Development of an internet and fuzzy based control system of manufacturing process

Zermane, Hanane; Mouss, Hayet

doi:10.1007/s11633-016-1027-x

Cited by 8 publications

(2 citation statements)

References 16 publications

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“…fuzzy rules) which are acquired from experimental knowledge of domain experts. Fuzzy systems can solve complex decision-making issues when equipped with abundant fuzzy rules [26]. Li et al designed a fuzzy keyword search engine based on a fuzzy system for searching encrypted data over cloud sources, and it solved the drawback of traditional techniques that struggled to match keywords on cloud [27].…”

Section: Fuzzy Neural Networkmentioning

confidence: 99%

A Fuzzy Neural Network Based Dynamic Data Allocation Model on Heterogeneous Multi-GPUs for Large-scale Computations

Zhang

et al. 2018

Int. J. Autom. Comput.

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The parallel computation capabilities of modern GPU (Graphics Processing Unit) processors have attracted increasing attention from researchers and engineers who have been conducting high computational throughput studies. However, current single GPU based engineering solutions are often struggle to fulfill their real-time requirements. Thus, the multi-GPU-based approach has become a popular and cost-effective choice for tackling the demands. In those cases, the computational load balancing over multiple GPU "nodes" is often the key and bottleneck that affect the quality and performance of the runtime system. The existing load balancing approaches are mainly based on the assumption that all GPU nodes in the same computer framework are of equal computational performance, which are often not the case due to cluster design and other legacy issues. This paper presents a novel dynamic load balancing (DLB) model for rapid data division and allocation on heterogeneous GPU nodes based on an innovative fuzzy neural network (FNN). In this research, a 5-state parameter feedback mechanism defining the overall cluster and node performances is proposed. The corresponding FNN-based DLB model will be capable of monitoring and predicting individual node performance under different workload scenarios. A real-time adaptive scheduler has been devised to reorganize the data inputs to each node when necessary to maintain their runtime computational performances. The devised model has been implemented on two dimensional (2D) discrete wavelet transform (DWT) tasks for evaluation. Experiment results show that this DLB model has enabled a high computational throughput while ensuring real-time and precision requirements from complex computational tasks.

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Section: Fuzzy Neural Networkmentioning

confidence: 99%

A Fuzzy Neural Network Based Dynamic Data Allocation Model on Heterogeneous Multi-GPUs for Large-scale Computations

Zhang

et al. 2018

Int. J. Autom. Comput.

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“…A number of research reports are found in literature that are related to network-enabled process automation. [1][2][3][4] All the leading programmable logic controller (PLC) manufacturers including Siemens, Allen-Bradley have started to adapt the web-enabled automation in order to increase the productivity. The credibility of network-mediated monitoring and control is influenced by many factors such as the number of nodes, the internet loads, time-delay, processing speed of nodes, connection bandwidth, amount of data and the transmission speed.…”

Section: Introductionmentioning

confidence: 99%

Internet-mediated automation of a cascade control system-an Engineering laboratory experiment

Sangeetha¹,

Bharathi²,

Ganesh

et al. 2019

The International Journal of Electrical Engineering & Educa

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The paper aims to enhance the controllability of a standalone cascade control system with Internet architecture and promote the system to be accessible by remote students. The user interactive web page is developed by using platform independent ASP.NET language and enabled with both monitoring and controlling functionalities. The Internet transmission time delays that are associated with both feed-forward and feedback channels are compensated by using model predictive controller. The performance of cascade control system with and without compensation is validated by measuring indices, such as rise time, peak time and settling time, and also integral square error and integral absolute error. Access privileges among web page users have been added to ensure simultaneous operations as well as security. The cascade control system is an engineering laboratory experiment interfaced with a dedicated computer by using MODBUS protocol and it is made available to the remote students. The user perception analysis is carried out by using a set of questionnaire that observes 85% of positive feedback.

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Feature of Predicting the Thermal Characteristics of Machine Tools Using Feedforward Neural Networks

Polyakov

Pozevalkin

Nikitina

2022

Lecture Notes in Mechanical Engineering

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Development of an internet and fuzzy based control system of manufacturing process

Cited by 8 publications

References 16 publications

A Fuzzy Neural Network Based Dynamic Data Allocation Model on Heterogeneous Multi-GPUs for Large-scale Computations

A Fuzzy Neural Network Based Dynamic Data Allocation Model on Heterogeneous Multi-GPUs for Large-scale Computations

Internet-mediated automation of a cascade control system-an Engineering laboratory experiment

Feature of Predicting the Thermal Characteristics of Machine Tools Using Feedforward Neural Networks

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