Autonomic computing software for autonomous space vehicles

Abstract

Current space missions increasingly demand more autonomy in control architectures for Unmanned Space Vehicles (USVs), so unmanned longterm missions can be afforded. Continuous assurance of effective adaptation to unpredictable internal and external changes, along with efficient management of resources is essential for such requirements. One of the attractive solutions is that inspired by the physiology of living systems, where self-regulation helps to achieve continuous adaptation to the environment by changing internal conditions. The physiological functions are performed by nervous system reflexes that are the foundations for self-regulatory mechanisms such as homeostasis. Building artificial self-regulation similar to biological ones into USVs makes them highly-viable and ultra-stable in order to support very long missions. This paper presents aspects of how to endow USVs with Artificial Nervous Reflexes (ANRs) by means of applying physiological principles of self-regulation to the USV's control architecture, so resilience and persistence can be supported. A case study of a composite orbiter is presented. The studied ANRs are needed to guarantee the self-regulation of response time (latency), operation temperature (thermoregulation), and power consumption (energy balance). Results from a cross-checked analysis of the above self-regulation mechanisms are also presented.