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

2026-05-05

AI Summary

This work addresses the challenge of robust estimation and adaptive control in uncertain environments by proposing a neuromorphic observer and control framework based on spike-timing-encoded signals. The approach integrates leaky integrate-and-fire neuron dynamics with a biologically inspired adaptive threshold mechanism to emulate spike-frequency adaptation, enabling history-dependent, event-driven updates. Compared to fixed-threshold schemes, the proposed method reduces spike events by 57.4% (down to 42.6% of the original count) under noisy conditions while preserving superior robustness and energy efficiency. This significant reduction in computational load enhances both the system’s adaptability and overall computational efficiency without compromising performance.

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.

Problem

• neuromorphic disturbance observer
• spike-based processing
• robustness
• adaptability
• event-driven control

Innovation

• neuromorphic disturbance observer
• spike-timing encoding
• integrate-and-fire neuron
• adaptive-threshold triggering
• spike-frequency adaptation