Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Deshpande, Vedang M."'
In this paper, we present novel convex optimization formulations for designing full-state and output-feedback controllers with sparse actuation that achieve user-specified $\mathcal{H}_2$ and $\mathcal{H}_\infty$ performance criteria. For output-feed
Externí odkaz:
http://arxiv.org/abs/2409.09596
The temperature distribution in the battery significantly impacts the short-term and long-term performance of battery systems. Therefore, efficient, safe, and reliable battery system operation requires an accurate estimation of the temperature field.
Externí odkaz:
http://arxiv.org/abs/2105.05976
In this paper the tracking problem of multi-agent systems, in a particular scenario where a segment of agents entering a sensing-denied environment or behaving as non-cooperative targets, is considered. The focus is on determining the optimal sensor
Externí odkaz:
http://arxiv.org/abs/2103.00739
We consider the problem of sensor selection for designing observer and filter for continuous linear time invariant systems such that the sensor precisions are minimized, and the estimation errors are bounded by the prescribed $\mathcal{H}_2/\mathcal{
Externí odkaz:
http://arxiv.org/abs/2103.00750
We present a framework which incorporates three aspects of the estimation problem, namely, sparse sensor configuration, optimal precision, and robustness in the presence of model uncertainty. The problem is formulated in the $\mathcal{H}_{\infty}$ op
Externí odkaz:
http://arxiv.org/abs/2009.01930
In this paper we present a data-driven approach for uncertainty propagation. In particular, we consider stochastic differential equations with parametric uncertainty. Solution of the differential equation is approximated using maximum entropy (maxent
Externí odkaz:
http://arxiv.org/abs/2004.01736
Publikováno v:
2020 IEEE Control System Letters
In this paper, we propose a robust Kalman filtering framework for systems with probabilistic uncertainty in system parameters. We consider two cases, namely discrete time systems, and continuous time systems with discrete measurements. The uncertaint
Externí odkaz:
http://arxiv.org/abs/2003.10926
In this paper, we simultaneously determine the optimal sensor precision and the observer gain, which achieves the specified accuracy in the state estimates. Along with the unknown observer gain, the formulation parameterizes the scaling of the exogen
Externí odkaz:
http://arxiv.org/abs/2003.10887
A unified framework to derive optimized compact schemes for a uniform grid is presented. The optimal scheme coefficients are determined analytically by solving an optimization problem to minimize the spectral error subject to equality constraints tha
Externí odkaz:
http://arxiv.org/abs/1912.07382
In this paper we present a data driven approach for approximating dynamical systems. A dynamics is approximated using basis functions, which are derived from maximization of the information-theoretic entropy, and can be generated directly from the da
Externí odkaz:
http://arxiv.org/abs/1911.03016