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Found 18 papers, 1 papers with code
Data-driven Interval MDP for Robust Control Synthesis
The abstraction of dynamical systems is a powerful tool that enables the design of feedback controllers using a correct-by-design framework.
Data-Driven Abstractions for Control Systems
At the intersection of dynamical systems, control theory, and formal methods lies the construction of symbolic abstractions: these typically represent simpler, finite-state models whose behaviour mimics the one of an underlying concrete system but are easier to analyse.
Distributionally Robust Strategy Synthesis for Switched Stochastic Systems
The framework we present first learns an abstraction of a switched stochastic system as a robust Markov decision process (robust MDP) by accounting for both the stochasticity of the system and the uncertainty in the noise distribution.
Data-driven Abstractions for Verification of Deterministic Systems
A common technique to verify complex logic specifications for dynamical systems is the construction of symbolic abstractions: simpler, finite-state models whose behaviour mimics the one of the systems of interest.
Robust Event-Driven Interactions in Cooperative Multi-Agent Learning
We present an approach to reduce the communication required between agents in a Multi-Agent learning system by exploiting the inherent robustness of the underlying Markov Decision Process.
Data-driven Abstractions with Probabilistic Guarantees for Linear PETC Systems
We extend the scenario approach to multiclass SVM algorithms in order to construct a PAC map between the concrete, unknown state-space and the inter-sample times.
ETCetera: beyond Event-Triggered Control
We present ETCetera, a Python library developed for the analysis and synthesis of the sampling behaviour of event triggered control (ETC) systems.
Formal Analysis of the Sampling Behaviour of Stochastic Event-Triggered Control
Analyzing Event-Triggered Control's (ETC) sampling behaviour is of paramount importance, as it enables formal assessment of its sampling performance and prediction of its sampling patterns.
Chaos and order in event-triggered control
Then, we present abstraction-based methods to compute limit metrics, such as limit average and limit inferior inter-sample time (IST) of periodic ETC (PETC), with considerations to the robustness of such metrics, as well as measuring the emergence of chaos.
Computing the average inter-sample time of event-triggered control using quantitative automata
Event-triggered control (ETC) is a major recent development in cyber-physical systems due to its capability of reducing resource utilization in networked devices.
Event-Based Communication in Distributed Q-Learning
We present an approach to reduce the communication of information needed on a Distributed Q-Learning system inspired by Event Triggered Control (ETC) techniques.
Self-Triggered Control for Near-Maximal Average Inter-Sample Time
Self-triggered control (STC) is a sample-and-hold control method aimed at reducing communications within networked-control systems; however, existing STC mechanisms often maximize how late the next sample is, and as such they do not provide any sampling optimality in the long-term.
Abstracting the Sampling Behaviour of Stochastic Linear Periodic Event-Triggered Control Systems
Recently, there have been efforts towards understanding the sampling behaviour of event-triggered control (ETC), for obtaining metrics on its sampling performance and predicting its sampling patterns.
Abstracting the Traffic of Nonlinear Event-Triggered Control Systems
To construct an ETC system's abstraction: a) the state space is partitioned into regions, b) for each region an interval is determined, containing all intersampling times of points in the region, and c) the abstraction's transitions are determined through reachability analysis.
Formal synthesis of closed-form sampled-data controllers for nonlinear continuous-time systems under STL specifications
Subsequently, the best candidate is verified using reachability analysis; if the candidate solution does not satisfy the specification, an initial condition violating the specification is extracted as a counterexample.
Region-Based Self-Triggered Control for Perturbed and Uncertain Nonlinear Systems
In this work, we derive a region-based self-triggered control (STC) scheme for nonlinear systems with bounded disturbances and model uncertainties.
Scalable Traffic Models for Scheduling of Linear Periodic Event-Triggered Controllers
It is augmented with early triggering actions that can be used by a scheduler to mitigate communication conflicts.
Formal Synthesis of Analytic Controllers for Sampled-Data Systems via Genetic Programming
This paper presents an automatic formal controller synthesis method for nonlinear sampled-data systems with safety and reachability specifications.
