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arXiv · 2606.05189

Bio-plausible Neuromorphic Disturbance Observer Based on Emulation Theory: Extended Version

Hongfu Xu·Xiaoyu Guo·Shengbo Wang·Shuo Gao
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Abstract

Biological neural systems achieve remarkable robustness and adaptability in uncertain environments through sparse, event-driven spike-based information processing and adaptive regulation. Inspired by this paradigm, this paper develops a neuromorhpic disturbance observer (NDO) and control framework that replaces conventional continuous-time signal representations with spike-timing encoding. Both disturbance estimates and control inputs are constructed via integrate-and-fire (IF) neuron dynamics from discrete spike events, yielding intrinsically event-driven updates. An adaptive-threshold triggering mechanism is inspired by spike-frequency adaptation (SFA), enabling history-dependent regulation of spike generation. Simulation results demonstrate that the proposed framework achieves neurally inspired robustness and adaptability, while the adaptive-threshold spiking scheme reduces spike events to 42.6% of the fixed-threshold case under noisy conditions.

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Hongfu Xu, Xiaoyu Guo, Shengbo Wang, Shuo Gao. 2026-05-05. Bio-plausible Neuromorphic Disturbance Observer Based on Emulation Theory: Extended Version. https://arxiv.org/abs/2606.05189

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