Neuromorphic-computing-based feedback control: A cognitive supervisory control framework

In this paper, we propose and explain a novel control system that mimics the intrinsic human thinking and decision-making processes. Specifically, we propose a neuromorphic-computing-based cognitive feedback control framework, which consists of a neuronic network model and a hybrid controller, for the supervisory control of a general dynamical system. The dynamical system is controlled by the hybrid controller embedded with consensus and optimization, while the neuronal network model mimics the brain dynamics and determines the safe/unsafe mode of the hybrid controller. Several theoretical results are given, and computer simulation with unknown disturbances added helps illustrate the ideas presented in this paper.

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