Reza Vafaee PhD Proposal Review

Announcing:
PhD Proposal Review

Name:
Reza Vafaee

Title:
Efficient Algorithms for Sparse Sensor Scheduling in Large-Scale Dynamical Systems with Performance Guarantees

Date:
4/1/2024

Time:
10:30:00 AM

Location: Zoom

Committee Members:
Prof. Milad Siami (Advisor)
Prof. Eduardo Sontag
Prof. Laurent Lessard
Prof. Alex Olshevsky (Boston University)

Abstract:
This research proposal introduces innovative frameworks for sparse sensor scheduling in large-scale dynamical networks. The first framework addresses sensor scheduling in discrete-time linear time-invariant dynamical networks, presenting a novel learning-based rounding method to convert weighted sensor schedules into sparse, unweighted schedules while maintaining comparable observability performance. The second framework extends the approach to dynamically select sensors for linear time-varying systems, utilizing an online sparse sensor scheduling framework with randomized algorithms to approximate fully-sensed systems with a constant average number of active sensors at each time step. Finally, a myopic approach within a Kalman filtering framework is adopted in the third framework, addressing non-submodular sensor scheduling in large-scale linear time-varying dynamics. A simple greedy algorithm is employed, providing approximation bounds based on submodularity and curvature concepts. Simulation results validate the theoretical foundations and demonstrate the proposed approach’s superiority over existing methods.