The Performance Comparison of ANFIS and Hammerstein-Wiener Models for BLDC Motors

Nemati, Abbas; Faieghi, Mohammadreza

doi:10.1007/978-3-642-21697-8_5

Cited by 13 publications

(8 citation statements)

References 13 publications

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“…However, ANFIS outperformed both models. Similar to other studies in different fields, by combining FLS interpretability and ANN ability to learn and optimize fuzzy parameters, ANFIS provides more accurate predictions (Badde, Gupta, & Patki, 2013;Bilgehan, 2011;Gaya, Wahab, Sam, & Samsuddin, 2013;Ho & Tsai, 2011;Jang, 1993;Nemati & Faieghi, 2011).…”

Section: Discussionmentioning

confidence: 69%

Forgiveness and trust dynamics on social networks

2018

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Social media users can easily be offended or hurt on those platforms, which leads to discomfort and health issues such as stress and anxiety. Forgiveness plays an important role to maintain healthy online relationships, which is the central constituent of social dynamics, from cooperation to social cohesion. While most prior studies have focused on analyzing forgiveness factors in offline settings using statistical methods, this study offers a new perspective using a two-staged approach whereby a research model was tested using structural equation modeling (SEM), and then the results were used as inputs for artificial neural network (ANN) and fuzzy logic (FL) models. An agent-based simulation was then performed to shed light on a possible use of the implemented models. Combining ANN and FL provided more accurate prediction results. In addition, simulation experiments call attention to the potential benefits of forgiveness in maintaining connectedness in a social network. The main purpose of this investigation was to evaluate the applicability of soft computing techniques on forgiveness prediction. Instead of relying on data mining techniques, we looked into questions that can improve our understanding of how society works in a digital age. In addition, this study provides an interesting example of a different and insightful way of doing computational social science that is useful to both researchers and practitioners.

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Section: Discussionmentioning

confidence: 69%

Forgiveness and trust dynamics on social networks

2018

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“…For clarity purposes, a superscript k in each function/parameter in this section is added to represent the corresponding term for Motor "k". In this work, both motors belong to Π p with slightly different dynamics, i.e., P A 0 ∼ (−10.23, 5.5, 1.0, 0), P B 0 ∼ (−8.8, 5.8, 1.0, 0), (α A min , α A max ) as described in Equations (5) and (6), and (α B min , α B max ) as described in Equations (5) and (7). where υ is retrieved via the voltage sensor connected to one of the analog pins of the microcontroller.…”

Section: Resultsmentioning

confidence: 99%

“…In this regard, many efforts have been devoted towards modelling DC motors in order to ensure the associated closed-loop systems can operate at varying conditions while preserving the desired performance [5]. Examples include decoupling the linear and nonlinear parts to form the so-called Hammerstein/Wiener structure [6], and employing neural network approach to characterize the nonlinearity [7,8].…”

Section: Introductionmentioning

confidence: 99%

Robust ℋ∞-Fuzzy Logic Control for Enhanced Tracking Performance of a Wheeled Mobile Robot in the Presence of Uncertain Nonlinear Perturbations

Ahmad

2020

Sensors

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Motion control involving DC motors requires a closed-loop system with a suitable compensator if tracking performance with high precision is desired. In the case where structural model errors of the motors are more dominating than the effects from noise disturbances, accurate system modelling will be a considerable aid in synthesizing the compensator. The focus of this paper is on enhancing the tracking performance of a wheeled mobile robot (WMR), which is driven by two DC motors that are subject to model parametric uncertainties and uncertain deadzones. For the system at hand, the uncertain nonlinear perturbations are greatly induced by the time-varying power supply, followed by behaviour of motion and speed. In this work, the system is firstly modelled, where correlations between the model parameters and different input datasets as well as voltage supply are obtained via polynomial regressions. A robust H ∞ -fuzzy logic approach is then proposed to treat the issues due to the aforementioned perturbations. Via the proposed strategy, the H ∞ controller and the fuzzy logic (FL) compensator work in tandem to ensure the control law is robust against the model uncertainties. The proposed technique was validated via several real-time experiments, which showed that the speed and path tracking performance can be considerably enhanced when compared with the results via the H ∞ controller alone, and the H ∞ with the FL compensator, but without the presence of the robust control law.

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“…The relation between matrix A and vector a of (4a) is given in (5), considering the definition of extended identity matrix.…”

Section: Problem Formulationmentioning

confidence: 99%

Hammerstein–Wiener identification of industrial plants: A pressure control valve case study

Esmaeilani

Ghaisari

Bagherzadeh

2020

IET Control Theory & Appl

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Hammerstein-Wiener (H-W) identification problem is investigated under practical considerations for industrial plants. The main consideration in these cases is inability to apply arbitrary input signals. An algorithm is proposed to identify H-W model for industrial systems, in the presence of noise and disturbance. The identification problem is changed into a constrained optimisation problem and is solved by minimising the non-linear functions modelling error. To improve the efficiency of the proposed method, the known information about non-linear functions are used. To make the proposed method applicable for general systems with hard non-linearities, non-linear functions are described by some ordered pairs. A pressure control valve that is used for anti-surge protection of an air compressor in the second refinery of South Pars Gas Complex is considered as the case study to demonstrate the effectiveness of the proposed algorithm. Seventy-five percent of the gathered data during the time is used for identification and the remaining 25% is used for verification of the resulted model. Verification of the obtained H-W model showed that accuracy of the identified model is more than 95%.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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The Performance Comparison of ANFIS and Hammerstein-Wiener Models for BLDC Motors

Cited by 13 publications

References 13 publications

Forgiveness and trust dynamics on social networks

Forgiveness and trust dynamics on social networks

Robust ℋ∞-Fuzzy Logic Control for Enhanced Tracking Performance of a Wheeled Mobile Robot in the Presence of Uncertain Nonlinear Perturbations

Hammerstein–Wiener identification of industrial plants: A pressure control valve case study

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