Abstract
Sliding mode controllers are frequently employed to track reference signals in the presence of model errors provided a worst-case bound on such errors is known. The uncertainty bound is often chosen through intuition or heuristic observations which can degrade control authority if the bound is too conservative. We describe a method for applying quantified parameter uncertainties obtained via Bayesian techniques to the design of sliding mode controllers. We illustrate the performance of this approach through numerical simulation in the context of ferroelectric actuator systems.
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