Guest Editorial Special Issue on State-of-the-Art Applications of Model Predictive Control

Advancements in computing hardware and refinements of numerical solvers for convex optimization problems have prompted a burst of interest in the utilization of model predictive control (MPC) to a myriad of challenging control problems and scenarios. Undoubtedly, the tremendous success enjoyed by model-predictive controllers across a wide variety of industrial and technological settings is ascribable to the potential for optimizing performance while guaranteeing the satisfaction of system constraints via recursive online optimization. This unique capability represents a most appealing feature in contexts where autonomy, safety, reliability, flexibility, and cost-effectiveness are important or essential requirements.