In addition to typical tuning rules, such as Cohen-Coon, Chien-Hrones-Reswick, Ziegler-Nichols, or refined Ziegler-Nichols rules, more advanced methods have also been proposed. Usually, they use more complex algorithms to identify the processes [1][2][3][4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Parametric and Nonparametric PI Controller Tuning Method for Integrating Processes Based on Magnitude Optimum

2020

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Integrating systems are frequently encountered in the oil industry (oil–water–gas separators, distillation columns), power plants, paper-production plants, polymerisation processes, and in storage tanks. Due to the non-self-regulating character of the processes, any disturbance can cause a drift of the process output signal. Therefore, efficient closed-loop control of such processes is required. There are many PI and PID controller tuning methods for integrating processes. However, it is hard to find one requiring only a simple tuning procedure on the process, while the tuning method is based either on time-domain measurements or on a process transfer function of arbitrary order, which are the advantages of the magnitude optimum multiple integration (MOMI) tuning method. In this paper, we propose the extension of the MOMI tuning method to integrating processes. Besides the mentioned advantages, the extension provides efficient closed-loop control, while PI controller parameters calculation is still based on simple algebraic expressions, making it suitable for less-demanding hardware, like simpler programmable logic controllers (PLC). Additionally, the proposed method incorporates reference weighting factor b that allows users to emphasize either the disturbance-rejection or reference-following response. The proposed extension of the MOMI method (time-domain approach) was also tested on a charge-amplifier drift-compensation system, a laboratory hydraulic plant, on an industrial autoclave, and on a solid-oxide fuel-cell temperature control. All closed-loop responses were relatively stable and fast, all in accordance with the magnitude optimum criteria.

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“…Robustness plays a fundamental role in automatic control theory and practice [1][2][3][4]. Parametric uncertainty represents a natural, effective, but also a relatively simple tool for the mathematical description of real-life systems with potentially complex behavior (including nonlinearities, fast dynamics or changes in physical parameters) by means of linear time-invariant (LTI) models.…”

Section: Introductionmentioning

confidence: 99%

Value-Set-Based Approach to Robust Stability Analysis for Ellipsoidal Families of Fractional-Order Polynomials with Complicated Uncertainty Structure

2019

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This paper presents the application of a value-set-based graphical approach to robust stability analysis for the ellipsoidal families of fractional-order polynomials with a complex structure of parametric uncertainty. More specifically, the article focuses on the families of fractional-order linear time-invariant polynomials with affine linear, multilinear, polynomic, and general uncertainty structure, combined with the uncertainty bounding set in the shape of an ellipsoid. The robust stability of these families is investigated using the zero exclusion condition, supported by the numerical computation and visualization of the value sets. Four illustrative examples are elaborated, including the comparison with the families of fractional-order polynomials having the standard box-shaped uncertainty bounding set, in order to demonstrate the applicability of this method.

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Optimal Robust PID Control for First- and Second-Order Plus Dead-Time Processes

Cited by 13 publications

References 17 publications

Parametric and Nonparametric PID Controller Tuning Method for Integrating Processes Based on Magnitude Optimum

Parametric and Nonparametric PID Controller Tuning Method for Integrating Processes Based on Magnitude Optimum

Parametric and Nonparametric PI Controller Tuning Method for Integrating Processes Based on Magnitude Optimum

Value-Set-Based Approach to Robust Stability Analysis for Ellipsoidal Families of Fractional-Order Polynomials with Complicated Uncertainty Structure

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