Experimental Study of the Performance Test for the Infusion Monitoring System

2013 ◽  
Vol 756-759 ◽  
pp. 407-410
Author(s):  
Zhi Hui Xu ◽  
Wei Zhong Li ◽  
Yong Jun Xiao
Keyword(s):  
Monitoring System ◽  
System Performance ◽  
Pid Controller ◽  
Performance Test ◽  
High Reliability ◽  
Fuzzy Pid ◽  
Time Consumption ◽  
Fuzzy Pid Controller ◽  
Manual Adjustment ◽  
Result Show

Comparison with conventional manual adjustment to control the drop speed in clinical infusion, the infusion monitoring system can achieve much more high reliability and efficiency, and is easy to realize the automation of infusion. So the infusion monitoring system has been designed in the last papers. To test the designed system performance, some experiments are done. And the result show that under requirement of the system precision, the time consumption increase with the incensement of speed difference value; Comparing to the conventional PID controller, the fuzzy-PID controller can achieve high precision and little stabilizing time consumption.

Research on Tyred Machinery Chassis Dynamometer

2013 ◽  
Vol 631-632 ◽  
pp. 1106-1110
Author(s):  
Wei Zhao ◽  
Qiang Wang ◽  
Sheng Li Song
Keyword(s):  
Control System ◽  
System Performance ◽  
Pid Controller ◽  
Fuzzy Pid ◽  
Chassis Dynamometer ◽  
Technical Parameters ◽  
The Road ◽  
Fuzzy Pid Controller ◽  
System A ◽  
Line Measure

In the tyred machinery chassis dynamometer control system, a fuzzy PID controller was used to adjust the exciting current of a DC dynamometer in order to change the resistance load torque, so the requirement of roller load for simulating the run resistance from the road surface was satisfied. A fuzzy PID arithmetic was designed to control the resistance loads, the system performance was improved by simulation. The software of the detection line measure-control system was designed in VB, the technical parameters of the machinery chassis could the automatically detected.

scholarly journals Two Area Systems for Restructuring and Deregulation in Load Frequency using Fuzzy PID Controller

2019 ◽  
Vol 9 (1) ◽  
pp. 4154-4157
Keyword(s):  
System Performance ◽  
Pid Controller ◽  
Research Paper ◽  
Fuzzy Pid ◽  
Matlab Simulink ◽  
Fuzzy Pid Controller ◽  
Load Frequency

In this research paper, a fuzzy PID method has been used to improve the Load frequency problem (LFC). This technique will help in correcting the system performance. The two area system is used to describe the load frequency problem using Fuzzy PID Controller. To support the proposal, two areas have been considered. They have been modelled in MATLAB Simulink and accordingly simulated results have been obtained.

The Sinter Mixture Moisture Control System Based on Fuzzy PID Controller

2013 ◽  
Vol 457-458 ◽  
pp. 899-904
Author(s):  
Ting Gui Li ◽  
Qin Hui Gong
Keyword(s):  
Control System ◽  
System Performance ◽  
Pid Controller ◽  
Production Condition ◽  
Structural Features ◽  
Fuzzy Pid ◽  
Moisture Control ◽  
Fuzzy Pid Controller ◽  
Self Tuning ◽  
Sinter Mixture

Because the sinter mixture moisture control system has time-varying, nonlinear and time-delay characteristics, it is difficult to establish its precise mathematical model. According to the defects that the conventional PID control in the fixed parameter is difficult to guarantee the system performance, this paper proposed the parameter self-tuning fuzzy PID controller which is used to the system. Based on the sintering furnace structural features and control performance requirements, the PID parameters are set by fuzzy logic reasoning. The actual operation results proved that the parameter self-tuning fuzzy PID controller improved more obviously the system performance than the original PID controller, and stabilized the sinter mixture moisture, and improved the sintering production condition and promoted the production capacity.

Grasshopper Algorithm Optimized Fractional Order Fuzzy PID Frequency Controller for Hybrid Power Systems

2019 ◽  
Vol 12 (6) ◽  
pp. 519-531
Author(s):  
Deepak Kumar Lal ◽  
Ajit Kumar Barisal
Keyword(s):  
Power Systems ◽  
Power System ◽  
Fractional Order ◽  
Pid Controller ◽  
Load Frequency Control ◽  
Pid Controllers ◽  
Fuzzy Pid ◽  
Fuzzy Pid Controller ◽  
Hybrid Power ◽  
Increasing Demand

Background: Due to the increasing demand for the electrical power and limitations of conventional energy to produce electricity. Methods: Now the Microgrid (MG) system based on alternative energy sources are used to provide electrical energy to fulfill the increasing demand. The power system frequency deviates from its nominal value when the generation differs the load demand. The paper presents, Load Frequency Control (LFC) of a hybrid power structure consisting of a reheat turbine thermal unit, hydropower generation unit and Distributed Generation (DG) resources. Results: The execution of the proposed fractional order Fuzzy proportional-integral-derivative (FO Fuzzy PID) controller is explored by comparing the results with different types of controllers such as PID, fractional order PID (FOPID) and Fuzzy PID controllers. The controller parameters are optimized with a novel application of Grasshopper Optimization Algorithm (GOA). The robustness of the proposed FO Fuzzy PID controller towards different loading, Step Load Perturbations (SLP) and random step change of wind power is tested. Further, the study is extended to an AC microgrid integrated three region thermal power systems. Conclusion: The performed time domain simulations results demonstrate the effectiveness of the proposed FO Fuzzy PID controller and show that it has better performance than that of PID, FOPID and Fuzzy PID controllers. The suggested approach is reached out to the more practical multi-region power system. Thus, the worthiness and adequacy of the proposed technique are verified effectively.

Core power control of a space nuclear reactor based on a nonlinear model and fuzzy-PID controller

2021 ◽  
pp. 103564
Author(s):  
Wenjie Zeng ◽  
Qingfeng Jiang ◽  
Yinuo Liu ◽  
Shoujun Yan ◽  
Guangchun Zhang ◽  
...  
Keyword(s):  
Power Control ◽  
Nonlinear Model ◽  
Pid Controller ◽  
Nuclear Reactor ◽  
Fuzzy Pid ◽  
Fuzzy Pid Controller
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