scholarly journals Automated closed-loop resuscitation of multiple hemorrhages: a comparison between fuzzy logic and decision table controllers in a sheep model

2017 ◽  
Vol 3 (1) ◽  
Author(s):  
Nicole Ribeiro Marques ◽  
Brent J. Ford ◽  
Muzna N. Khan ◽  
Michael Kinsky ◽  
Donald J. Deyo ◽  
...  
Author(s):  
William J. Emblom ◽  
Klaus J. Weinmann

This paper describes the development and implementation of closed-loop control for oval stamp forming tooling using MATLAB®’s SIMULINK® and the dSPACE®CONTROLDESK®. A traditional PID controller was used for the blank holder pressure and an advanced controller utilizing fuzzy logic combining a linear quadratic gauss controller and a bang–bang controller was used to control draw bead position. The draw beads were used to control local forces near the draw beads. The blank holder pressures were used to control both wrinkling and local forces during forming. It was shown that a complex, advanced controller could be modeled using MATLAB’s SIMULINK and implemented in DSPACE CONTROLDESK. The resulting control systems for blank holder pressures and draw beads were used to control simultaneously local punch forces and wrinkling during the forming operation thereby resulting in a complex control strategy that could be used to improve the robustness of the stamp forming processes.


Author(s):  
Amjed A. Al-mousa ◽  
Ali H. Nayfeh ◽  
Pushkin Kachroo

Abstract Rotary cranes (tower cranes) are common industrial structures that are used in building construction, factories, and harbors. These cranes are usually operated manually. With the size of these cranes becoming larger and the motion expected to be faster, the process of controlling them became difficult without using automatic control methods. In general, the movement of cranes has no prescribed path. Cranes have to be run under different operating conditions, which makes closed-loop control preferable. In this work a fuzzy logic controller is introduced with the idea of split-horizon; that is, fuzzy inference engines (FIE) are used for tracking the position and others are used for damping the load oscillations. The controller consists of two independent controllers: radial and rotational. Each of these controllers has two fuzzy inference engines (FTEs). Computer simulations are used to verify the performance of the controller. Three simulation cases are introduced: radial, compound, and damping. The results from the simulations show that the fuzzy controller is capable of keeping the load-oscillation angles small throughout the maneuvers while completing them in a relatively reasonable time.


2021 ◽  
Author(s):  
Mustafa Shakir ◽  
Sohaib Aslam ◽  
Muhammad Adnan ◽  
Kashif A. Janjua

1998 ◽  
Vol 38 (3) ◽  
pp. 209-217 ◽  
Author(s):  
J. Ferrer ◽  
M. A. Rodrigo ◽  
A. Seco ◽  
J. M. Penya-roja

An aeration fuzzy logic based control system has been developed and tested in the main aerobic reactor of a BARDENPHO process pilot plant. This system has been compared with two ordinary aeration process controllers: one- and two-aeration-level on/off controllers. Energy savings of about 40% over the one-level on/off controller and a more stable closed-loop response have been obtained. Thus, an improvement of about 60% in average deviation can be accomplished by the use of an AFLBC.


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