How does dynamic-optimizing control reduce time or cost?

Dynamic-optimizing control reduces time or cost by ensuring that a system operates to satisfy a specific performance criterion. In this framework, the control system is designed to move the process from its original state to a new, desired position in the minimum possible time or at the minimum total cost.1

By continuously identifying the current state of the system and comparing its performance against defined optimums, the controller can initiate modifications to drive the process toward that ideal state. In industrial applications, such as chemical processing or manufacturing, this often involves using digital computers to execute optimizing strategies. These systems integrate data from multiple control loops to perform complex calculations that exceed human capability, thereby increasing productivity and efficiency while minimizing waste or unnecessary expenditure.12