Real-time implementation of constrained control system on experimental hybrid plant using RT-Lab

2008 ◽  
Author(s):  
M. Addel-Geliel
Keyword(s):  
Control System ◽  
Real Time ◽  
Hybrid Plant ◽  
Constrained Control

scholarly journals Advanced Control System for Grid-Connected SOFC Hybrid Plants: Experimental Verification in Cyber-Physical Mode

2019 ◽  
Author(s):  
Mario L. Ferrari ◽  
Iacopo Rossi ◽  
Alessandro Sorce ◽  
Aristide F. Massardo
Keyword(s):  
Control System ◽  
Fuel Cell ◽  
Real Time ◽  
Pid Control ◽  
Controller Design ◽  
Experimental Tests ◽  
Cell System ◽  
Hybrid Plant ◽  
Time Model ◽  
Point Data

Abstract This paper presents a Model Predictive Controller (MPC) operating an SOFC Gas Turbine hybrid plant at end-of-life performance condition. Its performance was assessed with experimental tests showing a comparison with a Proportional Integral Derivative (PID) control system. The hybrid system operates in grid-connected mode, i.e. at variable speed condition of the turbine. The control system faces a multivariable constrained problem, as it must operate the plant into safety conditions while pursuing its objectives. The goal is to test whether a linearized controller design for normal operating condition is able to govern a system which is affected by strong performance degradation. The control performance was demonstrated in a cyber-physical emulator test rig designed for experimental analyses on such hybrid systems. This laboratory facility is based on the coupling of a 100 kW recuperated microturbine with a fuel cell emulation system based on vessels for both anodic and cathodic sides. The components not physically present in the rig were studied with a real-time model running in parallel with the plant. Model output values were used as set-point data for obtaining in the rig (in real-time mode) the effect of the fuel cell system. The result comparison of the MPC tool against a PID control system was carried out considering several plant properties and the related constraints. Both systems succeeded in managing the plant, still the MPC performed better in terms of smoothing temperature gradient and peaks.

scholarly journals Advanced Control System for Grid-Connected SOFC Hybrid Plants: Experimental Verification in Cyber-Physical Mode

2019 ◽  
Vol 141 (9) ◽  
Author(s):  
Mario L. Ferrari ◽  
Iacopo Rossi ◽  
Alessandro Sorce ◽  
Aristide F. Massardo
Keyword(s):  
Control System ◽  
Fuel Cell ◽  
Real Time ◽  
Pid Control ◽  
Controller Design ◽  
Experimental Tests ◽  
Cell System ◽  
Hybrid Plant ◽  
Time Model ◽  
Point Data

This paper presents a model predictive controller (MPC) operating a solid oxide fuel cell (SOFC) gas turbine hybrid plant at end-of-life performance condition. Its performance was assessed with experimental tests showing a comparison with a proportional integral derivative (PID) control system. The hybrid system (HS) operates in grid-connected mode, i.e., at variable speed condition of the turbine. The control system faces a multivariable constrained problem, as it must operate the plant into safety conditions while pursuing its objectives. The goal is to test whether a linearized controller design for normal operating condition is able to govern a system which is affected by strong performance degradation. The control performance was demonstrated in a cyber-physical emulator test rig designed for experimental analyses on such HSs. This laboratory facility is based on the coupling of a 100 kW recuperated microturbine with a fuel cell emulation system based on vessels for both anodic and cathodic sides. The components not physically present in the rig were studied with a real-time model running in parallel with the plant. Model output values were used as set-point data for obtaining in the rig (in real-time mode) the effect of the fuel cell system. The result comparison of the MPC tool against a PID control system was carried out considering several plant properties and the related constraints. Both systems succeeded in managing the plant, still the MPC performed better in terms of smoothing temperature gradient and peaks.

Development of real time welding control system by using image processing.

1989 ◽  
Vol 7 (3) ◽  
pp. 363-367 ◽  
Author(s):  
Takaichi Koyama ◽  
Yoichi Takahashi ◽  
Masahiro Kobayashi ◽  
Junichiro Morisawa
Keyword(s):  
Image Processing ◽  
Control System ◽  
Real Time

scholarly journals A Real-Time, Automatic, and Dynamic Scheduling and Control System for PET Patients Based on Wearable Sensors

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1104
Author(s):  
Shin-Yan Chiou ◽  
Kun-Ju Lin ◽  
Ya-Xin Dong
Keyword(s):  
Control System ◽  
Real Time ◽  
Human Error ◽  
Dynamic Scheduling ◽  
Wearable Sensors ◽  
Time Data ◽  
Scan Time ◽  
Number Of Patients ◽  
And Control ◽  
Automatic Scheduling

Positron emission tomography (PET) is one of the commonly used scanning techniques. Medical staff manually calculate the estimated scan time for each PET device. However, the number of PET scanning devices is small, the number of patients is large, and there are many changes including rescanning requirements, which makes it very error-prone, puts pressure on staff, and causes trouble for patients and their families. Although previous studies proposed algorithms for specific inspections, there is currently no research on improving the PET process. This paper proposes a real-time automatic scheduling and control system for PET patients with wearable sensors. The system can automatically schedule, estimate and instantly update the time of various tasks, and automatically allocate beds and announce schedule information in real time. We implemented this system, collected time data of 200 actual patients, and put these data into the implementation program for simulation and comparison. The average time difference between manual and automatic scheduling was 7.32 min, and it could reduce the average examination time of 82% of patients by 6.14 ± 4.61 min. This convinces us the system is correct and can improve time efficiency, while avoiding human error and staff pressure, and avoiding trouble for patients and their families.

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