Seminar Details
2021-04-13 (14h) : Welcome Seminar for new postdocs (#2)
At MS Teams
Organized by Mathematical Engineering
Section 1: Event-Triggered Tracking Control of Networked Control Systems
Speaker :
Wei Ren
Abstract :
In this talk, I will show how to deal with the tracking control problem of networked control systems under both multiple networks and event-triggered mechanisms. Multiple networks are to connect the plant and reference system with decentralized controllers to guarantee their information transmission, whereas event-triggered mechanisms are to reduce the information transmission via multiple networks. All networks are independent and asynchronous and have local event-triggered mechanisms, which are based on local measurements and determine whether the local measurements need to be transmitted. I will implement an emulation-based approach to develop a novel hybrid model for tracking control of networked control systems. Then, sufficient conditions are derived and decentralized event-triggered mechanisms are designed to ensure the tracking performance.
This is a joint work with Dimos V. Dimarogonas (KTH) and Raphael Jungers (UCLouvain).
Section 2: Uniform Signal Recovery from Non-Linear Observations
Speaker :
Stollenwerk, Alexander
Abstract :
In this talk, I will consider the problem of estimating high-dimensional signal vectors from few non-linear measurements.
The focus will be on uniform recovery guarantees, that is, results which show that recovery succeeds for an entire class of signal vectors using a fixed
measurement ensemble. In the linear case, classical compressed sensing theory shows that efficient recovery algorithms exist, which are able to robustly estimate signals from very few measurements. The standing assumption in these type of results is that the signal vectors exhibit some form of low-complexity (e.g. sparsity), which the algorithm may exploit. In contrast to the well-understood linear case and despite significant results in various special cases, a general understanding of uniform recovery from non-linear observations is still missing. Taking a step in that direction, I will present a unified approach to this problem under the assumption of i.i.d. sub-Gaussian measurement vectors. This is joint work with Martin Genzel from Utrecht University.