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Artificial homeostasis for vehicle control architecture of unmanned spacecraft

Insaurralde, Carlos C.; Vassev, Emil


Emil Vassev


Current space missions are increasingly demanding more autonomy in control architectures for Unmanned Space Vehicles (USVs), so unmanned long-term 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 as to self-regulation in order 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 the biological ones into USVs makes them highly-viable and ultra-stable in order to support very long missions. This paper presents aspects on how to endow USVs with Artificial Nervous Reflexes (ANRs) by means of applying physiological principles of self-regulation to the USV control architecture, so resilience and persistence can be supported. A case study of a composite orbiter (i.e. a USV) for the BepiColombo mission to Mercury is presented. The ANRs studied 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. © 2014 IEEE.


Insaurralde, C. C., & Vassev, E. (2014). Artificial homeostasis for vehicle control architecture of unmanned spacecraft.

Conference Name 2014 IEEE Aerospace Conference
Start Date Mar 1, 2014
End Date Mar 8, 2014
Acceptance Date Jan 1, 2014
Online Publication Date Jun 19, 2014
Publication Date Jun 19, 2014
Deposit Date Mar 10, 2020
Publisher Institute of Electrical and Electronics Engineers (IEEE)
Pages 1-9
ISBN 9781479916221
Keywords Physiology, Nervous system, Resilience, Monitoring, Adaptation models, Temperature measurement, Robots
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