The optimal control methodology called concentration-of-measure optimal control (COMOC), seeks to minimise a concen- tration-of-measure upper bound on the probability of failure of an uncertain system. This bound is computed for a system characterised by a single performance measure depending on random inputs.

This work considers controlled multibody dynamics taking place in an uncertain environment. The goal is to quantify uncertainty in a controlled robot manoeuvre and to minimise the probability of failure with regard to a performance measure. First, a deterministic optimal control problem is solved, yielding state and control trajectories that minimise an objective function. Boundary conditions for the optimal control problem are chosen such that the system performs ideally in the sense of the performance measure. Secondly, the obtained manoeuvre is reconsidered in the presence of uncertainty. Using a concentration-of-measure inequality, a rigorous upper bound for the probability of failure is derived. Finally, an optimisation is performed that searches for a control sequence (in the neighbourhood of the given one), that minimises the probability of failure.

}, author = {Leyendecker, Sigrid and Lucas, Leonard J. and Owhadi, Houman and Ortiz, Michael}, booktitle = {PAMM}, date = {2010-03-22/2010-03-26}, doi = {10.1002/pamm.201010303}, faupublication = {no}, note = {UnivIS-Import:2015-04-16:Pub.2010.tech.FT.ltd.certif}, pages = {621-622}, peerreviewed = {unknown}, title = {{Certification} with optimal control strategies}, venue = {Karlsruhe, Germany}, volume = {10}, year = {2010} }