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Distributed set-based observers using diffusion strategies

المراقبون الموزعون القائمون على المجموعات باستخدام استراتيجيات الانتشار
Authors: Amr Alanwar; Jagat Jyoti Rath; Hazem Said; Karl Henrik Johansson; Matthias Althoff;

Distributed set-based observers using diffusion strategies

Abstract

Nous proposons deux observateurs basés sur des ensembles distribués utilisant des approches à base de bandes et de propagation d'ensembles pour des systèmes dynamiques linéaires à temps discret avec des incertitudes de modélisation et de mesure bornées. Les deux algorithmes utilisent une étape de diffusion basée sur un ensemble, qui diminue les erreurs d'estimation et la taille des ensembles estimés, et peuvent être considérés comme une approche légère pour parvenir à un consensus partiel entre les ensembles estimés distribués. Chaque nœud partage sa mesure avec son voisin lors de l'étape de mise à jour de la mesure. Dans l'étape de diffusion, les voisins croisent leurs ensembles estimés en utilisant notre nouvelle technique d'intersection de zonotopes légers. Un exemple de localisation démontre l'applicabilité de nos algorithmes.

Proponemos dos observadores distribuidos basados en conjuntos que utilizan enfoques basados en tiras y de propagación de conjuntos para sistemas dinámicos lineales de tiempo discreto con modelado acotado e incertidumbres de medición. Ambos algoritmos utilizan un paso de difusión basado en conjuntos, que disminuye los errores de estimación y el tamaño de los conjuntos estimados, y puede verse como un enfoque ligero para lograr un consenso parcial entre los conjuntos estimados distribuidos. Cada nodo comparte su medición con su vecino en el paso de actualización de la medición. En el paso de difusión, los vecinos cruzan sus conjuntos estimados utilizando nuestra novedosa técnica de intersección zonotopo ligera. Un ejemplo de localización demuestra la aplicabilidad de nuestros algoritmos.

We propose two distributed set-based observers using strip-based and set-propagation approaches for linear discrete-time dynamical systems with bounded modeling and measurement uncertainties. Both algorithms utilize a set-based diffusion step, which decreases the estimation errors and the size of estimated sets, and can be seen as a lightweight approach to achieve partial consensus between the distributed estimated sets. Every node shares its measurement with its neighbor in the measurement update step. In the diffusion step, the neighbors intersect their estimated sets using our novel lightweight zonotope intersection technique. A localization example demonstrates the applicability of our algorithms.

نقترح اثنين من المراقبين الموزعين على أساس المجموعات باستخدام النهج القائمة على الشريط والانتشار المحدد للأنظمة الديناميكية الخطية المنفصلة مع النمذجة المحدودة وعدم اليقين في القياس. تستخدم كلتا الخوارزميتين خطوة نشر قائمة على المجموعة، مما يقلل من أخطاء التقدير وحجم المجموعات المقدرة، ويمكن النظر إليها على أنها نهج خفيف الوزن لتحقيق إجماع جزئي بين المجموعات المقدرة الموزعة. تشارك كل عقدة قياسها مع جارتها في خطوة تحديث القياس. في خطوة الانتشار، يتقاطع الجيران مع مجموعاتهم المقدرة باستخدام تقنية التقاطع النطاقي خفيفة الوزن الجديدة. يوضح مثال التوطين إمكانية تطبيق خوارزمياتنا.

Keywords

Signal Processing (eess.SP), Artificial intelligence, Nonlinear dimensionality reduction, Structural engineering, linear discrete-time dynamical systems, Set (abstract data type), Systems and Control (eess.SY), Node (physics), Process Fault Detection and Diagnosis in Industries, Electrical Engineering and Systems Science - Systems and Control, Mathematical analysis, Bounded function, Diffusion, Discrete-time control/observation systems, Engineering, Distributed Optimization, FOS: Electrical engineering, electronic engineering, information engineering, Diffusion map, FOS: Mathematics, Electrical Engineering and Systems Science - Signal Processing, Observers, Mathematics - Optimization and Control, Physics, Distributed Control, set-based observers, Computer science, Dimensionality reduction, Programming language, Algorithm, Aerospace engineering, Model Predictive Control in Industrial Processes, Linear systems in control theory, Optimization and Control (math.OC), Control and Systems Engineering, Physical Sciences, Thermodynamics, Intersection (aeronautics), Networked Control Systems, Mathematics, ddc: ddc:

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
13
Top 10%
Top 10%
Top 10%
Green
hybrid