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A Fast Multiscale Method for Approximate Explicit Model Predictive Control


S. Summers

IfA Internal Seminar Series

A model predictive control law is given by the solution to a parameteric optimization problem that can be pre-computed offline and provides an explicit optimal map from state to control input. In this talk, an algorithm is introduced based on classical wavelet multiresolution analysis that returns a low complexity explicit model predictive control law built on a hierarchy of second order interpolating wavelets. It is proven that the resulting interpolation is everywhere feasible. Further, tests to confirm stability and to compute a bound on the performance loss are introduced. Since the controller approximation is built on a gridded hierarchy, the evaluation of the control law in real-time systems is naturally fast and runs in a bounded logarithmic time.


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J. Lygeros

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