/self_tuning_network_control

Self-tuning Network Control Architecture

Primary LanguageJupyter Notebook

Self-tuning Network Control Architecture - code submission for CDC'22

We compare the control costs and performance from run-time greedy actuator selection and full-state feedback with current state information to a random set of design-time actuators and the corresponding fixed full-state feedback.

Dynamics: 50 node randomly generated well-connected ER network (open-loop unstable with eigenvalue magnitude 1.05)

Python

Use work_env to install a conda environment with all relevant packages for the code

File Organization