Neuromorphic Control

TL;DR

This paper presents a neuromorphic control approach inspired by biological neural systems, utilizing mixed feedback loops to develop scalable, hardware-based control methods for neuromorphic circuits.

Contribution

It introduces a novel mixed-feedback control methodology based on biological principles, implemented with neuromorphic hardware for scalable neural network control.

Findings

Demonstrates control via input-output shaping in neuromorphic circuits

Shows scalability of mixed-feedback principles in network examples

Proposes a simple, biologically inspired control design

Abstract

Neuromorphic engineering is a rapidly developing field that aims to take inspiration from the biological organization of neural systems to develop novel technology for computing, sensing, and actuating. The unique properties of such systems call for new signal processing and control paradigms. The article introduces the mixed feedback organization of excitable neuronal systems, consisting of interlocked positive and negative feedback loops acting in distinct timescales. The principles of biological neuromodulation suggest a methodology for designing and controlling mixed-feedback systems neuromorphically. The proposed design consists of a parallel interconnection of elementary circuit elements that mirrors the organization of biological neurons and utilizes the hardware components of neuromorphic electronic circuits. The interconnection structure endows the neuromorphic systems with a simple control methodology that reframes the neuronal control as an input-output shaping problem. The potential of neuronal control is illustrated on elementary network examples that suggest the scalability of the mixed-feedback principles.