DMC Algorithm for Model Predictive Control with Simulation Examples
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In this article, we explore Model Predictive Control (MPC) with a focus on the Dynamic Matrix Control (DMC) algorithm. MPC is a widely adopted engineering control technique that utilizes system modeling to predict future behavior and formulate control strategies based on these predictions. The DMC algorithm, a prominent MPC approach, optimizes control signals to minimize prediction errors while continuously updating the predictive model during runtime. To demonstrate practical implementation, we provide simulation examples with code snippets illustrating key components such as step response matrix construction, optimization solver usage (e.g., quadratic programming with MATLAB's quadprog function), and real-time model adaptation techniques. These examples will help readers understand the algorithm's workflow, including how to handle constraints and adjust horizon parameters for effective control system design.
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