Robust Experiment Design through Randomisation with Chance Constraints
World Congress, Volume # 18 | Part# 1
Welsh, James; Kong, He
Digital Object Identifier (DOI)
Input and excitation design
It is well known that robust optimal experiment design is an extremely computationally expensive problem. The design is generally solved by discretisation of the design space resulting in a discrete semi-infinite convex programming problem. To ease the computational burden it is possible to solve the design problem using the scenario approach to robust convex optimisation. In this paper we examine the application of a recently proposed idea of `variable robustness' to the experiment design problem. This approach provides insight into the problem in terms of the effect of reducing the number of scenarios in a manner that has a suitable trade-off between performance and guarantees. A numerical example is used to examine the applicability to robust experiment design.
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