More engineers are turning to reinforcement learning to incorporate adaptive and self-tuning control into industrial systems. It aims to strike a balance between traditional ...

Abstract: MPC has gained popularity for its ability to satisfy constraints and guarantee robustness for certain classes of systems. However, for systems whose dynamics are characterized by a high ...

AI optimizes injection molding beyond human understanding, creating new challenges for process control and failure recovery.

After go-live health systems must monitor AI tools for clinical outcomes, model drift, bias, and patient safety to ensure sustained impact.

Abstract: This article introduces a learning-based model predictive control (MPC) framework that leverages Gaussian mixture models (GMMs) to address dynamic system uncertainties effectively. To ...

The evolution of safety-critical autonomous systems, including agile drones and surgical robots, has fundamentally increased the demands for control design.

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