Abstract
In this chapter, we focus on robust controller synthesis in the \(\mathcal{H}_{\infty}\) and structured singular value setting. The design solution is formulated in the form of linear matrix inequality conditions. Linear quadratic regulator, guaranteed-cost, and \(\mathcal{H}_{2}\) controller design problems are also discussed. The chapter ends with some historical notes on robustness and related discussions.
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Notes
- 1.
To this end, take , where \(D_{21}^{T\bot}\) is the orthogonal complement of \(D_{21}^{T}\), i.e. \(D_{21}D_{21}^{T\bot}=0\) and \(D_{21}^{T\bot T}D_{21}^{T\bot}=I\). Since \(D_{21}B_{1}^{T}=0\) we may write \(B_{1}^{T}=D_{21}^{T\bot}Z\) for some matrix Z and, therefore, \(B_{1}D_{21}^{T\bot}D_{21}^{T\bot T}B_{1}^{T}=B_{1}B_{1}^{T}\). Everything follows in a similar way for the first inequality, choosing .
- 2.
\(X\in{ \mathbb{S}^{n} } \) is a stabilizing solution of the ARE A T X+XA+XRX+Q=0 if it satisfies the equation and A+RX is stable.
- 3.
The asterisks indicate elements whose values are easily inferred by symmetry.
- 4.
T.J. Sargent was awarded the Nobel Memorial Prize in Economic Sciences in 2011 together with C.A. Sims “for their empirical research on cause and effect in the macroeconomy.”
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Tempo, R., Calafiore, G., Dabbene, F. (2013). Linear Robust Control Design. In: Randomized Algorithms for Analysis and Control of Uncertain Systems. Communications and Control Engineering. Springer, London. https://doi.org/10.1007/978-1-4471-4610-0_4
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