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- posterMay 2024
Spatiotemporal Tubes for Reach-Avoid-Stay Specifications✱
HSCC '24: Proceedings of the 27th ACM International Conference on Hybrid Systems: Computation and ControlArticle No.: 28, Pages 1–2https://doi.org/10.1145/3641513.3652533This study focuses on synthesizing controllers for unknown dynamics control-affine nonlinear systems, aiming to satisfy reach-avoid-stay (RAS) specifications within prescribed-time. The main objective is to derive a closed-form control law, ...
- research-articleJuly 2024
Poster Abstract: Signal Temporal Logic Compliant Motion Planning using Reinforcement Learning
2024 ACM/IEEE 15th International Conference on Cyber-Physical Systems (ICCPS)Pages 283–284https://doi.org/10.1109/ICCPS61052.2024.00037This work proposes a novel approach for model-free motion planning in autonomous robots, with a specific emphasis on handling signal temporal logic (STL) tasks. The approach is structured into two main phases: first, we learn spatio-temporal motion ...
- research-articleDecember 2021
Distributed Consensus of Stochastic Multi-agent Systems with Prescribed Performance Constraints
2021 60th IEEE Conference on Decision and Control (CDC)Pages 1911–1916https://doi.org/10.1109/CDC45484.2021.9683249This paper focuses on the problem of distributed consensus control of multi-agent systems while considering two main practical concerns (i) stochastic noise in the agent dynamics and (ii) predefined performance constraints over evolutions of multi-agent ...
- posterMay 2021
Formal safety verification of unknown continuous-time systems: a data-driven approach
HSCC '21: Proceedings of the 24th International Conference on Hybrid Systems: Computation and ControlArticle No.: 29, Pages 1–2https://doi.org/10.1145/3447928.3456661This work studies formal verification of continuous-time continuous-space systems with unknown dynamics against safety specifications. The proposed framework is based on a data-driven construction of barrier certificates using which the safety of ...
- research-articleDecember 2020
Control Barrier Functions for Unknown Nonlinear Systems using Gaussian Processes<sup>*</sup>
2020 59th IEEE Conference on Decision and Control (CDC)Pages 3699–3704https://doi.org/10.1109/CDC42340.2020.9303847This paper focuses on the controller synthesis for unknown, nonlinear systems while ensuring safety constraints. Our approach consists of two steps, a learning step that uses Gaussian processes and a controller synthesis step that is based on control ...
- research-articleAugust 2020
Software Fault Tolerance for Cyber-Physical Systems via Full System Restart
ACM Transactions on Cyber-Physical Systems (TCPS), Volume 4, Issue 4Article No.: 47, Pages 1–20https://doi.org/10.1145/3407183The article addresses the issue of reliability of complex embedded control systems in the safety-critical environment. In this article, we propose a novel approach to design controller that (i) guarantees the safety of nonlinear physical systems, (ii) ...
- demonstrationApril 2020
dtControl: decision tree learning algorithms for controller representation
HSCC '20: Proceedings of the 23rd International Conference on Hybrid Systems: Computation and ControlArticle No.: 30, Pages 1–2https://doi.org/10.1145/3365365.3383468Decision tree learning is a popular classification technique most commonly used in machine learning applications. Recent work has shown that decision trees can be used to represent provably-correct controllers concisely. Compared to representations ...
dtControl: decision tree learning algorithms for controller representation
HSCC '20: Proceedings of the 23rd International Conference on Hybrid Systems: Computation and ControlArticle No.: 17, Pages 1–7https://doi.org/10.1145/3365365.3382220Decision tree learning is a popular classification technique most commonly used in machine learning applications. Recent work has shown that decision trees can be used to represent provably-correct controllers concisely. Compared to representations ...
- research-articleApril 2020
Compositional construction of control barrier functions for interconnected control systems
HSCC '20: Proceedings of the 23rd International Conference on Hybrid Systems: Computation and ControlArticle No.: 22, Pages 1–11https://doi.org/10.1145/3365365.3382196In this paper, we provide a compositional framework for synthesizing hybrid controllers for interconnected discrete-time control systems enforcing specifications expressed by co-Büchi automata. In particular, we first decompose the given specification ...
- rapid-communicationJanuary 2020
Symbolic models for retarded jump–diffusion systems
Automatica (Journal of IFAC) (AJIF), Volume 111, Issue Chttps://doi.org/10.1016/j.automatica.2019.108666AbstractIn this paper, we provide for the first time an automated, correct-by-construction, controller synthesis scheme for a class of infinite dimensional stochastic systems, namely, retarded jump–diffusion systems. First, we construct finite ...
- research-articleDecember 2016
Backstepping design for incremental stability of stochastic Hamiltonian systems
2016 IEEE 55th Conference on Decision and Control (CDC)Pages 5367–5372https://doi.org/10.1109/CDC.2016.7799092Incremental stability is a property that ensures the uniform asymptotic stability of each trajectory rather than a fixed equilibrium point or trajectory. This makes it a stronger stability notion for dynamical systems. Here, we introduce a notion of ...
- research-articleSeptember 2016
On incremental stability of time-delayed stochastic control systems
2016 54th Annual Allerton Conference on Communication, Control, and Computing (Allerton)Pages 577–581https://doi.org/10.1109/ALLERTON.2016.7852283Incremental stability is a strong property of dynamical systems ensuring the uniform asymptotic stability of each trajectory rather than a fixed equilibrium point or fixed trajectory. Here, we introduce a notion of incremental stability for time-delayed ...
- research-articleMarch 2016
Prediction of ground motion parameters using randomized ANFIS (RANFIS)
Applied Soft Computing (APSC), Volume 40, Issue CPages 624–634https://doi.org/10.1016/j.asoc.2015.12.013Prediction of ground motion parameters using hybrid soft computing technique.The neuro-fuzzy inference system uses Sugeno type fuzzy rules with a randomized fuzzy layer and a linear neural network output layer.Faster prediction of peak ground ...