Parallel synthesis of robust control systems

Wolfgang M. Schubert; Robert F. Stengel

doi:10.1109/87.726531

Parallel synthesis of robust control systems

Wolfgang M. Schubert, Robert F. Stengel

Mechanical & Aerospace Engineering

Research output: Contribution to journal › Article › peer-review

14 Scopus citations

Abstract

Parallel computing is used to evaluate compensator robustness numerically and to automate the design of control systems. Robustness is quantified by Monte Carlo evaluation of the effects of plant-parameter uncertainty, and it is maximized by searching the control-design-parameter space with a genetic algorithm. This design approach requires considerable computation, and parallel computing can reduce execution times. Because evaluation times vary among trials, computation time could be prolonged if some nodes remain idle while others finish their tasks. A dynamic scheduler is proposed as a solution. Theoretical and experimental results for a shared-virtual-memory computer illustrate that speed-up of controller design computations is nearly linear in the number of computing nodes.

Original language	English (US)
Pages (from-to)	701-706
Number of pages	6
Journal	IEEE Transactions on Control Systems Technology
Volume	6
Issue number	6
DOIs	https://doi.org/10.1109/87.726531
State	Published - 1998

All Science Journal Classification (ASJC) codes

Control and Systems Engineering
Electrical and Electronic Engineering

Keywords

Control systems
Design methodology
Parallel processing

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10.1109/87.726531

Cite this

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abstract = "Parallel computing is used to evaluate compensator robustness numerically and to automate the design of control systems. Robustness is quantified by Monte Carlo evaluation of the effects of plant-parameter uncertainty, and it is maximized by searching the control-design-parameter space with a genetic algorithm. This design approach requires considerable computation, and parallel computing can reduce execution times. Because evaluation times vary among trials, computation time could be prolonged if some nodes remain idle while others finish their tasks. A dynamic scheduler is proposed as a solution. Theoretical and experimental results for a shared-virtual-memory computer illustrate that speed-up of controller design computations is nearly linear in the number of computing nodes.",

keywords = "Control systems, Design methodology, Parallel processing",

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note = "Funding Information: Manuscript received August 12, 1996. Recommended by Associate Editor, E. G. Collins, Jr. This work was supported by the Federal Aviation Administration and the National Aeronautics and Space Administration under Grant 95-G-011, and used computers located at the Cornell Theory Center.",

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AB - Parallel computing is used to evaluate compensator robustness numerically and to automate the design of control systems. Robustness is quantified by Monte Carlo evaluation of the effects of plant-parameter uncertainty, and it is maximized by searching the control-design-parameter space with a genetic algorithm. This design approach requires considerable computation, and parallel computing can reduce execution times. Because evaluation times vary among trials, computation time could be prolonged if some nodes remain idle while others finish their tasks. A dynamic scheduler is proposed as a solution. Theoretical and experimental results for a shared-virtual-memory computer illustrate that speed-up of controller design computations is nearly linear in the number of computing nodes.

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Parallel synthesis of robust control systems

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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