Analytical tuning rules for second-order reduced ADRC with SOPDT models

Malladi, Srikanth; Yadaiah, N.

doi:10.1016/j.isatra.2022.05.009

Cited by 9 publications

(3 citation statements)

References 28 publications

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“…Parameter tuning There are several methods available in the literature to tune ADRC, such as: margins approaches, step response curves, multiobjective optimization problems, and minimizing performance indices. [38][39][40] Another often-used approach to tune ADRC parameters is based on bandwidth. 41 This path expresses ⊗ obs and K as a function of two quantities called observer bandwidth (ω 0 ) and controller bandwidth (ω c ).…”

Section: Tmentioning

confidence: 99%

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Active disturbance rejection control: an application to continuous microalgae photobioreactors

Sangregorio‐Soto,

Mazzanti,

Cortés‐Romero

et al. 2023

J of Chemical Tech & Biotech

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BACKGROUNDMathematical modelling is a widely employed approach for investigating the growth behaviour of microalgae. As a result, the development of model‐based controllers to regulate process variables has garnered increasing attention. However, despite the significant efforts invested in this area, control performance can be adversely affected by unmodelled dynamics and disturbances.RESULTSTwo active disturbance rejection controllers (ADRC) were designed to enable robust tracking of biomass concentration in continuous microalgae photobioreactors, with reduced reliance on the mathematical model of the system. The controllers were tuned to achieve a nonovershoot response and minimize settling time based on the culture's characteristics. Simulations were performed using optimal setpoints specific to each model. The results showcased a maximum output signal deviation of ±2.2%, ±7.8% and ± 7.62% for the Dunaliella tertiolecta, Isochrysis affinis galbana and Chlorella vulgaris models, respectively, regardless of the presence of simulated disturbances.CONCLUSIONSThe findings of this study significantly contribute to the advancement of the field of sustainable microalgae production. By introducing less dependent model‐based controllers, this research enhances the feasibility of implementing robust control strategies. These controllers require only knowledge of the equation system's order and the control gain function, simplifying the design process. This approach effectively addresses control performance degradation arising from unmodelled dynamics and disturbances. The ability to maintain desired process variables through ADRC controllers not only ensures improved control performance, but also supports the cultivation of specific microalgal species, when an accurate model is not available, thus promoting the overall progress and viability of microalgae biomass production. © 2023 Society of Chemical Industry.

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Section: Tmentioning

confidence: 99%

“…There are several methods available in the literature to tune ADRC, such as: margins approaches, step response curves, multi‐objective optimization problems, and minimizing performance indices 38‐40 . Another often‐used approach to tune ADRC parameters is based on bandwidth 41 .…”

Section: Active Disturbance Rejection Controller Applied To Microalga...mentioning

confidence: 99%

Active disturbance rejection control: an application to continuous microalgae photobioreactors

Sangregorio‐Soto,

Mazzanti,

Cortés‐Romero

et al. 2023

J of Chemical Tech & Biotech

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“…Maximum sensitivity (M s ) [17] is the robustness measure which is defined as the shortest distance from the Nyquist curve of the loop transfer function to the critical point -1. Mathematically, M s is expressed as follows [18]:…”

Section: Stability and Robustness Analysismentioning

confidence: 99%

Robust control of a single-ended primary inductor converter using adrc technique

Kumar,

Ajmeri

2023

Eng. Res. Express

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Control of a single-ended primary inductor converter (SEPIC) is a challenging task as it is a fourth-order non-linear system. In this paper, an active disturbance rejection control (ADRC) scheme is proposed for the SEPIC converter with a high switching frequency. Selection of the observers and controller bandwidth is done according to the maximum sensitivity requirement to achieve robust performance towards varying input voltage and load. The effectiveness of the suggested ADRC is shown by calculating power and efficiencies for different loading conditions.

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