Skip to main content

Research Repository

Advanced Search

Outputs (4)

The Pointillist principle for variation operators and jump functions (2024)
Journal Article
Hughes, K. (in press). The Pointillist principle for variation operators and jump functions. Revista de la Unión Matemática Argentina, https://doi.org/10.33044/revuma.4124

I extend the pointillist principles of Moon and Carrillo-de Guzmán to variational operators and jump functions. 1. The pointillist principle In [11], Moon observed that, for a sequence of sufficiently smooth convolution operators and any q ≥ 1, the w... Read More about The Pointillist principle for variation operators and jump functions.

Operator-valued multiplier theorems for causal translation-invariant operators with applications to control theoretic input-output stability (2024)
Journal Article
Guiver, C., Logemann, H., & Opmeer, M. R. (in press). Operator-valued multiplier theorems for causal translation-invariant operators with applications to control theoretic input-output stability. Mathematics of Control, Signals, and Systems,

We prove an operator-valued Laplace multiplier theorem for causal translation-invariant linear operators which provides a characterization of continuity from~$H^\alpha(\mR,U)$ to~$H^\beta(\mR,U)$ (fractional~$U$-valued Sobolev spaces, $U$ a complex H... Read More about Operator-valued multiplier theorems for causal translation-invariant operators with applications to control theoretic input-output stability.

The energy-balance method for optimal control in renewable energy applications (2024)
Journal Article
Guiver, C., & Opmeer, M. R. (in press). The energy-balance method for optimal control in renewable energy applications. Renewable Energy Focus,

A theoretical method is presented, called the energy-balance method, for maximising the energy extracted from a renewable energy converter in terms of determination of an optimal control. The method applies to control systems specified by linear grap... Read More about The energy-balance method for optimal control in renewable energy applications.

Convex neural network synthesis for robustness in the 1-norm (2024)
Presentation / Conference Contribution
Drummond, R., Guiver, C., & Turner, M. C. (2024, July). Convex neural network synthesis for robustness in the 1-norm. Presented at 6th Annual Learning for Dynamics & Control Conference, Oxford, England

With neural networks being used to control safety-critical systems, they increasingly have to be both accurate (in the sense of matching inputs to outputs) and robust. However, these two properties are often at odds with each other and a trade-off ha... Read More about Convex neural network synthesis for robustness in the 1-norm.