Predictive Functional Control MATLAB Implementation with Signal Analysis

This MATLAB implementation of predictive functional control allows comprehensive analysis of system responses under various input signal types. The program includes three main test scenarios: step inputs for stability testing, sinusoidal inputs for frequency response analysis, and random inputs for robustness evaluation. Key implementation features include: - Prediction horizon configuration using the 'N' parameter - Control weighting adjustment through the 'lambda' variable - Reference trajectory generation for smooth setpoint tracking - Real-time performance monitoring with error calculation functions The code structure incorporates: 1. Signal generation module with customizable amplitude and frequency parameters 2. Plant model initialization using transfer function or state-space representations 3. Predictive controller core algorithm with constraint handling capabilities 4. Data logging and visualization functions for response comparison Through systematic testing with different input patterns, users can evaluate controller performance metrics including settling time, overshoot, and disturbance rejection capabilities. The implementation provides a practical framework for understanding predictive control applications in various dynamic scenarios.