AI-Based Actuator/Sensor Fault Detection With Low Computational Cost for Industrial Applications

Michail, Konstantinos; Deliparaschos, Kyriakos M.; Tzafestas, Spyros G.; Zolotas, Argyrios

doi:10.1109/tcst.2015.2422794

Cited by 38 publications

(17 citation statements)

References 21 publications

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“…The main limitation of the presentation is that it is focused on second-order inputaffine nonlinear systems. The application to higher order systems is a challenge due to the possible difficult computation of the partial derivatives of fuzzy controller input-output static map F. This is one of the directions of future research in a strong relation with inclusion of several advantageous features specific to fuzzy systems [109][110][111][112][113][114][115] so as to modify the control system structure.…”

Section: Validation On Electro-hydraulic Servo System Position Controlmentioning

confidence: 99%

A Center Manifold Theory-Based Approach to the Stability Analysis of State Feedback Takagi-Sugeno-Kang Fuzzy Control Systems

Precup

Preitl²,

Petriu³

et al. 2020

FU Mech Eng

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The aim of this paper is to propose a stability analysis approach based on the application of the center manifold theory and applied to state feedback Takagi-Sugeno-Kang fuzzy control systems. The approach is built upon a similar approach developed for Mamdani fuzzy controllers. It starts with a linearized mathematical model of the process that is accepted to belong to the family of single input second-order nonlinear systems which are linear with respect to the control signal. In addition, smooth right-hand terms of the state-space equations that model the processes are assumed. The paper includes the validation of the approach by application to stable state feedback Takagi-Sugeno-Kang fuzzy control system for the position control of an electro-hydraulic servo-system.

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Section: Validation On Electro-hydraulic Servo System Position Controlmentioning

confidence: 99%

A Center Manifold Theory-Based Approach to the Stability Analysis of State Feedback Takagi-Sugeno-Kang Fuzzy Control Systems

Precup

Preitl²,

Petriu³

et al. 2020

FU Mech Eng

View full text Add to dashboard Cite

show abstract

“…Evidence theory was developed by Shafer and was firstly proposed by Dempster [ 30 ], thus it is also called D–S evidence theory. Recently, theoretical research on evidence theory has played a very important role in many applications such as decision-making [ 31 , 32 , 33 , 34 ], complex networks [ 35 , 36 ], fault diagnosis [ 37 , 38 , 39 , 40 , 41 ], classification [ 42 , 43 ] and so on [ 44 , 45 , 46 , 47 ].…”

Section: Preliminariesmentioning

confidence: 99%

An Intuitionistic Evidential Method for Weight Determination in FMEA Based on Belief Entropy

Liu

Xiao

2019

Entropy

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Failure Mode and Effects Analysis (FMEA) has been regarded as an effective analysis approach to identify and rank the potential failure modes in many applications. However, how to determine the weights of team members appropriately, with the impact factor of domain experts’ uncertainty in decision-making of FMEA, is still an open issue. In this paper, a new method to determine the weights of team members, which combines evidence theory, intuitionistic fuzzy sets (IFSs) and belief entropy, is proposed to analyze the failure modes. One of the advantages of the presented model is that the uncertainty of experts in the decision-making process is taken into consideration. The proposed method is data driven with objective and reasonable properties, which considers the risk of weights more completely. A numerical example is shown to illustrate the feasibility and availability of the proposed method.

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“…An Improved Particle Swarm Optimization (IPSO) parameter estimation method is used to accurately determine the load model using AI based load modeling [56]. Actuator and sensor fault detection with low computational cost is developed using a novel AI method which uses single fault detection estimator instead of bank of estimators employed in traditional methods [57]. The literature talks about the different intelligent techniques that can be used to gather deeper meaning of the big data obtained from different source like physical social and cyber environment [58].…”

Section: From Artificial Intelligence To Automated Intelligencementioning

confidence: 99%

A transition from manual to Intelligent Automated power system operation -A Indicative Review

Doddamani¹,

Kapale²

2019

IJECE

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<p>This paper reviews the transition of the power system operation from the traditional manual mode of power system operations to the level where automation using Internet of Things (IOT) and intelligence using Artificial Intelligence (AI) is implemented. To make the review paper brief only indicative papers are chosen to cover multiple power system operation based implementation. Care is taken there is lesser repeatation of similar technology or application be reviewed. The indicative review is to take only a representative literature to bypass scrutinizing multiple literatures with similar objectives and methods. A brief review of the slow transition from the traditional to the intelligent automated way of carrying out power system operations like the energy audit, load forecasting, fault detection, power quality control, smart grid technology, islanding detection, energy management etc is discussed .The Mechanical Engineering Perspective on the basis of applications would be noticed in the paper although the energy management and power delivery concepts are electrical.</p>

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AI-Based Actuator/Sensor Fault Detection With Low Computational Cost for Industrial Applications

Cited by 38 publications

References 21 publications

A Center Manifold Theory-Based Approach to the Stability Analysis of State Feedback Takagi-Sugeno-Kang Fuzzy Control Systems

A Center Manifold Theory-Based Approach to the Stability Analysis of State Feedback Takagi-Sugeno-Kang Fuzzy Control Systems

An Intuitionistic Evidential Method for Weight Determination in FMEA Based on Belief Entropy

A transition from manual to Intelligent Automated power system operation -A Indicative Review

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