Adaptive fuzzy PI controller with shifted control singletons

Filip, Ioan; Szeidert, Iosif

doi:10.1016/j.eswa.2016.01.036

Cited by 15 publications

(7 citation statements)

References 14 publications

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“…A starting procedure of a minimum variance control system, involving successively different values of the control penalty factor, is presented in [16]. A relatively similar solution, proposing a self-tuning algorithm for controller output singletons of an adaptive fuzzy PI control system, has been implemented and the results were published by the authors in [7], noting comparably good performances. The theoretical aspects and the full calculus regarding the analytical determination of the minimum-variance control law were described in extenso in [11,12].…”

Section: The Self-tuning Algorithm Of Control Penalty Factormentioning

confidence: 99%

“…The usage of adaptive control systems is suitable for the control of complex systems for which an accurate mathematical model is not available, with the system being subject to unknown parameter variations and large disturbances over time [1][2][3][4][5][6]. Furthermore, if the operating point changes under the action of external disturbances (taking into account a wide variation range of disturbances) or due to the variation of internal parameters, the usage of classical control solutions (PI, PID controllers) becomes infeasible [5,7]. In these cases, a minimum variance control system is a viable solution due to its adaptive nature, ensured by the self-tuning characteristic of the controller parameters [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

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Minimum-Variance Control System with Variable Control Penalty Factor

et al. 2020

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The present paper proposes (as the main contribution) an additional self-tuning mechanism for an adaptive minimum-variance control system, whose main goal is to extend its functionality for a large value range of unmeasurable perturbations which disturb the controlled process. Through the standard design procedure, a minimum variance controller uses by default an internal self-tuning mechanism based on the process parameter estimates. However, the main parameter which overwhelmingly influences the control performance is the control penalty factor ( ρ ) . This parameter weights the term that describes the control variance in a criterion function whose minimization is the starting point of the control law design. The classical minimum-variance control involves an off-line tuning of this parameter, its value being set as constant throughout the entire operating regime. Based on the measurement of the process output error, the contribution of the proposed strategy consists in a real-time tuning of the control penalty factor, to ensure the stability of the control system, even under conditions of high disturbances. The proposed tuning mechanism adjusts this parameter by implementing a bipositional switching strategy based on a sharp hysteresis loop. Therefore, instead of the standard solution that involves a constant value of the control penalty factor ρ (a priori computed and set), this paper proposes a dual value for this controller parameter. The main objective is to allow the controlled process to operate in a stable fashion even in more strongly disturbed regimes (regimes where the control system becomes unstable and is usually switched off for safety reasons). To validate the proposed strategy, an induction generator integrated into a wind energy conversion system was considered as controlled plant. Operating under the action of strong disturbances (wind gusts, electrical load variations), the extension of safe operating range (thus avoiding the system disengagement) is an important goal of such a control system.

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Section: The Self-tuning Algorithm Of Control Penalty Factormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Minimum-Variance Control System with Variable Control Penalty Factor

et al. 2020

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“…Permintaan Batu bara (Set-Point) (kg/s) 10 [19] kedua hasil dari algoritma pengendali yang digunakan samasama mampu mencapai rentang kerja dari parameter akumulasi massa batu bara tersebut, namun kendali PI-Fuzi mampu menunjukkan hasil yang lebih efisien dan mampu mengompensasi lambatnya rise time yang dihasilkan oleh kendali PI-Fuzi daripada kendali PI (Tabel V). TABEL V. HASIL ANALISIS AKUMULASI MASSA BATU BARA Suhu keluaran batu bara menunjukkan pengaruh pada parameter kelembaban dan kehalusan batu bara.…”

Section: Pengendaliunclassified

“…Penerapan dan pengujian kendali PI-Fuzi pada beberapa sistem plant dengan basis yang berbeda-beda telah banyak dilakukan. Uji kinerja kendali PI-Fuzi banyak diterapkan pada perangkat lunak MATLAB/Simulink dengan menggunakan beberapa jenis plant yang berbeda-beda, antara lain Automatic Generation Control (AGC) [6], grid interactive inverter [7], sistem konversi energi angin [8], Motor Brushless DC (BLDC) [9], Generator Induksi [10], dan magnet permanen motor multi-sinkron [11]. Penerapan dan pengujian pengendali PI-Fuzi pada [6], [8]- [11] merupakan penelitian yang berskala simulasi, di mana hasil dari penelitian tersebut adalah pengendali PI-Fuzi mampu menunjukkan kinerja yang lebih baik dari pengendali PI yang juga ikut diujikan pada beberapa sistem plant tersebut [6], [8]- [11].…”

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Pengembangan Blok Fungsi Kendali PI-Fuzi pada IEC 61499

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Wardana

Effendy

2019

Jurnal Teknik Elektro

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Automation system in the form of automatic control is needed in one or several operating units in the process industry. Several control system algorithms have been widely implemented in the process industry, one of them is PI (Proportional and Integral) controller. This PI controller has a simple structure, but the adaptive ability of the controller is still not better for the controlled process. Therefore, the development of PI controller is needed to have a better adaptive ability to the process, in order to produce the responses that are also better and more robust. This research develops PI controller by adding the Fuzzy controller algorithm or also known as PI-Fuzzy controller. The PI-Fuzzy controller in this study is applied to the IEC 61499 Programmable Logic Controller (PLC) standard and to see its performance, the PI-Fuzzy controller based on IEC 61499 is tested and validated on an industrial scale process, namely coal mill. The test was carried out for three hours in real-time on the 4DIAC-IDE software, then the response results were compared with the response results of the PI controller. The PI-Fuzzy controller function block based on IEC 61499 made in this study showed good performance in controlling industrial-scale processes. This is demonstrated in testing and validation using a coal mill, with able to achieve the working range of each parameter. The mean value of coal flow parameter is 13.584 kg/s, coal mass accumulation is 2,196 kg, coal output temperature is 83.296 0 C, coal moisture is 0.021, and coal fineness is 75.338 %. Abstrak-Sistem otomasi yang berupa kendali otomatis sangat diperlukan pada satu atau beberapa unit operasi pada industri proses. Beberapa algoritma sistem kendali telah banyak diimplementasikan pada industri proses, salah satunya adalah kendali Proporsional dan Integral (PI). Kendali PI ini mempunyai struktur yang sederhana, namun kemampuan adaptif yang dimiliki pengendali ini masih kurang baik terhadap proses yang dikendalikan. Oleh karena itu, pengembangan kendali PI dibutuhkan agar mempunyai kemampuan adaptif yang lebih baik terhadap proses, sehingga menghasilkan tanggapan respons yang juga lebih baik dan kokoh. Penelitian ini mengembangkan kendali PI dengan menambahkan algoritma kendali Fuzi atau dikenal juga dengan sebutan kendali PI-Fuzi. Kendali PI-Fuzi pada penelitian ini diterapkan pada standar Programmable Logic Controller (PLC) IEC 61499 dan untuk melihat kinerjanya, kendali PI-Fuzi berbasis IEC 61499 diujikan dan divalidasi pada proses berskala industri, yaitu coal mill. Pengujian dilakukan selama tiga jam secara waktu nyata pada perangkat lunak 4DIAC-IDE, lalu hasil responsnya dibandingkan dengan hasil respons pengendali PI. Blok fungsi kendali PI-Fuzi berbasis IEC 61499 yang dibuat pada penelitian ini menunjukkan kinerja yang baik dalam mengendalikan proses yang berskala industri. Hal ini ditunjukkan pada pengujian dan validasinya menggunakan coal mill, dengan mampu mencapai rentang kerja dari setiap parameter. Nilai rerata parameter aliran batu bara mencapai ...

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“…Multiple attribute group decision making (MAGDM) is an important and hot topic in modern decision fields. Since Zadeh (1965) proposed the fuzzy set (FS) theory, researches on FS have made a large number of achievements in many fields, including intelligent fuzzy control (Filip & Szeidert, 2016;Mendel & Wu, 2010), decision support system Gong, Zhang, Forrest, Li, & Xu, 2015;Merigó, Gil-Lafuente, & Martorell, 2012) and so on. However, one of the shortcomings of FS is that it only reflects the degree of membership, but dose not take the degree of non-membership into consideration.…”

Section: Introductionmentioning

confidence: 99%

Some new Hamacher aggregation operators under single-valued neutrosophic 2-tuple linguistic environment and their applications to multi-attribute group decision making

Zhou

et al. 2018

Computers & Industrial Engineering

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This paper proposes an approach to linguistic multiple attribute group decision making (MAGDM) problem with single-valued neutrosophic 2-tuple linguistic (SVN2TL) assessment information by adding a subjective imprecise estimation of reliability of the 2-tuple linguistic terms (2TLTs). SVN2TL includes the truth-membership (TM), indeterminacy-membership (IM) and faulty-membership (FM), which can express the incomplete, indeterminate and inconsistent information perfectly and avoid information and precision losing in aggregation process ideally. We first propose the concept of SVN2TL set (SVN2TLS) and single valued neutrosophic 2-tuple linguistic element (SVN2TLE), basic operational rules on SVN2TLEs via Hamacher triangular norms, and ranking method for SVN2TLEs. Then, some SVN2TL aggregation operators including SVN2TL Hamacher weighted averaging (SVN2TLHWA) operator, SVN2TL Hamacher geometric weighted averaging (SVN2TLHGWA) operator, are developed, their some properties are investigated as well. Moreover, we apply new operators to develop approach to MAGDM problem with SVN2TL assessment information, where a model for optimal weighting vector is constructed. Finally, an numerical example related to evaluation of emergency response solutions for sustainable community development is provided to show the utility and effectiveness of the method described in this paper. A sensitivity and comparative analysis are also conducted to demonstrate the strength and practicality of the proposed method.

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Adaptive fuzzy PI controller with shifted control singletons

Cited by 15 publications

References 14 publications

Minimum-Variance Control System with Variable Control Penalty Factor

Minimum-Variance Control System with Variable Control Penalty Factor

Pengembangan Blok Fungsi Kendali PI-Fuzi pada IEC 61499

Some new Hamacher aggregation operators under single-valued neutrosophic 2-tuple linguistic environment and their applications to multi-attribute group decision making

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