The Networked Controls and Intelligent Diagnostics (NCID) Laboratory focuses on the design and development of controllers and fault diagnosis algorithms that target the optimal and robust performance of industrial and dynamic systems. Decentralized control techniques are specifically designed for large-scale dynamic systems in which computation resources are distributed and communication bandwidth is limited. Moreover, hybrid diagnostics algorithms are designed based on a combination of classical and artificial intelligence-based fault diagnosis techniques that aim at the resilient and reconfigurable performance of dynamic systems in the presence of faults and failures. These control and fault diagnosis algorithms are developed for microgrids and renewable energy systems, and will be applied in the future to other applications, including autonomous vehicles, robotics and aerospace systems.
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