Application of multi-region fuzzy logic to some model flow control problems

1998 ◽  
Author(s):  
Kyungmoon Nho ◽  
Ramesh Agarwal
Keyword(s):  
Fuzzy Logic ◽  
Flow Control ◽  
Control Problems ◽  
Model Flow

Neural network approaches to some model flow control problems

1997 ◽  
Author(s):  
Yongseung Cho ◽  
Ramesh Agarwal ◽  
Kyungmoon Nho ◽  
Yongseung Cho ◽  
Ramesh Agarwal ◽  
...  
Keyword(s):  
Neural Network ◽  
Flow Control ◽  
Control Problems ◽  
Model Flow ◽  
Network Approaches

Vortex Flow Controllers in Sanitary Engineering

1984 ◽  
Vol 106 (2) ◽  
pp. 129-133 ◽  
Author(s):  
H. Brombach
Keyword(s):  
Flow Control ◽  
Flow Pattern ◽  
Flow Resistance ◽  
Vortex Flow ◽  
Vortex Chamber ◽  
Control Problems ◽  
Inlet Port ◽  
Input Pressure ◽  
Conical Vortex ◽  
Moving Parts

Flow control problems in combined sewerage systems can be solved with the aid of a new variation of the vortex amplifier. This valve has no moving parts, and comes under the category of pure fluidics; it has a conical vortex chamber and a single inlet port. Depending on the level of water in the vortex chamber the flow pattern may be either axially symmetrical or axially asymmetrical. This effect enables the device to alter its flow resistance in response to the input pressure. Several hundred of this type of the flow controller are already in operation. An example of their application is described below.

scholarly journals Computational Methods for Modelling and Optimization of Flow Control Devices

Energies ◽  
2020 ◽  
Vol 13 (14) ◽  
pp. 3710 ◽  
Author(s):  
Alejandro Ballesteros-Coll ◽  
Unai Fernandez-Gamiz ◽  
Iñigo Aramendia ◽  
Ekaitz Zulueta ◽  
Jose Manuel Lopez-Guede
Keyword(s):  
Flow Control ◽  
Vortex Generators ◽  
Performance Study ◽  
Mesh Model ◽  
Flow Control Devices ◽  
Model Flow ◽  
Working Together ◽  
A Cell ◽  
Control Devices ◽  
Modelling And Optimization

Over the last few years, the advances in size and weight for wind turbines have led to the development of flow control devices. The current work presents an innovative method to model flow control devices based on a cell-set model, such as Gurney flaps (GFs). This model reuses the cells which are around the required geometry and a wall boundary condition is assigned to the generated region. Numerical simulations based on RANS equations and with Re = 2 × 10 6 have been performed. Firstly, a performance study of the cell-set model on GFs was carried out by comparing it with a fully mesh model of a DU91W250 airfoil. A global relative error of 1.13% was calculated. Secondly, optimum GF lengths were determined (from 0% to 2% of c) for a DU97W300 airfoil and an application of them. The results showed that for lower angles of attack (AoAs) larger GFs were needed, and as the AoA increased, the optimum GF length value decreased. For the purpose of studying the effects generated by two flow control devices (vortex generators (VGs) and optimum GF) working together, a triangular VG based on the jBAY model was implemented. Resulting data indicated, as expected, that when both flow control devices were implemented, higher CL and lower CD values appeared.

scholarly journals Fuzzy Dynamic Adaptation of Gap Generation and Mutation in Genetic Optimization of Type 2 Fuzzy Controllers

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Leticia Cervantes ◽  
Oscar Castillo ◽  
Denisse Hidalgo ◽  
Ricardo Martinez-Soto
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Logic ◽  
Flight Control ◽  
Fuzzy Systems ◽  
Performance Enhancement ◽  
Fuzzy Controller ◽  
Control Problems ◽  
Genetic Optimization ◽  
Two Parameters

We propose to use an approach based on fuzzy logic for the adaptation of gap generation and mutation probability in a genetic algorithm. The performance of this method is presented with the benchmark problem of flight control and results show how it can decrease the error during the flight of an airplane using fuzzy logic for some parameters of the genetic algorithm. In this case of study, we use fuzzy systems for adapting two parameters of the genetic algorithm to improve the design of a type 2 fuzzy controller and enhance its performance to achieve flight control. Finally, a statistical test is presented to prove the performance enhancement in the application using fuzzy adaptation in the genetic algorithm. It is important to mention that not only is this idea for control problems but also it can be used in pattern recognition and many different problems.

Existence of optimal controls for viscous flow problems

1992 ◽  
Vol 439 (1905) ◽  
pp. 81-102 ◽  
Keyword(s):  
Optimal Control ◽  
Flow Control ◽  
Viscous Flow ◽  
Existence Theorem ◽  
General Class ◽  
Optimal Control Problems ◽  
Control Problems ◽  
Optimal Controls ◽  
Flow Problems ◽  
Existence Of Optimal Controls

A class of optimal control problems in viscous flow is studied. Main result is the existence theorem for optimal control. Three typical flow control problems are formulated within this general class.

scholarly journals Fuzzy Logic Control of a Ball on Sphere System

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Seyed Alireza Moezi ◽  
Ehsan Zakeri ◽  
Yousef Bazargan-Lari ◽  
Mahmood Khalghollah
Keyword(s):  
Fuzzy Logic ◽  
Dynamic Systems ◽  
Fuzzy Logic Control ◽  
Fuzzy Controller ◽  
Nonlinear Dynamic Systems ◽  
Underactuated System ◽  
Control Problems ◽  
Logic Control ◽  
Good State ◽  
Simulation Results

The scope of this paper is to present a fuzzy logic control of a class of multi-input multioutput (MIMO) nonlinear systems called “system of ball on a sphere,” such an inherently nonlinear, unstable, and underactuated system, considered truly to be two independent ball and wheel systems around its equilibrium point. In this work, Sugeno method is investigated as a fuzzy controller method, so it works in a good state with optimization and adaptive techniques, which makes it very attractive in control problems, particularly for such nonlinear dynamic systems. The system’s dynamic is described and the equations are illustrated. The outputs are shown in different figures so as to be compared. Finally, these simulation results show the exactness of the controller’s performance.

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