1 citations · 1 across the 5 of their papers we have counts for
5 papers
On the Design of Rational Polynomial State Feedback Controllers
Matthew Newton, Zuxun Xiong, Han Wang +1
One of the desirable objectives in feedback control design is to formulate and solve the design problem as an optimisation problem that is convex, so that an optimal solution can b…
Scalable Forward Reachability Analysis of Multi-Agent Systems with Neural Network Controllers
Oliver Gates, Matthew Newton, Konstantinos Gatsis
Neural networks (NNs) have been shown to learn complex control laws successfully, often with performance advantages or decreased computational cost compared to alternative methods.…
Rational Neural Network Controllers
Matthew Newton, Antonis Papachristodoulou
Neural networks have shown great success in many machine learning related tasks, due to their ability to act as general function approximators. Recent work has demonstrated the eff…
Stability of Non-linear Neural Feedback Loops using Sum of Squares
Matthew Newton, Antonis Papachristodoulou
Neural network controllers have the potential to improve the performance of feedback systems compared to traditional controllers, due to their ability to act as general function ap…
Sparse Polynomial Optimisation for Neural Network Verification
Matthew Newton, Antonis Papachristodoulou
The prevalence of neural networks in society is expanding at an increasing rate. It is becoming clear that providing robust guarantees on systems that use neural networks is very i…