no code implementations • 12 Dec 2022 • Amir-Salar Esteki, Solmaz S. Kia
Our approach consists of a two-stage dynamics, where the first one samples the first and second derivatives of the local costs periodically to construct an estimate of the descent direction towards the optimal trajectory, and the second one uses this estimate and a consensus term to drive local states towards the time-varying solution while reaching consensus.
no code implementations • 11 Dec 2021 • Navid Rezazadeh, Maxwell Kolarich, Solmaz S. Kia, Negar Mehr
We then learn both the control policy and the contraction metric such that the distance between the trajectories from the offline data set and our generated auxiliary sample trajectories decreases over time.
no code implementations • 6 Dec 2021 • Jianan Zhu, Solmaz S. Kia
This paper proposes a measurement scheduling for CL that follows the SG approach but reduces the communication and computation cost by using a neural network-based surrogate model as a proxy for the SG algorithm's merit function.
no code implementations • 8 Sep 2020 • Jianan Zhu, Solmaz S. Kia
We also propose a bias compensation method for NLoS UWB measurements.
1 code implementation • 10 Apr 2019 • Navid Rezazadeh, Solmaz S. Kia
This paper considers the problem of privacy preservation against passive internal and external malicious agents in the continuous-time Laplacian average consensus algorithm over strongly connected and weight-balanced digraphs.
Systems and Control