Intelligent Systems
Note: This research group has relocated.

6 results (View BibTeX file of all listed publications)

2016

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Supplemental material for ’Communication Rate Analysis for Event-based State Estimation’

Ebner, S., Trimpe, S.

Max Planck Institute for Intelligent Systems, January 2016 (techreport)

PDF [BibTex]

2016

Ebner, S., Trimpe, S. Supplemental material for ’Communication Rate Analysis for Event-based State Estimation’ Max Planck Institute for Intelligent Systems, January 2016 (techreport)

PDF [BibTex]

2015

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Distributed Event-based State Estimation

Trimpe, S.

Max Planck Institute for Intelligent Systems, November 2015 (techreport)

Abstract
An event-based state estimation approach for reducing communication in a networked control system is proposed. Multiple distributed sensor-actuator-agents observe a dynamic process and sporadically exchange their measurements and inputs over a bus network. Based on these data, each agent estimates the full state of the dynamic system, which may exhibit arbitrary inter-agent couplings. Local event-based protocols ensure that data is transmitted only when necessary to meet a desired estimation accuracy. This event-based scheme is shown to mimic a centralized Luenberger observer design up to guaranteed bounds, and stability is proven in the sense of bounded estimation errors for bounded disturbances. The stability result extends to the distributed control system that results when the local state estimates are used for distributed feedback control. Simulation results highlight the benefit of the event-based approach over classical periodic ones in reducing communication requirements.

arXiv [BibTex]

2015

Trimpe, S. Distributed Event-based State Estimation Max Planck Institute for Intelligent Systems, November 2015 (techreport)

arXiv [BibTex]

Gaussian Process Optimization for Self-Tuning Control
Gaussian Process Optimization for Self-Tuning Control

Marco, A.

Polytechnic University of Catalonia (BarcelonaTech), October 2015 (mastersthesis)

PDF Project Page Project Page [BibTex]

Marco, A. Gaussian Process Optimization for Self-Tuning Control Polytechnic University of Catalonia (BarcelonaTech), October 2015 (mastersthesis)

PDF Project Page Project Page [BibTex]

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Adaptive and Learning Concepts in Hydraulic Force Control

Doerr, A.

University of Stuttgart, September 2015 (mastersthesis)

[BibTex]

Doerr, A. Adaptive and Learning Concepts in Hydraulic Force Control University of Stuttgart, September 2015 (mastersthesis)

[BibTex]

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Policy Search for Imitation Learning

Doerr, A.

University of Stuttgart, January 2015 (thesis)

link (url) Project Page [BibTex]