Optimisation of fuzzy logic quadrotor attitude controller – particle swarm, cuckoo search and BAT algorithms

Author(s):  
Mohamed Siddiq Zatout ◽  
Amar Rezoug ◽  
Abdellah Rezoug ◽  
Khalifa Baizid ◽  
Jamshed Iqbal
Author(s):  
Fachrudin Hunaini ◽  
Imam Robandi ◽  
Nyoman Sutantra

Fuzzy Logic Control (FLC) is a reliable control system for controlling nonlinear systems, but to obtain optimal fuzzy logic control results, optimal Membership Function parameters are needed. Therefore in this paper Particle Swarm Optimization (PSO) is used as a fast and accurate optimization method to determine Membership Function parameters. The optimal control system simulation is carried out on the automatic steering system of the vehicle model and the results obtained are the vehicle's lateral motion error can be minimized so that the movement of the vehicle can always be maintained on the expected trajectory


Author(s):  
Honglei Xu ◽  
Linhuan Wang

In order to improve the accuracy of dynamic detection of wind field in the three-dimensional display space, system software is carried out on the actual scene and corresponding airborne radar observation information data, and the particle swarm algorithm fuzzy logic algorithm is introduced into the wind field dynamic simulation process in three-dimensional display space, to analyze the error of the filtering result in detail, to process the hurricane Lily Doppler radar measurement data with the optimal adaptive filtering according to the error data. The three-dimensional wind field synchronous measurement data obtained by filtering was compared with three-dimensional wind field synchronous measurement data of the GPS dropsonde in this experiment, the sea surface wind field measurement data of the multi-band microwave radiometer, and the wind field data at aircraft altitude.


2018 ◽  
Vol 33 (10) ◽  
pp. 40-50 ◽  
Author(s):  
German David Goez-Sanchez ◽  
Jorge Alberto Jaramillo-Garzon ◽  
Ricardo Andres Velasquez

2008 ◽  
Vol 5 (2) ◽  
pp. 247-262 ◽  
Author(s):  
Boumediene Allaoua ◽  
Abderrahmani Abdessalam ◽  
Gasbaoui Brahim ◽  
Nasri Abdelfatah

Author(s):  
Viswanathan Ramasamy ◽  
Jagatheswari Srirangan ◽  
Praveen Ramalingam

In Intelligent Transport Systems, traffic management and providing stable routing paths between vehicles using vehicular ad hoc networks (VANET's) is critical. Lots of research and several routing techniques providing a long path lifetime have been presented to resolve this issue. However, the routing algorithms suffer excessive overhead or collisions when solving complex optimization problems. In order to improve the routing efficiency and performance in the existing schemes, a Position Particle Swarm Optimization based on Fuzzy Logic (PPSO-FL) method is presented for VANET that provides a high-quality path for communication between nodes. The PPSO-FL has two main steps. The first step is selecting candidate nodes through collectively coordinated metrics using the fuzzy logic technique, improving packet delivery fraction, and minimizing end-to-end delay. The second step is the construction of an optimized routing model. The optimized routing model establishes an optimal route through the candidate nodes using position-based particle swarm optimization. The proposed work is simulated using an NS2 simulator. Simulation results demonstrate that the method outperforms the standard routing algorithms in packet delivery fraction, end-to-end delay and execution time for routing in VANET scenarios.


2013 ◽  
Vol 72 (7) ◽  
pp. 34-37
Author(s):  
Labeed Hassan ◽  
Seyed Hossein Sadati ◽  
Mohamad Bagher Malaeak ◽  
Mohamad Ali Ashtiani ◽  
Jalal Karimi

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