Internal Model Control, Smith Predictor, Feedforward Compensation, and Predictive Algorithm Simulations

This program is designed to simulate advanced control algorithms including Internal Model Control (IMC), Smith Predictor, Feedforward Compensation, and Predictive algorithms. The simulation evaluates algorithm performance under various scenarios through MATLAB/Simulink implementations featuring configurable parameters and comparative analysis modules. Key implementation aspects include: IMC structure design using process model inversion, Smith Predictor's dead-time compensation through parallel model pathways, feedforward disturbance rejection mechanisms, and predictive controllers with rolling optimization horizons. During simulation, users can modify algorithm parameters such as controller gains, filter time constants, and prediction horizons to compare performance metrics like settling time, overshoot, and disturbance rejection capability. Beyond algorithm simulation, the program facilitates deep analysis of working principles and characteristics through result visualization tools, enabling better understanding of stability margins, robustness trade-offs, and practical implementation considerations for real-world control problems.