Zobrazeno 1 - 10
of 57
pro vyhledávání: '"Poonawala, Hasan"'
Autor:
Samanipour, Pouya, Poonawala, Hasan A.
This paper introduces an algorithm for approximating the invariant set of closed-loop controlled dynamical systems identified using ReLU neural networks or piecewise affine PWA functions, particularly addressing the challenge of providing safety guar
Externí odkaz:
http://arxiv.org/abs/2402.04243
Autor:
Samanipour, Pouya, Poonawala, Hasan A.
This paper presents an automated algorithm to analyze the stability of piecewise affine (PWA) dynamical systems due to their broad applications. We parametrize the Lyapunov function as a PWA function, with polytopic regions defined by the PWA dynamic
Externí odkaz:
http://arxiv.org/abs/2307.03868
This paper develops a provably stable sensor-driven controller for path-following applications of robots with unicycle kinematics, one specific class of which is the wheeled mobile robot (WMR). The sensor measurement is converted to a scalar value (t
Externí odkaz:
http://arxiv.org/abs/2303.12182
Autor:
Badings, Thom, Romao, Licio, Abate, Alessandro, Parker, David, Poonawala, Hasan A., Stoelinga, Marielle, Jansen, Nils
Publikováno v:
Journal of Artificial Intelligence Research (JAIR) 76 (2023) 341-391
Controllers for dynamical systems that operate in safety-critical settings must account for stochastic disturbances. Such disturbances are often modeled as process noise in a dynamical system, and common assumptions are that the underlying distributi
Externí odkaz:
http://arxiv.org/abs/2301.01526
Autor:
Badings, Thom S., Abate, Alessandro, Jansen, Nils, Parker, David, Poonawala, Hasan A., Stoelinga, Marielle
Publikováno v:
AAAI 2022 (distinguished paper)
Controllers for autonomous systems that operate in safety-critical settings must account for stochastic disturbances. Such disturbances are often modelled as process noise, and common assumptions are that the underlying distributions are known and/or
Externí odkaz:
http://arxiv.org/abs/2110.12662
We study feedback controller synthesis for reach-avoid control of discrete-time, linear time-invariant (LTI) systems with Gaussian process and measurement noise. The problem is to compute a controller such that, with at least some required probabilit
Externí odkaz:
http://arxiv.org/abs/2103.02398
Air traffic control is an example of a highly challenging operational problem that is readily amenable to human expertise augmentation via decision support technologies. In this paper, we propose a new intelligent decision making framework that lever
Externí odkaz:
http://arxiv.org/abs/2004.01387
Increasing urban concentration raises operational challenges that can benefit from integrated monitoring and decision support. Such complex systems need to leverage the full stack of analytical methods, from state estimation using multi-sensor fusion
Externí odkaz:
http://arxiv.org/abs/1906.03040
One approach for feedback control using high dimensional and rich sensor measurements is to classify the measurement into one out of a finite set of situations, each situation corresponding to a (known) control action. This approach computes a contro
Externí odkaz:
http://arxiv.org/abs/1903.03688
The preponderance of connected devices provides unprecedented opportunities for fine-grained monitoring of the public infrastructure. However while classical models expect high quality application-specific data streams, the promise of the Internet of
Externí odkaz:
http://arxiv.org/abs/1903.01045