An input-output based robust stabilization criterion for neural-network control of nonlinear systems

J Fernández de Cañete1, A Barreiro, A García-Cerezo

  • 1Departmento de Ingenería de Sistemas y Automatica, ETSI Industriales, Universidad de Málaga, Málaga 29071, Spain. canete@ctima.uma.es

Summary

A new neural control method ensures system stability by adjusting controller dynamics and modifying training data. This approach enhances control for nonlinear systems with unknown dynamics, offering a simpler alternative to Lyapunov methods.

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