Offline System Identification Program Using MATLAB System Identification Toolbox

This program implements an offline system identification solution using MATLAB's System Identification Toolbox. The core functionality utilizes identification algorithms to achieve precise modeling and predictive analysis for target systems. It supports identification of various system types including both linear and nonlinear systems, with enhanced accuracy through configurable signal models such as ARX, ARMAX, OE, and BJ models. The implementation features a GUI-based interface for intuitive parameter configuration and result visualization. Key functions include data preprocessing, model structure selection, parameter estimation via prediction error methods, and model validation through residual analysis. Through this program, users can effectively analyze system dynamics, predict future behaviors, and optimize control strategies to improve system performance. The code architecture modularizes data input, algorithm processing, and result output stages for maintainability and extensibility.