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Journal ArticleDOI

A novel interval dynamic reliability computation approach for the risk evaluation of vibration active control systems based on PID controllers

TLDR
A non-probability based method to calculate time-dependent reliability is introduced to estimate the safety of a vibration active control system of based on PID controller performance to avoid the disadvantages of traditional probabilistic methods.
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This article is published in Applied Mathematical Modelling.The article was published on 2021-04-01. It has received 102 citations till now. The article focuses on the topics: PID controller & Reliability (statistics).

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Citations
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Journal ArticleDOI

Effects of welding residual stresses on fatigue reliability assessment of a PC beam bridge with corrugated steel webs under dynamic vehicle loading

TL;DR: In this article , a numerical simulation method of welded residual stress in corrugated steel webs (CSWs) has been proposed and the effect of bending angle, welding path, and the number of welds on the residual stress field distribution has also been analyzed.
Journal ArticleDOI

A support vector regression (SVR)-based method for dynamic load identification using heterogeneous responses under interval uncertainties

TL;DR: A support vector regression (SVR)-based method is presented, which aims to reconstruct the uncertain dynamic load using heterogeneous responses, and results indicate that the proposed method can be utilized to identify the interval of dynamic load with outstanding accuracy and efficiency.
Journal ArticleDOI

Two-stage vibration-suppression framework for optimal robust placements design and reliable PID gains design via set-crossing theory and artificial neural network

TL;DR: In this article , a two-stage framework for uncertain vibration active control systems via non-probabilistic time-dependent reliability (NTDR) and artificial neutral network (ANN) is proposed.
Journal ArticleDOI

Interval-based optimal trajectory tracking control method for manipulators with clearance considering time-dependent reliability constraints

TL;DR: In this paper , a non-probabilistic uncertainty quantification approach is proposed to simplify the process of system uncertainties, and the corresponding response range is attended by collocation method with advantages upon precision and efficiency.
Journal ArticleDOI

Energy Management and Voltage Control in Microgrids Using Artificial Neural Networks, PID, and Fuzzy Logic Controllers

TL;DR: In this article , a microgrid consisting of renewable sources, Li-ion batteries, the main grid as a backup system, and AC/DC loads was designed for effective microgrid operations using three smart controllers.
References
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Journal ArticleDOI

Robust Control and Model Uncertainty

TL;DR: In this paper, a Benchmark Resource Allocation Problem with Model Misspecification and Robust Control Problems is discussed. But the problem is not addressed in this paper, and the following sections are included:
Journal ArticleDOI

A non-probabilistic concept of reliability

TL;DR: Non-probabilistic convex models of uncertainty are used to formulate reliability in terms of acceptable system performance given uncertain operating environment or uncertain geometrical imperfections.
Journal ArticleDOI

The PHI2 method: a way to compute time-variant reliability

TL;DR: This paper presents a method called PHI2 which is based on the outcrossing approach and allows to solve time-variant reliability problems using classical time-invariant reliability tools such as FORM/SORM methods.
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Structural reliability analysis using non-probabilistic convex model

TL;DR: In this article, a non-probabilistic reliability model is given for structures with convex model uncertainty, which is defined as a ratio of the multidimensional volume falling into the reliability domain to the one of the whole model.
Journal ArticleDOI

Probabilistic interval reliability of structural systems

TL;DR: This study introduces the interval approach into the conventional reliability theory and presents a novel approach which allows to obtain the system failure probability interval from the statistical parameter intervals of the basic variables.
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