Estimating plant model parameters and tuning controllers are challenging tasks. Optimization-based methods help to systematically accelerate the tuning 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 workers—but how do you know when an optimization problem is a good candidate for parallelization?
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