49 citations · 163 across the 51 of their papers we have counts for
11 papers · 1 filter
Identification and Adaptive Control of Markov Jump Systems: Sample Complexity and Regret Bounds
Yahya Sattar, Zhe Du, Davoud Ataee Tarzanagh +3
Learning how to effectively control unknown dynamical systems is crucial for intelligent autonomous systems. This task becomes a significant challenge when the underlying dynamics…
Automaton-based Implicit Controlled Invariant Set Computation for Discrete-Time Linear Systems
Zexiang Liu, Tzanis Anevlavis, Necmiye Ozay +1
In this paper, we derive closed-form expressions for implicit controlled invariant sets for discrete-time controllable linear systems with measurable disturbances. In particular, a…
Optimal Control for Linear Networked Control Systems with Information Transmission Constraints
Antoine Aspeel, Kwesi Rutledge, Raphaël M. Jungers +2
This paper addresses the problem of robust control of a linear discrete-time system subject to bounded disturbances and to measurement and control budget constraints. Using Q-param…
Synthesis-guided Adversarial Scenario Generation for Gray-box Feedback Control Systems with Sensing Imperfections
Liren Yang, Necmiye Ozay
In this paper, we study feedback dynamical systems with memoryless controllers under imperfect information. We develop an algorithm that searches for "adversarial scenarios", which…
Controlled invariant sets: implicit closed-form representations and applications
Tzanis Anevlavis, Zexiang Liu, Necmiye Ozay +1
We revisit the problem of computing (robust) controlled invariant sets for discrete-time linear systems. Departing from previous approaches, we consider implicit, rather than expli…
Scalable Zonotopic Under-approximation of Backward Reachable Sets for Uncertain Linear Systems
Liren Yang, Necmiye Ozay
Zonotopes are widely used for over-approximating forward reachable sets of uncertain linear systems for verification purposes. In this paper, we use zonotopes to achieve more scala…
Certainty Equivalent Quadratic Control for Markov Jump Systems
Zhe Du, Yahya Sattar, Davoud Ataee Tarzanagh +3
Real-world control applications often involve complex dynamics subject to abrupt changes or variations. Markov jump linear systems (MJS) provide a rich framework for modeling such…
Model Error Propagation via Learned Contraction Metrics for Safe Feedback Motion Planning of Unknown Systems
Glen Chou, Necmiye Ozay, Dmitry Berenson
We present a method for contraction-based feedback motion planning of locally incrementally exponentially stabilizable systems with unknown dynamics that provides probabilistic saf…
Towards Better Adaptive Systems by Combining MAPE, Control Theory, and Machine Learning
Danny Weyns, Bradley Schmerl, Masako Kishida +5
Two established approaches to engineer adaptive systems are architecture-based adaptation that uses a Monitor-Analysis-Planning-Executing (MAPE) loop that reasons over architectura…
A General Language-Based Framework for Specifying and Verifying Notions of Opacity
Andrew Wintenberg, Matthew Blischke, Stéphane Lafortune +1
Opacity is an information flow property that captures the notion of plausible deniability in dynamic systems, that is whether an intruder can deduce that "secret" behavior has occu…
On the Value of Preview Information For Safety Control
Zexiang Liu, Necmiye Ozay
Incorporating predictions of external inputs, which can otherwise be treated as disturbances, has been widely studied in control and computer science communities. These predictions…