Neuro-aided H2 Controller Design for Aircraft under Actuator Failure

Conference paper
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 145)

Abstract

To advocate the development of new robust and reliable controllers, it has been defined a benchmark problem, where robust controllers are required for controlling a 6-Degree of Freedom (6-DOF) nonlinear F16 aircraft in auto-landing phase undergoing actuator failures. This paper attempt to provide a solution by developing a robust Neural Network (Neuro) aided H2 controller. Simulation results show that the fault tolerant performance of the proposed Neuro-aided H2 controller is better than H2 controller under actuator failure condition, both the number of hidden neurons and the time of on-line learning are small enough to be used in engineer problems.

Keywords

Radial Basis Function Radial Basis Function Neural Network Neural Controller Flight Control System Actuator Failure 
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 GmbH Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.School of AutomationNorthwestern Polytechnical UniversityXianChina

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