scholarly journals Real-time dynamic process control loop identification, tuning and optimization software

2016 ◽  
Vol 49 (6) ◽  
pp. 213-217 ◽  
Author(s):  
S. Howes ◽  
I. Mohler ◽  
N. Bolf
Keyword(s):  
Process Control ◽  
Real Time ◽  
Dynamic Process ◽  
Control Loop ◽  
Optimization Software ◽  
Time Dynamic

Implementation of Real-Time Concentration Process Control System Design Based on PID and Fuzzy Logic Controller

2015 ◽  
Vol 772 ◽  
pp. 147-153
Author(s):  
Mohamed Amir Gabir Elbakri
Keyword(s):  
Fuzzy Logic ◽  
Process Control ◽  
Real Time ◽  
Fuzzy Logic Controller ◽  
Control Loop ◽  
Time System ◽  
Real Time System ◽  
Concentration Process ◽  
Labview Software ◽  
Model Control

Concentration process is commonly process in industries for chemicals and products that want to reach desired amount of matter in product, so concentration process control is important to reach the desired concentrate of product.Concentration in streams are affected by physical variables around it like pressure, temperature and amount of matter that solvent in streams, so the amplitude of concentration is randomly change with time that make control process not easy.In this project controller was designed for concentration process and was implemented in real-time system that constructed to verify the response of controller, in prototype concentrated solutions-juice and sugar-used to control in it separately with water then mixed to produce juice with desired property.The Mathematical model of concentrated process was evolved and Matlab used to analyze and design control loop for these model, control algorithms used as PID & Fuzzy logic controller to build controller that achieve the specification requirements of a system process.The Fuzzy PI-controller designed to control that for characteristic of nonlinearity of real-time system, and implement simulation of control loops in LABVIEW software with appropriate interface.The DAQ hardware with LABVIEW software are used to implement the control loop that designed for real-time prototype to produce the juice with desired concentrated.

Control Model Constructing on Real-Time Dynamic Reversible Lane in Condition of Connected Vehicle

CICTP 2020 ◽  
2020 ◽  
Author(s):  
Lina Mao ◽  
Wenquan Li ◽  
Pengsen Hu ◽  
Guiliang Zhou ◽  
Huiting Zhang ◽  
...  
Keyword(s):  
Real Time ◽  
Control Model ◽  
Connected Vehicle ◽  
Time Dynamic

scholarly journals Real-Time Compression for Tactile Internet Data Streams

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1924
Author(s):  
Patrick Seeling ◽  
Martin Reisslein ◽  
Frank H. P. Fitzek
Keyword(s):  
Real Time ◽  
Data Streams ◽  
Control Loop ◽  
Real World Data ◽  
Perceptual Coding ◽  
Great Flexibility ◽  
Broad Application ◽  
Time Compression ◽  
Perceptual Threshold ◽  
Selection Of

The Tactile Internet will require ultra-low latencies for combining machines and humans in systems where humans are in the control loop. Real-time and perceptual coding in these systems commonly require content-specific approaches. We present a generic approach based on deliberately reduced number accuracy and evaluate the trade-off between savings achieved and errors introduced with real-world data for kinesthetic movement and tele-surgery. Our combination of bitplane-level accuracy adaptability with perceptual threshold-based limits allows for great flexibility in broad application scenarios. Combining the attainable savings with the relatively small introduced errors enables the optimal selection of a working point for the method in actual implementations.

scholarly journals Dynamic Gesture Recognition System with Gesture Spotting Based on Self-Organizing Maps

2021 ◽  
Vol 11 (4) ◽  
pp. 1933
Author(s):  
Hiroomi Hikawa ◽  
Yuta Ichikawa ◽  
Hidetaka Ito ◽  
Yutaka Maeda
Keyword(s):  
Real Time ◽  
Gesture Recognition ◽  
Weight Vector ◽  
Recognition System ◽  
Self Organizing Map ◽  
Self Organizing Maps ◽  
Time Dynamic ◽  
System Input ◽  
Self Organizing ◽  
Gesture Spotting

In this paper, a real-time dynamic hand gesture recognition system with gesture spotting function is proposed. In the proposed system, input video frames are converted to feature vectors, and they are used to form a posture sequence vector that represents the input gesture. Then, gesture identification and gesture spotting are carried out in the self-organizing map (SOM)-Hebb classifier. The gesture spotting function detects the end of the gesture by using the vector distance between the posture sequence vector and the winner neuron’s weight vector. The proposed gesture recognition method was tested by simulation and real-time gesture recognition experiment. Results revealed that the system could recognize nine types of gesture with an accuracy of 96.6%, and it successfully outputted the recognition result at the end of gesture using the spotting result.

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