Genetic Optimization Design of Type-1 and Type-2 Fuzzy Systems for Longitudinal Control of an Airplane

  • Oscar Castillo
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 272)


In this chapter we present the design of fuzzy systems for the longitudinal control of an F-14 airplane using genetic algorithms [23]. The longitudinal control is carried out by controlling only the elevators of the airplane. To carry out such control it is necessary to use the stick, the rate of elevation and the angle of attack. These 3 variables are the input to the fuzzy inference system, which is of Mamdani type, and we obtain as output the value of the elevators. After designing the fuzzy inference system we turn to the simulation stage. Simulation results of the longitudinal control are obtained using a plant in Simulink and those results are compared against the PID controller. For optimizing the fuzzy logic control design we use a genetic algorithm.


Genetic Algorithm Membership Function Fuzzy System Fuzzy Controller Fuzzy Inference System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Computer ScienceTijuana Institute of TechnologyChula VistaUSA

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