Designing image-based control systems considering workload variations

Sajid Mohamed; Asad Ullah Awan; Dip Goswami; A.A. (Twan) Basten

doi:10.1109/CDC40024.2019.9030035

Designing image-based control systems considering workload variations

Sajid Mohamed, Asad Ullah Awan, Dip Goswami, A.A. (Twan) Basten

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

8 Citations (Scopus)

138 Downloads (Pure)

Abstract

We consider the problem of designing an Image-
Based Control (IBC) application mapped to a multiprocessor platform. Sensing in IBC consists of compute-intensive image processing algorithms whose execution times are dependent on image workload. The challenge is that the IBC systems have a high (worst-case) workload with significant workload variations. Designing controllers for such IBC systems typically consider the worst-case workload that results in a long sensing delay with suboptimal quality-of-control (QoC). The challenge is: how to improve the QoC of IBC for a given multiprocessor platform allocation?

We present a controller synthesis method based on a Markovian jump linear system (MJLS) formulation considering workload variations. Our method assumes that system knowledge is available for modelling the workload variations as a Markov chain. We compare the MJLS-based method with two relevant control paradigms - LQR control considering worst-case workload, and switched linear control - with respect to QoC and available system knowledge. Our results show that taking into account workload variations in controller design benefits QoC. We then provide design guidelines on the control paradigm to choose for an IBC application given the requirements and the system knowledge.

Original language	English
Title of host publication	58th IEEE Conference on Decision and Control (CDC 2019)
Place of Publication	Piscataway
Publisher	Institute of Electrical and Electronics Engineers
Pages	3997-4004
Number of pages	8
ISBN (Electronic)	978-1-7281-1398-2
DOIs	https://doi.org/10.1109/CDC40024.2019.9030035
Publication status	Published - 12 Mar 2020
Event	58th IEEE Conference on Decision and Control, CDC 2019 - Nice, France, Nice, France Duration: 11 Dec 2019 → 13 Dec 2019 Conference number: 58 https://cdc2019.ieeecss.org/

Publication series

Name	Proceedings of the IEEE Conference on Decision and Control
Volume	2019-December
ISSN (Print)	0743-1546
ISSN (Electronic)	2576-2370

Conference

Conference	58th IEEE Conference on Decision and Control, CDC 2019
Abbreviated title	CDC 2019
Country/Territory	France
City	Nice
Period	11/12/19 → 13/12/19
Internet address	https://cdc2019.ieeecss.org/

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10.1109/CDC40024.2019.9030035

Author versionFinal author version , 1.11 MBLicence: CC BY-ND

Cite this

Mohamed, S., Awan, A. U., Goswami, D., & Basten, A. A. (2020). Designing image-based control systems considering workload variations. In 58th IEEE Conference on Decision and Control (CDC 2019) (pp. 3997-4004). Article 9030035 (Proceedings of the IEEE Conference on Decision and Control; Vol. 2019-December). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/CDC40024.2019.9030035

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title = "Designing image-based control systems considering workload variations",

abstract = "We consider the problem of designing an Image-Based Control (IBC) application mapped to a multiprocessor platform. Sensing in IBC consists of compute-intensive image processing algorithms whose execution times are dependent on image workload. The challenge is that the IBC systems have a high (worst-case) workload with significant workload variations. Designing controllers for such IBC systems typically consider the worst-case workload that results in a long sensing delay with suboptimal quality-of-control (QoC). The challenge is: how to improve the QoC of IBC for a given multiprocessor platform allocation?We present a controller synthesis method based on a Markovian jump linear system (MJLS) formulation considering workload variations. Our method assumes that system knowledge is available for modelling the workload variations as a Markov chain. We compare the MJLS-based method with two relevant control paradigms - LQR control considering worst-case workload, and switched linear control - with respect to QoC and available system knowledge. Our results show that taking into account workload variations in controller design benefits QoC. We then provide design guidelines on the control paradigm to choose for an IBC application given the requirements and the system knowledge.",

author = "Sajid Mohamed and Awan, {Asad Ullah} and Dip Goswami and Basten, {A.A. (Twan)}",

year = "2020",

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doi = "10.1109/CDC40024.2019.9030035",

language = "English",

series = "Proceedings of the IEEE Conference on Decision and Control",

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Mohamed, S, Awan, AU, Goswami, D & Basten, AA 2020, Designing image-based control systems considering workload variations. in 58th IEEE Conference on Decision and Control (CDC 2019)., 9030035, Proceedings of the IEEE Conference on Decision and Control, vol. 2019-December, Institute of Electrical and Electronics Engineers, Piscataway, pp. 3997-4004, 58th IEEE Conference on Decision and Control, CDC 2019, Nice, France, 11/12/19. https://doi.org/10.1109/CDC40024.2019.9030035

Designing image-based control systems considering workload variations. / Mohamed, Sajid; Awan, Asad Ullah; Goswami, Dip et al.
58th IEEE Conference on Decision and Control (CDC 2019). Piscataway: Institute of Electrical and Electronics Engineers, 2020. p. 3997-4004 9030035 (Proceedings of the IEEE Conference on Decision and Control; Vol. 2019-December).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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N2 - We consider the problem of designing an Image-Based Control (IBC) application mapped to a multiprocessor platform. Sensing in IBC consists of compute-intensive image processing algorithms whose execution times are dependent on image workload. The challenge is that the IBC systems have a high (worst-case) workload with significant workload variations. Designing controllers for such IBC systems typically consider the worst-case workload that results in a long sensing delay with suboptimal quality-of-control (QoC). The challenge is: how to improve the QoC of IBC for a given multiprocessor platform allocation?We present a controller synthesis method based on a Markovian jump linear system (MJLS) formulation considering workload variations. Our method assumes that system knowledge is available for modelling the workload variations as a Markov chain. We compare the MJLS-based method with two relevant control paradigms - LQR control considering worst-case workload, and switched linear control - with respect to QoC and available system knowledge. Our results show that taking into account workload variations in controller design benefits QoC. We then provide design guidelines on the control paradigm to choose for an IBC application given the requirements and the system knowledge.

AB - We consider the problem of designing an Image-Based Control (IBC) application mapped to a multiprocessor platform. Sensing in IBC consists of compute-intensive image processing algorithms whose execution times are dependent on image workload. The challenge is that the IBC systems have a high (worst-case) workload with significant workload variations. Designing controllers for such IBC systems typically consider the worst-case workload that results in a long sensing delay with suboptimal quality-of-control (QoC). The challenge is: how to improve the QoC of IBC for a given multiprocessor platform allocation?We present a controller synthesis method based on a Markovian jump linear system (MJLS) formulation considering workload variations. Our method assumes that system knowledge is available for modelling the workload variations as a Markov chain. We compare the MJLS-based method with two relevant control paradigms - LQR control considering worst-case workload, and switched linear control - with respect to QoC and available system knowledge. Our results show that taking into account workload variations in controller design benefits QoC. We then provide design guidelines on the control paradigm to choose for an IBC application given the requirements and the system knowledge.

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PB - Institute of Electrical and Electronics Engineers

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ER -

Designing image-based control systems considering workload variations

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Multiprocessor Image-Based Control: Model-Driven Optimisation

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