An overview on fault diagnosis and nature-inspired optimal control of industrial process applications

RE Precup, P Angelov, BSJ Costa… - Computers in …, 2015 - Elsevier
Fault detection, isolation and optimal control have long been applied to industry. These
techniques have proven various successful theoretical results and industrial applications …

Comparison of AHP and fuzzy AHP models for prioritization of watersheds

SG Meshram, E Alvandi, VP Singh, C Meshram - Soft Computing, 2019 - Springer
Prioritization of watersheds for conservation measures is essential for a variety of functions,
such as flood control projects for which determining areas of top priority is a managerial …

Application of SAW and TOPSIS in prioritizing watersheds

SG Meshram, E Alvandi, C Meshram, E Kahya… - Water Resources …, 2020 - Springer
Prioritization of watersheds for conservation measures is essential for a variety of functions,
such as flood control projects in which the determination of top priority areas is an important …

Evolving model identification for process monitoring and prediction of non-linear systems

G Andonovski, G Mušič, S Blažič, I Škrjanc - Engineering applications of …, 2018 - Elsevier
This paper tackles the problem of model identification for monitoring of non-linear processes
using evolving fuzzy models. To ensure a high production quality and to match the economic …

Local joint information based active fault tolerant control for reconfigurable manipulator

B Zhao, Y Li - Nonlinear dynamics, 2014 - Springer
This paper is concerned with the active fault tolerant control problem for reconfigurable
manipulator actuator based on local joint information. It is considered that the entire …

Dynamic process monitoring using adaptive local outlier factor

Y Ma, H Shi, H Ma, M Wang - Chemometrics and Intelligent Laboratory …, 2013 - Elsevier
A numerically efficient moving window local outlier factor (LOF) algorithm is proposed in this
paper for monitoring industrial processes with time-varying and multimode characteristics …

A self-learning and self-optimizing framework for the fault diagnosis knowledge base in a workshop

Q Lin, Y Zhang, S Yang, S Ma, T Zhang… - Robotics and Computer …, 2020 - Elsevier
The knowledge base is an essential part of the fault diagnosis system, which is crucial to the
performance of fault recognition. As the intelligence of the fault diagnosis system has made …

Discretization of hybrid CPPS data into timed automaton using restricted Boltzmann machines

N Hranisavljevic, A Maier, O Niggemann - Engineering Applications of …, 2020 - Elsevier
Abstract Cyber–Physical Production Systems (CPPSs) are hybrid systems composed of a
discrete and continuous part. However, most of the applied machine learning algorithms …

A comprehensive framework of factory-to-factory dynamic fleet-level prognostics and operation management for geographically distributed assets

C **, D Djurdjanovic, HD Ardakani… - 2015 ieee …, 2015 - ieeexplore.ieee.org
This paper proposes a comprehensive Prognostics and Health Management (PHM)
framework for large fleets of geographically distributed assets. The objective of this research …

Adaptive parameter estimation in LTI systems

MN Kapetina, MR Rapaić, A Pisano… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
An adaptive algorithm solving the on-line parameter estimation problem for a broad class of
linear systems is proposed. The approach can be applied to systems with delay, distributed …