Dynamic Matrix Predictive Control M-File Implementation

The Dynamic Matrix Predictive Control (DMPC) program implemented in M-language is specifically designed for the MATLAB computational environment. This implementation utilizes MATLAB's matrix manipulation capabilities to model dynamic systems that evolve over time, providing an intuitive platform for system prediction and control. The core algorithm employs a predictive model based on step response coefficients arranged in a dynamic matrix format, enabling future system behavior predictions through convolution operations. Key implementation features include: - Matrix-based system representation using step response data - Quadratic programming optimization for control sequence calculation - Rolling horizon implementation with receding window strategy - Constraint handling capabilities for input and output limitations The program structure incorporates modular functions for prediction, optimization, and control law calculation, with clear annotations throughout the code to facilitate parameter adjustments and algorithm modifications. This implementation has demonstrated effectiveness across various engineering domains including robotics trajectory planning, aerospace system control, and industrial process automation. The solution provides engineers and researchers with a robust framework for designing predictive controllers that can handle system constraints while optimizing performance criteria through quadratic cost functions.