I develop novel engineering methods and advanced mathematical tools for investigating large-scale complex networked systems and ensemble systems. Applications include autonomous and self-driving vehicles, unmanned aircrafts, sensor-actuator networks, social networks, and energy networks. I address questions about designing control laws that organize the network systems for achieving global objectives, questions about controlling and stabilizing network systems under the constraint that agents can only access local informations, questions about improving/fixing the robustness issues under perturbations and/or malicious attacks, and questions about optimal allocation of resources—such as power supply, sensor bandwidth, computational capacity—for maximizing performance measures and/or minimizing costs.
geometric control theory, stochastic control theory, optimization, decision theory, networked control, distributed control, ensemble control and estimation
ECEN 3810 - Introduction to Probability Theory
Covers the fundamentals of probability theory, and treats the random variables and random processes of greatest importance in electrical engineering. Provides a foundation for study of communication theory, control theory, reliability theory, and optics. Credit not granted for this course and MATH 4510 or APPM 3570.
ECEN 5008 - Special Topics
Examines a special topic in Electrical, Computer and Energy Engineering. May be repeated up to 9 total credits.
ECEN 5448 - Advanced Linear Systems
Fall 2018 / Fall 2019
Offers a state space approach to analysis and synthesis of linear systems, state transition matrix, controllability and observability, system transformation, minimal realization, and analysis and synthesis of multi-input and multi-output systems. Recommended prerequisites: ECEN 3300 and ECEN 4138.