Disturbance rejection in nonlinear systems using neural networks

S Mukhopadhyay1, K S Narendra

  • 1Dept. of Electr. Eng., Yale Univ., New Haven, CT.

Summary

This study introduces a novel method using neural networks to minimize input disturbances in nonlinear systems. The approach expands the state space to reject unwanted effects, enhancing system control and identification.

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