Optimization of control parameters for genetic algorithms
IEEE Transactions on Systems, Man and Cybernetics
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Development of an integrated fuzzy-logic-based missile guidance law against high speed target
IEEE Transactions on Fuzzy Systems
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Fuzzy logic controller (FLC) is well-known of its robustness to parameter variations and ability to reject noise. But its design requires defining many parameters. In this work, a systematic and simple procedure is proposed to develop an integrated fuzzy based guidance law which consists of three FLC. Each one of them is activated in a region of the interception. To allow smooth transition between these controllers, another fuzzy-based switching system is introduced. The parameters of all the fuzzy controllers which include the distribution of the membership functions and the rules are simply obtained by observing the function of each controller. Furthermore, these parameters are optimally tuned by the method of genetic algorithms through solving an optimization problem to minimize the interception time, the missile acceleration commands and the miss distance. The simulation results show that the proposed procedure was able to generate a guidance law with a satisfactory performance.