scholarly journals MARGO (Massively Automated Real-time GUI for Object-tracking), a platform for high-throughput ethology

2019 ◽  
Author(s):  
Zach Werkhoven ◽  
Christian Rohrsen ◽  
Chuan Qin ◽  
Björn Brembs ◽  
Benjamin de Bivort
Keyword(s):  
Object Tracking ◽  
Real Time ◽  
High Throughput ◽  
Large Scale ◽  
Closed Loop ◽  
Optomotor Response ◽  
Behavioral Experiments ◽  
Loop Control ◽  
Flexible Control ◽  
Large Numbers

AbstractFast object tracking in real time allows convenient tracking of very large numbers of animals and closed-loop experiments that control stimuli for multiple animals in parallel. We developed MARGO, a real-time animal tracking suite for custom behavioral experiments. We demonstrated that MARGO can rapidly and accurately track large numbers of animals in parallel over very long timescales. We incorporated control of peripheral hardware, and implemented a flexible software architecture for defining new experimental routines. These features enable closed-loop delivery of stimuli to many individuals simultaneously. We highlight MARGO’s ability to coordinate tracking and hardware control with two custom behavioral assays (measuring phototaxis and optomotor response) and one optogenetic operant conditioning assay. There are currently several open source animal trackers. MARGO’s strengths are 1) robustness, 2) high throughput, 3) flexible control of hardware and 4) real-time closed-loop control of sensory and optogenetic stimuli, all of which are optimized for large-scale experimentation.

A Playbook(trademark) for Real-Time, Closed-Loop Control

2005 ◽  
Author(s):  
Harry Funk ◽  
Robert Goldman ◽  
Christopher Miller ◽  
John Meisner ◽  
Peggy Wu
Keyword(s):  
Real Time ◽  
Closed Loop ◽  
Closed Loop Control ◽  
Loop Control

scholarly journals Evaluation of Optimal Vibrotactile Feedback for Force-Controlled Upper Limb Myoelectric Prostheses

Sensors ◽  
2019 ◽  
Vol 19 (23) ◽  
pp. 5209 ◽  
Author(s):  
Andrea Gonzalez-Rodriguez ◽  
Jose L. Ramon ◽  
Vicente Morell ◽  
Gabriel J. Garcia ◽  
Jorge Pomares ◽  
...  
Keyword(s):  
Real Time ◽  
Upper Limb ◽  
Closed Loop ◽  
Fine Tuning ◽  
Vibrotactile Feedback ◽  
Loop Control ◽  
Myoelectric Prostheses ◽  
Amplitude Level ◽  
Real Time Application ◽  
Selection Of

The main goal of this study is to evaluate how to optimally select the best vibrotactile pattern to be used in a closed loop control of upper limb myoelectric prostheses as a feedback of the exerted force. To that end, we assessed both the selection of actuation patterns and the effects of the selection of frequency and amplitude parameters to discriminate between different feedback levels. A single vibrotactile actuator has been used to deliver the vibrations to subjects participating in the experiments. The results show no difference between pattern shapes in terms of feedback perception. Similarly, changes in amplitude level do not reflect significant improvement compared to changes in frequency. However, decreasing the number of feedback levels increases the accuracy of feedback perception and subject-specific variations are high for particular participants, showing that a fine-tuning of the parameters is necessary in a real-time application to upper limb prosthetics. In future works, the effects of training, location, and number of actuators will be assessed. This optimized selection will be tested in a real-time proportional myocontrol of a prosthetic hand.

Modeling and Closed-Loop Control of Stretch Bending of Aluminum Rectangular Tubes

2003 ◽  
Vol 125 (1) ◽  
pp. 113-119 ◽  
Author(s):  
Hong Zhu ◽  
Kim A. Stelson
Keyword(s):  
Experimental Data ◽  
Real Time ◽  
Control Algorithm ◽  
Closed Loop ◽  
Strain History ◽  
Closed Loop Control ◽  
Loop Control ◽  
Stretch Bending ◽  
Rectangular Tube ◽  
Rectangular Tubes

During stretch bending, considerable springback will occur after a tube has been plastically bent. To predict the springback, a simplified two-flange model for stretch bending of a rectangular tube has been developed in which the strain history has been considered. A comparison has been made between the springback predicted by this model and experimental data, which shows rough agreement. Based on this model, a real time closed-loop control algorithm is developed.

Controlling Nylon Dyeing by Dye and Chemical Metering

1997 ◽  
Vol 67 (8) ◽  
pp. 609-616 ◽  
Author(s):  
Ralph McGregor ◽  
Manpreet S. Arora ◽  
Warren J. Jasper
Keyword(s):  
Adaptive Control ◽  
Binary Mixture ◽  
Real Time ◽  
Closed Loop ◽  
Closed Loop Control ◽  
Good Reproducibility ◽  
Acid Dyes ◽  
Loop Control ◽  
Polyamide Fibers ◽  
The Individual

Closed-loop control of the dosing of dyes and chemicals is used to obtain an on-tone build-up of shade in dyeing polyamide fibers with a binary mixture of monosulfonated acid dyes. Computerized dosing pumps control the pH, the dyebath concentrations of the individual dyes, and the total sorption of each dye during the process. This real-time, closed-loop adaptive control yields good reproducibility and uniform shade build-up in a laboratory dyeing machine. It is possible to reuse a dyebath containing residual dyes and chemicals from a previous dyeing.

Wireless closed-loop control of centrifugo-pneumatic valving towards large-scale microfluidic process integration

2018 ◽  
Author(s):  
David J. Kinahan ◽  
Sarai M. Delgado ◽  
Lourdes A.N. Julius ◽  
Adam Mallette ◽  
David Saenz-Ardila ◽  
...  
Keyword(s):  
Large Scale ◽  
Closed Loop ◽  
Process Integration ◽  
Closed Loop Control ◽  
Loop Control

scholarly journals Real-Time Low-Cost Speed Monitoring and Control of Three-Phase Induction Motor via a Voltage/Frequency Control Approach

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Ali Hmidet ◽  
Olfa Boubaker
Keyword(s):  
Real Time ◽  
Induction Motor ◽  
Closed Loop ◽  
Low Cost ◽  
Closed Loop Control ◽  
Loop Control ◽  
Control Approach ◽  
Three Phase ◽  
Wide Range ◽  
Voltage Frequency

In this paper, a new design of a real-time low-cost speed monitoring and closed-loop control of the three-phase induction motor (IM) is proposed. The proposed solution is based on a voltage/frequency (V/F) control approach and a PI antiwindup regulator. It uses the Waijung Blockset which considerably alleviates the heaviness and the difficulty of the microcontroller’s programming task incessantly crucial for the implementation and the management of such complex applications. Indeed, it automatically generates C codes for many types of microcontrollers like the STM32F4 family, also used in this application. Furthermore, it offers a cost-effective design reducing the system components and increasing its efficiency. To prove the efficiency of the suggested design, not only simulation results are carried out for a wide range of variations in load and reference speed but also experimental assessment. The real-time closed-loop control performances are proved using the aMG SQLite Data Server via the UART port board, whereas Waijung WebPage Designer (W2D) is used for the web monitoring task. Experimental results prove the accuracy and robustness of the proposed solution.

scholarly journals An Intelligent Microwave Oven with Thermal Imaging and Temperature Recommendation Using Deep Learning

2020 ◽  
Vol 3 (1) ◽  
pp. 13 ◽  
Author(s):  
Tareq Khan
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Thermal Imaging ◽  
Closed Loop ◽  
Thermal Image ◽  
Microwave Oven ◽  
Closed Loop Control ◽  
Target Temperature ◽  
Thermal Camera ◽  
Loop Control

Whenever food in a microwave oven is heated, the user estimates the time to heat. This estimation can be incorrect, leading the food to be too hot or still cold. In this research, an intelligent microwave oven is designed. After the food is put into the microwave oven and the door is closed, it captures the image of the food, classifies the image and then suggests the food’s target temperature by learning from previous experiences, so the user does not have to recall the target food temperature each time the same food is warmed. The temperature of the food is measured using a thermal camera. The proposed microwave incorporates a display to show a real-time colored thermal image of the food. The microwave automatically stops the heating when the temperature of the food hits the target temperature using closed-loop control. The deep learning-based image classifier gradually learns the type of foods that are consumed in that household and becomes smarter in temperature recommendation. The system can classify and recommend target temperature with 93% accuracy. A prototype is developed using a microcontroller-based system and successfully tested.

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