Improving Simulink Design Optimization Performance Using Parallel Computing 1.0

Estimating plant model parameters and tuning controllers are challenging tasks. Optimization-based methods help to systematically accelerate the tundlTCing process and let engineers tune multiple parameters at the same time. Further efficiencies can be gained by running the optimization in a parallel setting and distributing the computational load across multiple MATLAB workersd-deOCLbut how do you know when an optimization problem is a good candidate for parallelization?Using an aerospace system model as an example, this article describes the paraldlTClelization of a controller parameter tuning task using Parallel Computing Toolbox and Simulink Design Optimization. Topics covered include setting up an optimizadlTCtion problem for parallel computing, the types of models that benefit from parallel optimization, and the typical optimization speed-up that can be achieved.By Alec Stothert and Arkadiy Turevskiy, The MathWorksThis article was published in MATLAB Digest, May 2009, which you can read at http://www.mathworks.com/company/newsletters/?s_cid=nws_flex

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Platforms:	Matlab
Keyword:	Article,  Computing,  Controller,  Covered,  Describes,  Design,  Include,  Mathworksthis,  Optimiza Tion,  Optimization,  Paral Lelization,  Parallel,  Parameter,  Published,  Simulink,  Toolbox,  Topics,  Turevskiy
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