scholarly journals ML models for real-time hybrid systems

2021 ◽  
pp. 752-759
Author(s):  
Manuel I. Capel
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Real Time System ◽  
Loop Control ◽  
Ac Motor ◽  
Closed Loop Control System ◽  
Loop Control System ◽  
Flow Through ◽  
Automated Machine Learning ◽  
Time Systems

A correct system design can be systematically obtained from a specification model of a real-time system that integrates hybrid measurements In a realistic industrial environment, this has been carried out through complete Matlab / Simulink / Stateflow models. However, there is a widespread interest in carrying out that modeling resorting to Machine Learning models, which can be understood as Automated Machine Learning for Real-time systems that present some degree of hybridation. An AC motor controller which must be able to maintain a constant air flow through a filter is one of these systems. The article also discusses a practical application of the method for implementing a closed loop control system to show how the proposed procedure can be applied to derive complete hybrid system designs with ANN.

Research on Integrated Control and Simulation of Three-Phase Voltage Source PWM Rectifier Based on 64-bit RTW

2015 ◽  
Vol 743 ◽  
pp. 172-175
Author(s):  
S.S. Shi ◽  
Z.W. Zhang ◽  
Liu Shu ◽  
T.Y. Yin ◽  
Y. Li
Keyword(s):  
Real Time ◽  
Integrated Control ◽  
Voltage Source ◽  
Pwm Rectifier ◽  
Phase Voltage ◽  
Loop Control ◽  
Development Cycle ◽  
Closed Loop Control System ◽  
Three Phase ◽  
Loop Control System

This article presents a double closed loop control system for three-phase voltage source<br />PWM rectifier based on a real-time workshop(RTW), introduces the debugging method of 64-bit<br />RTW platform. Then the simulation model is converted into the real-time code, and downloaded to<br />the platform controlled of DSP TMS320F2812 to verify the feasibility. The experimental results<br />agrees the simulation results. This method greatly reduces the project development cycle and cost.

scholarly journals ADAPT: A Smart Mask for Active Defense Against Air-Borne Pathogens

2021 ◽  
Author(s):  
Rohan Reddy Kalavakonda ◽  
Naren Vikram Raj Masna ◽  
Soumyajit Mandal ◽  
Swarup Bhunia
Keyword(s):  
Real Time ◽  
Preventive Measure ◽  
Smartphone Application ◽  
Sensor Data ◽  
Loop Control ◽  
Active Defense ◽  
Closed Loop Control System ◽  
Surgical Masks ◽  
Loop Control System ◽  
Micro Controller Unit

Abstract Face masks are a primary preventive measure against airborne pathogens. Thus, they have become one of the keys to controlling the spread of the COVID-19 virus. Common examples, including N95 masks, surgical masks, and face coverings, are passive devices that minimize the spread of suspended pathogens by inserting an aerosol-filtering barrier between the user’s nasal and oral cavities and the environment. However, the filtering process does not adapt to changing pathogen levels or other environmental factors, which reduces its effectiveness in real-world scenarios. This paper addresses the limitations of passive masks by proposing ADAPT, a smart IoT-enabled “active mask”. This wearable device contains a real-time closed-loop control system that senses airborne particles of different sizes near the mask by using an on-board particulate matter (PM) sensor. It then intelligently mitigates the threat by using mist spray, generated by a piezoelectric actuator, to load nearby aerosol particles such that they rapidly fall to the ground. The system is controlled by an on-board micro-controller unit (MCU) that collects sensor data, analyzes it, and activates the mist generator as necessary. A custom smartphone application enables the user to remotely control the device and also receive real-time alerts related to recharging, refilling, and/or decontamination of the mask before reuse. Experimental results on a working prototype confirm that aerosol clouds rapidly fall to the ground when the mask is activated, thus significantly reducing PM counts near the user. Also, usage of the mask significantly increases local relative humidity (RH) levels.

Real-Time Downhole Weight on Bit (DWOB) Automation in Directional Drilling

2015 ◽  
Author(s):  
Andrew Wu ◽  
Geir Hareland
Keyword(s):  
Real Time ◽  
Field Tests ◽  
Directional Drilling ◽  
Well Drilling ◽  
Loop Control ◽  
Closed Loop Control System ◽  
Loop Control System ◽  
Weight On Bit ◽  
The Difference ◽  
Predicted Values

This paper introduces the functionality of a new type of Autodriller software system, which can acquire downhole weight on bit (DWOB) based on surface rig measurement. Field tests are performed, including DWOB measured by downhole measuring tools and the hookload below the top drive using a TTS (Torque and Tension Sub). Three sets of drilling data from three horizontal wells in Western Canada were utilized to verify the models of this new Autodriller system. DWOB comparisons between the model and the measuring tools were carried out. The comparisons indicate a good agreement between the downhole measured DWOB and the new Autodriller predicted values. The difference between the new Autodriller prediction and downhole measured DWOB can be quantified using rooted mean square error (RMSE) or relative error (RE). This paper also analyzes the differences in some sections, and some measures are suggested to potentially reduce these differences. The new Autodriller is a closed loop control system which can automatically in real-time adjust surface weight on bit (SWOB) so that the DWOB is accurate, which will directly improve the performance of drill bits, and decrease the cost of drilling, especially in directional well drilling applications.

scholarly journals A smart mask for active defense against airborne pathogens

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rohan Reddy Kalavakonda ◽  
Naren Vikram Raj Masna ◽  
Soumyajit Mandal ◽  
Swarup Bhunia
Keyword(s):  
Real Time ◽  
Preventive Measure ◽  
Smartphone Application ◽  
Sensor Data ◽  
Loop Control ◽  
Active Defense ◽  
Closed Loop Control System ◽  
Surgical Masks ◽  
Loop Control System ◽  
Micro Controller Unit

AbstractFace masks are a primary preventive measure against airborne pathogens. Thus, they have become one of the keys to controlling the spread of the COVID-19 virus. Common examples, including N95 masks, surgical masks, and face coverings, are passive devices that minimize the spread of suspended pathogens by inserting an aerosol-filtering barrier between the user’s nasal and oral cavities and the environment. However, the filtering process does not adapt to changing pathogen levels or other environmental factors, which reduces its effectiveness in real-world scenarios. This paper addresses the limitations of passive masks by proposing ADAPT, a smart IoT-enabled “active mask”. This wearable device contains a real-time closed-loop control system that senses airborne particles of different sizes near the mask by using an on-board particulate matter (PM) sensor. It then intelligently mitigates the threat by using mist spray, generated by a piezoelectric actuator, to load nearby aerosol particles such that they rapidly fall to the ground. The system is controlled by an on-board micro-controller unit that collects sensor data, analyzes it, and activates the mist generator as necessary. A custom smartphone application enables the user to remotely control the device and also receive real-time alerts related to recharging, refilling, and/or decontamination of the mask before reuse. Experimental results on a working prototype confirm that aerosol clouds rapidly fall to the ground when the mask is activated, thus significantly reducing PM counts near the user. Also, usage of the mask significantly increases local relative humidity levels.

An Expert Controller Based on Transient Response Patterns

2011 ◽  
Vol 219-220 ◽  
pp. 3-7
Author(s):  
Ning Zhang ◽  
Rong Hua Liu
Keyword(s):  
Control System ◽  
Transient Response ◽  
Closed Loop ◽  
Performance Criterion ◽  
Response Patterns ◽  
Loop Control ◽  
Expert Control ◽  
Closed Loop Control System ◽  
Loop Control System ◽  
Control Decision

An expert control system based on transient response patterns and expert system techniques is proposed in this paper. Depending on the features of the closed-loop control system determines the control decision and adjusts the parameters of the controller. The proposed method requires minimal proper information about the controlled plant and, with the linear re-excitation learning method, the system is kept satisfying the performance criterion.

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