Print ISSN: 1681-6900

Online ISSN: 2412-0758

Keywords : Fuzzy Logic Control

Tuning of Composite Fuzzy Logic Guidance Law Using Genetic Algorithms

Saadi A. Al-Obaidi; Munther N. Al-Tikriti; Ammar Gh. Al-Ghizi

Engineering and Technology Journal, 2012, Volume 30, Issue 13, Pages 2341-2356

The application of Fuzzy Logic (FL) for the development of guidance laws for
homing missile is presented. Fuzzy logic has been used to develop a Composite
Fuzzy Guidance (CFG) law. The objective of this proposed guidance law is to
combine desirable features of PN and APN homing guidance laws to enhance the
interception of targets performing uncertain maneuvers without reaching the missile
to saturation limit.
During this work, it became apparent that the fuzzy controller of the CFG law can
be further tuned to enhance its performance. Genetic Algorithms (GAs) which are
inspired by natural genetics are one of the algorithms that can be used to tune the
parameters of fuzzy controllers due to the promising results that they introduced in
the field of optimization.
This paper introduces the integration of GAs and FL with a main emphasis on
tuning the membership function parameters of fuzzy logic controller of the proposed
CFG law using Genetic Algorithms (GAs) with the view to improve its performance.
The simulation has been performed using Borland C++ programming language
(version 5.02) along with the Matlab programming package (version 7.0) that has
been used for plotting the results of simulations.

Particle Swarm Optimization for Adapting Fuzzy Logic Controller of SPWM Inverter Fed 3-Phase I.M.

Fadhil A. Hassan; Lina J. Rashad

Engineering and Technology Journal, 2011, Volume 29, Issue 14, Pages 2912-2925

According to the high performance demand of speed control of an induction motor, Fuzzy Logic Controller (FLC) gives superior behavior over wide range of speed variation. Fuzzy logic is a robust controller for linear and non-linear system, even if good mathematical representation of the system is not available. But, adapting
fuzzy controller parameters is very complex and depends on operator experience. Particle Swarm Optimization (PSO) algorithm is proposed in this paper as an optimization technique for adapting centers and width of triangle inputs membership functions. The ordinary adapting method of FLC is represented too. Meanwhile, based on the concept of optimization, ways of defining the fitness function of the
PSO including different performance criteria are also illustrated. The complete mathematical model and simulation of an induction motor and inverter are represented in this paper. The simulation results demonstrate that the proposed PSOFL speed controller realizes a good dynamic behavior of the I.M with very good speed tracking.