dMC Dynamic Matrix Control for Single-Variable Systems

The dMC (dynamic matrix control) algorithm provides robust single-variable control capabilities and can be readily adapted through parameter modifications to meet specific program requirements. This predictive control method utilizes a dynamic matrix-based mathematical model to regulate process behavior through future output predictions. Implementation typically involves constructing a step-response matrix where each column represents the system's temporal response, enabling multi-step prediction calculations. Key functions include reference trajectory tracking, constraint handling, and rolling optimization computations. The control law can be programmed using matrix operations like pseudoinverse calculations for unconstrained cases or quadratic programming for constrained optimization. dMC achieves enhanced accuracy in single-variable regulation through its predictive nature, leading to improved process performance and operational efficiency. The algorithm's flexibility allows adaptation to various industrial processes through adjustments in prediction horizon, control horizon, and weighting matrices. This versatility makes dMC particularly valuable for control engineers and researchers working on process optimization, system identification, and advanced control strategy development. Code implementation typically involves initializing the dynamic matrix from step-response data, implementing a receding horizon controller with real-time feedback correction, and designing constraint handling mechanisms for practical applications.