Koopman operator theory: fundamentals, control and applications

Koopman operator theory has revolutionized the way nonlinear dynamical systems are approached, offering a global linear representation through observation functions. This approach allows applying classical control tools to complex problems such as robotics, industrial processes, or energy systems. In the business domain, its practical implementation requires robust and customized technological solutions. For example, at Q2BSTUDIO we develop AI for businesses that integrate models based on the Koopman operator to optimize processes and predict behaviors. Our team combines this theory with machine learning techniques and AWS and Azure cloud services to scale these models to production environments. Additionally, we offer tailored applications that allow organizations to incorporate nonlinear predictive control without rewriting their entire infrastructure. Cybersecurity also plays a key role in protecting training data and the decisions of deployed AI agents. From visualizing results with Power BI to automation through AI agents, each step relies on business intelligence services that transform data into decisions. Koopman theory, far from remaining in the academic realm, thus becomes a practical tool when implemented with custom software and the support of artificial intelligence experts. At Q2BSTUDIO, we accompany our clients through every phase, from conceptualization to the deployment of advanced control systems, ensuring efficiency and precision in increasingly complex environments.