From 111f1a4588e26446632b826b62860103e3963e71 Mon Sep 17 00:00:00 2001 From: Dane Sabo Date: Wed, 16 Oct 2024 09:54:38 -0400 Subject: [PATCH] vault backup: 2024-10-16 09:54:38 --- 4 Qualifying Exam/2 Writing/2. QE State of the Art.md | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/4 Qualifying Exam/2 Writing/2. QE State of the Art.md b/4 Qualifying Exam/2 Writing/2. QE State of the Art.md index bd600e8d0..e9984445c 100644 --- a/4 Qualifying Exam/2 Writing/2. QE State of the Art.md +++ b/4 Qualifying Exam/2 Writing/2. QE State of the Art.md @@ -16,7 +16,9 @@ type: single # Take 1 ## Attempt -Robust control as a field determines how resilient a control system is to a difference in plant dynamics for a given characteristic. This characteristic can be anything, but usually is either the performance or stability of the system. (Talk about what perturbations are in general) +Robust control as a field determines how resilient a control system is to a difference in plant dynamics for a given characteristic. In a real system, there will always be some inaccuracy in the model of plant dynamics, disturbances, or other noise. These unmodeled features will affect plant behavior if they are not anticipated. Robust control gives us tools to design for these perturbations proactively. We can design characteristics such as performance and stability to guarantee as 'robust'. + +Robustness is dependent on two features: the characteristic to be guaranteed, and the set of reasonably possible perturbed plants $\mathcal{P}$. Usually the characteristic we're interested in is internal stability or performance. The possible set of plants, however, is less straightforward. (The disk multiplicative perturbation)