Summers, Tyler H.
Browse by
Tyler Summers is an Assistant Professor in the Department of Electrical and Computer Engineering. He also serves as the Principal Investigator of the Control Optimization and Networks Lab. In 2017 he was awarded a $350,000 grant from the U.S. Army's Young Investigator Program to study the best ways to connect sensors and actuators into networks. His research interests include:
- Control and optimization
- Power and energy networks
- Distributed robotics
Works in Treasures @ UT Dallas are made available exclusively for educational purposes such as research or instruction. Literary rights, including copyright for published works held by the creator(s) or their heirs, or other third parties may apply. All rights are reserved unless otherwise indicated by the copyright owner(s).
Recent Submissions
-
Algorithms for Joint Sensor and Control Nodes Selection in Dynamic Networks
(Elsevier Ltd, 2019-05-17)The problem of placing or selecting sensors and control nodes plays a pivotal role in the operation of dynamic networks. This paper proposes optimal algorithms and heuristics to solve the Simultaneous Sensor and Actuator ... -
Performance Bounds for Optimal Feedback Control in Networks
Many important complex networks, including critical infrastructure and emerging industrial automation systems, are becoming increasingly intricate webs of interacting feedback control loops. A fundamental concern is to ... -
Simultaneous Sensor and Actuator Selection/Placement through Output Feedback Control
In most dynamic networks, it is impractical to measure all of the system states; instead, only a subset of the states are measured through sensors. Consequently, and unlike full state feedback controllers, output feedback ... -
Stochastic Optimal Power Flow Based on Data-Driven Distributionally Robust Optimization
We propose a data-driven method to solve a stochastic optimal power flow (OPF) problem based on limited information about forecast error distributions. The objective is to determine power schedules for controllable devices ... -
Concurrent Goal Assignment and Collision-Free Trajectory Generation for Multiple Aerial Robots
We develop computationally tractable methods for concurrent goal assignment and planning of collision-free trajectories for multiple aerial robot systems. Our method first assigns robots to goals to minimize total ...
RSS 1.0