Evolved auxiliary controller with applications to aerospace

Tim Chen, N. Kapronand, C. Y. Hsieh, J. Cy Chen

Research output: Contribution to journalArticlepeer-review


Purpose: To guarantee the asymptotic stability of discrete-time nonlinear systems, this paper aims to propose an evolved bat algorithm fuzzy neural network (NN) controller algorithm. Design/methodology/approach: In evolved fuzzy NN modeling, the NN model and linear differential inclusion representation are established for the arbitrary nonlinear dynamics. The control problems of the Fisher equation and a temperature cooling fin for high-speed aerospace vehicles will be described and demonstrated. The signal auxiliary controlled system is represented for the nonlinear parabolic partial differential equation (PDE) systems and the criterion of stability is derived via the Lyapunov function in terms of linear matrix inequalities. Findings: This representation is constructed by sector nonlinearity, which converts the nonlinear model to a multiple rule base for the linear model and a new sufficient condition to guarantee the asymptotic stability. Originality/value: This study also injects high frequency as an auxiliary and the control performance to stabilize the nonlinear high-speed aerospace vehicle system.

Original languageEnglish
JournalAircraft Engineering and Aerospace Technology
Early online date6 May 2021
Publication statusE-pub ahead of print - 6 May 2021


  • Aerospace vehicle
  • Artificial intelligence
  • Automated design
  • Linear matrix inequality

ASJC Scopus subject areas

  • Aerospace Engineering

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