Multiobjective fuzzy genetic algorithm optimization approach to nonlinear control system design

1996 ◽  
Author(s):  
A. Trebi-Ollennu
Keyword(s):  
Genetic Algorithm ◽  
Control System ◽  
Nonlinear Control ◽  
System Design ◽  
Control System Design ◽  
Optimization Approach ◽  
Algorithm Optimization ◽  
Genetic Algorithm Optimization ◽  
Fuzzy Genetic Algorithm ◽  
Fuzzy Genetic

scholarly journals Genetic Algorithm Optimization and Control System Design of Flexible Structures

2008 ◽  
Vol 17 (Supplement) ◽  
Author(s):  
M.O. Tokhi ◽  
M.Z. Md Zain ◽  
M.S. Alam ◽  
F.M. Aldebrez ◽  
S.Z. Mohd Hashim ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Control System ◽  
System Design ◽  
Flexible Structures ◽  
Control System Design ◽  
Algorithm Optimization ◽  
Genetic Algorithm Optimization ◽  
Optimization And Control ◽  
And Control

Knowledge-Based Automatic Fault Detection in Flight Control System

2007 ◽  
Author(s):  
C. H. Lo ◽  
Eric H. K. Fung ◽  
Y. K. Wong
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Control System ◽  
Fault Detection ◽  
Flight Control ◽  
Detection System ◽  
Flight Control System ◽  
Actuator Failure ◽  
Fuzzy Genetic Algorithm ◽  
Fuzzy Genetic

There are various possible failures, like, actuator, sensor, or structural, which can occur on a sophisticated modern aircraft. In certain situations the need for an automatic fault detection system provides additional information about the status of the aircraft to assist pilots to compensate for failures. In this paper, we develop an intelligent technique based on fuzzy-genetic algorithm for automatically detecting failures in flight control system. The fuzzy-genetic algorithm is proposed to construct the automatic fault detection system for monitoring aircraft behaviors. Fuzzy system is employed to estimates the times and types of actuator failure. Genetic algorithms are used to generate an optimal fuzzy rule set based on the training data. The optimization capability of genetic algorithms provides and efficient and effective way to generate optimal fuzzy rules. Different types of actuator failure can be detected by the fuzzy-genetic algorithm based automatic fault detection system after tuning its rule table. Simulations with different actuator failures of the non-linear F-16 aircraft model are conducted to appraise the performance of the proposed automatic fault detection system.

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