Data-driven control of nonlinear dynamic systems has emerged as a transformative paradigm in control engineering, leveraging empirical data rather than detailed first-principles models. By embedding ...

In the modelic control paradigm, the first step is to establish a dynamic model through system identification. This model offers a continuous but inaccurate description of state transition information ...

AI can be added to legacy motion control systems in three phases with minimal disruption: data collection via edge gateways, non-interfering anomaly detection and supervisory control integration.

How event-driven design can overcome the challenges of coordinating multiple AI agents to create scalable and efficient reasoning systems. While large language models are useful for chatbots, Q&A ...