Modern control system design is increasingly embracing data-driven methodologies, which bypass the traditional necessity for precise process models by utilising experimental input–output data. This ...

Data-driven control represents a paradigm shift in the design and implementation of controllers for both linear and nonlinear systems. Eschewing traditional reliance on first‐principles models, this ...

There is now broad consensus that data-driven decision-making is essential to success in today’s highly competitive manufacturing environment. Customers’ price-consciousness, combined with demands for ...

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 ...

We have considerable expertise in MPC as a powerful tool for providing optimal control in dynamic environments, ensuring real-time performance and adaptability. Our work includes developing predictive ...

The future of automation and artificial intelligence in warfare begins with structured, interoperable data. As a staff officer, the greatest obstacle I’ve observed to achieving truly data-driven ...