4 citations · 7 across the 9 of their papers we have counts for
8 papers · 1 filter
How to Learn a Model Checker
Dung Phan, Radu Grosu, Nicola Paoletti +2
We show how machine-learning techniques, particularly neural networks, offer a very effective and highly efficient solution to the approximate model-checking problem for continuous…
Declarative vs Rule-based Control for Flocking Dynamics
Usama Mehmood, Nicola Paoletti, Dung Phan +6
The popularity of rule-based flocking models, such as Reynolds' classic flocking model, raises the question of whether more declarative flocking models are possible. This question…
Automated Synthesis of Safe and Robust PID Controllers for Stochastic Hybrid Systems
Fedor Shmarov, Nicola Paoletti, Ezio Bartocci +3
We present a new method for the automated synthesis of safe and robust Proportional-Integral-Derivative (PID) controllers for stochastic hybrid systems. Despite their widespread us…
Data-Driven Robust Control for Type 1 Diabetes Under Meal and Exercise Uncertainties
Nicola Paoletti, Kin Sum Liu, Scott A. Smolka +1
We present a fully closed-loop design for an artificial pancreas (AP) which regulates the delivery of insulin for the control of Type I diabetes. Our AP controller operates in a fu…
Lagrangian Reachabililty
Jacek Cyranka, Md. Ariful Islam, Greg Byrne +3
We introduce LRT, a new Lagrangian-based ReachTube computation algorithm that conservatively approximates the set of reachable states of a nonlinear dynamical system. LRT makes use…
A Component-Based Simplex Architecture for High-Assurance Cyber-Physical Systems
Dung Phan, Junxing Yang, Matthew Clark +4
We present Component-Based Simplex Architecture (CBSA), a new framework for assuring the runtime safety of component-based cyber-physical systems (CPSs). CBSA integrates Assume-Gua…