scholarly journals Fuzzy PID Control for Respiratory Systems

2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Ibrahim M. Mehedi ◽  
Heidir S. M. Shah ◽  
Ubail M. Al-Saggaf ◽  
Rachid Mansouri ◽  
Maamar Bettayeb

This paper presents the implementation of a fuzzy proportional integral derivative (FPID) control design to track the airway pressure during the mechanical ventilation process. A respiratory system is modeled as a combination of a blower-hose-patient system and a single compartmental lung system with nonlinear lung compliance. For comparison purposes, the classical PID controller is also designed and simulated on the same system. According to the proposed control strategy, the ventilator will provide airway flow that maintains the peak pressure below critical levels when there are unknown parameters of the patient’s hose leak and patient breathing effort. Results show that FPID is a better controller in the sense of quicker response, lower overshoot, and smaller tracking error. This provides valuable insight for the application of the proposed controller.

2012 ◽  
Vol 241-244 ◽  
pp. 1248-1254
Author(s):  
Feng Chen Huang ◽  
Hui Feng ◽  
Zhen Li Ma ◽  
Xin Hui Yin ◽  
Xue Wen Wu

Fuzzy control, based on traditional Proportional-Integral-Derivative (PID) control, is used to improve the management of a hydro-junction’s sluice scheduling. In this study, we combined the PID and Fuzzy control theories and determined the PID parameters of the fuzzy self-tuning method of a hydro-junction’s sluice. A fuzzy self-tuning PID controller and its algorithm were designed. In hydro-junction sluice control, the Fuzzy PID controller can modify PID parameters in real-time, resulting in a more dynamic response. The application of the fuzzy self-tuning PID controller in the CiHuai River project information integration system yielded very good results.


2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Shebel AlSabbah ◽  
Mujahed AlDhaifallah ◽  
Mohammad Al-Jarrah

This work concerns designing multiregional supervisory fuzzy PID (Proportional-Integral-Derivative) control for pH reactors. The proposed work focuses, mainly, on two themes. The first one is to propose a multiregional supervisory fuzzy-based cascade control structure. It would enable modifying dynamics and enhance system’s stability. The fuzzy system (master loop) has been chosen as a tuner for PID controller (slave loop). It takes into consideration parameters uncertainties and reference tracking. The second theme concerns designing a hybrid neural network-based pH estimator. The proposed estimator would overcome the industrial drawbacks, that is, cost and size, found with conventional methods for pH measurement. The final end-user-interface (EUI) front panel and the results that evaluate the performance of the supervisory fuzzy PID-based control system and hybrid NN-based estimator have been presented using the compatibility found between LabView and MatLab. They lead to conclude that the proposed algorithms are appropriate to systems nonlinearities encountered with pH reactors.


2011 ◽  
Vol 305 ◽  
pp. 173-176
Author(s):  
Jian Bo Cao ◽  
Ming Qiang Mao ◽  
Wan Lu Xu ◽  
Jia Ji ◽  
Jia Jiang ◽  
...  

To deal with the control problem of brushless DC motor (BLDCM), based on analyzing the work principle of BLDCM, the fuzzy-PID control was studied, and the fuzzy-PID controller of BLDCM was designed. The experimental results show that the fuzzy-PID controller is superior to the PID controller at steady-state tracking error. Additionally, the current and torque undulation of BLDCM were also improved.


2014 ◽  
Vol 945-949 ◽  
pp. 2568-2572
Author(s):  
Si Yuan Wang ◽  
Guang Sheng Ren ◽  
Pan Nie

The test rig for hydro-pneumatic converter used in straddle type monorail vehicles was researched, and its electro-pneumatic proportional control system was set up and simulated based on AMESim/Simulink. Compared fuzzy-PID (Proportion Integral Derivative) controller with PID controller through fuzzy logic tool box in Simulink, the results indicate that, this electro-pneumatic proportional control system can meet design requirements better, and fuzzy-PID controller has higher accuracy and stability than PID controller.


Author(s):  
Bambang Sumantri ◽  
Eko Henfri Binugroho ◽  
Ilham Mandala Putra ◽  
Rika Rokhana

The two-wheeled electric skateboard (TWS) is designed for a personal vehicle. A Fuzzy-PID control strategy is designed and implemented for controlling its motion. Basically, motions control of the TWS is performed by balancing the pitch position of the TWS. Performance of the designed controller is demonstrated experimentally. The Fuzzy algorithm updates the PID gains and therefore it can handle the changing of the TWS load. Contribution of Fuzzy-PID in reducing the electric energy consumption, which is an important issue in electrical system, is also evaluated. The Fuzzy-PID successes to reduce the electric energy consumption of the TWS compared to the conventional PID.


2012 ◽  
Vol 217-219 ◽  
pp. 2463-2466 ◽  
Author(s):  
Xue Gang Hou ◽  
Cheng Long Wang

Induction heating furnace temperature control is a complex nonlinear hysteretic inertial process, it's difficult to obtain an accurate mathematical model because the temperature and disturb from outside is complicated. The normal PID control algorithm is hard to satisfy the standards of control. The fuzzy PID controller provided in this article is a combination between fuzzy control and the traditional PID control. The Fuzzy control theory is used to setting the ratio, the integral and the differential coefficient of the PID control. In the run-up stage, rapidity is guaranteed, overstrike and the steady-state error is up to the mustard. An example indicates that fuzzy PID control is superior to the normal PID controller.


2014 ◽  
Vol 903 ◽  
pp. 327-331 ◽  
Author(s):  
Ismail Mohd Khairuddin ◽  
Anwar P.P.A. Majeed ◽  
Ann Lim ◽  
Jessnor Arif M. Jizat ◽  
Abdul Aziz Jaafar

This paper elucidates the modeling of a + quadrotor configuration aerial vehicle and the design of its attitude and altitude controllers. The aircraft model consists of four fixed pitch angle propeller, each driven by an electric DC motor. The hovering flight of the quadrotor is governed by the Newton-Euler formulation. The attitude and altitude controls of the aircraft were regulated using heuristically tuned (Proportional-Integral-Derivative) PID controller. It was numerically simulated via Simulink that a PID controller was sufficient to bring the aircraft to the required altitude whereas the attitude of the vehicle is adequately controlled by a PD controller.


2014 ◽  
Vol 620 ◽  
pp. 363-368
Author(s):  
Lian Xia ◽  
Jing Qiu ◽  
Jiang Han

In this paper, theory analysis, the MATLAB research and experimental verification about feedforward fuzzy PID control have been performed by combining the characteristics of the PID, feedforward control and fuzzy control. Simulation results show that the feedforward fuzzy PID control could improve the response speed of the system and reduce the tracking error of the system which shows the obvious superiority compared with the PID, feedforward PID, and fuzzy PID. Load experiment for such four kinds of control modes is done on the linear motor platform, and the experimental results show that the accuracy of the feedforward fuzzy PID control is obviously higher than the other three kinds of control modes and the feedforward fuzzy PID control is easier to be implemented. The position error of feedforward fuzzy PID control is changeless during the load change, and the change of the speed tracking error is small, which proves that the feedforward fuzzy PID control is suitable for the condition of load change or the great disturbance.


2012 ◽  
Vol 220-223 ◽  
pp. 880-883
Author(s):  
Hui Wang ◽  
Zhuo Xu

According to the problem of large overshoot in the variable pump constant pressure output, the fuzzy controller and PID controller were combined. The dynamic response of system output pressure was obtained by combining simulation with a fuzzy adaptive PID controller designed in Matlab/Simulink and mechanical hydraulic model established in AMESim. The simulation results show that fuzzy PID control can achieve the goal of system response without overshoot, and response speed is improved further. The anti-interference ability is also stronger.


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