85 research outputs found
Output-Feedback Control of Nonlinear Systems using Control Contraction Metrics and Convex Optimization
Control contraction metrics (CCMs) are a new approach to nonlinear control
design based on contraction theory. The resulting design problems are expressed
as pointwise linear matrix inequalities and are and well-suited to solution via
convex optimization. In this paper, we extend the theory on CCMs by showing
that a pair of "dual" observer and controller problems can be solved using
pointwise linear matrix inequalities, and that when a solution exists a
separation principle holds. That is, a stabilizing output-feedback controller
can be found. The procedure is demonstrated using a benchmark problem of
nonlinear control: the Moore-Greitzer jet engine compressor model.Comment: Conference submissio
Control Contraction Metrics on Finsler Manifolds
Control Contraction Metrics (CCMs) provide a nonlinear controller design
involving an offline search for a Riemannian metric and an online search for a
shortest path between the current and desired trajectories. In this paper, we
generalize CCMs to Finsler geometry, allowing the use of non-Riemannian
metrics. We provide open loop and sampled data controllers. The sampled data
control construction presented here does not require real time computation of
globally shortest paths, simplifying computation.Comment: accepted to 2018 American Control Conferenc
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