MATLAB Code Implementation for System Identification

When implementing system identification in MATLAB, the following steps should be performed: First, clearly define the implementation objectives and the system to be identified. Second, conduct dynamic analysis and mathematical modeling of the system to ensure accurate characterization of system features. In MATLAB, this typically involves using functions like tf() for transfer function modeling or idss() for state-space representations. Third, based on the modeling results, select appropriate identification methods such as parametric estimation (using arx(), oe(), or pem() functions) or non-parametric approaches (like impulse response analysis with impulse() or frequency domain methods with spa()). Finally, evaluate and analyze the identification results using validation functions like compare() or resid(), and provide detailed explanations of the outcomes. For comprehensive understanding, it's recommended to practice with exercises from "Dynamic Analysis and Mathematical Modeling of Mechanical Systems" (Edited by Wen Xisen) to master the implementation process and technical key points of system identification.