Research Paper on Subspace Identification with Accompanying Code Implementation

This literature discusses various subspace identification methods and techniques, accompanied by corresponding program code implementations that demonstrate practical applications of these algorithms. The paper provides detailed explanations of subspace identification principles and their application scenarios, supplemented with concrete examples to facilitate better understanding. The accompanying code includes implementations of key algorithms such as N4SID (Numerical algorithms for Subspace State Space System IDentification) and MOESP (Multivariable Output Error State Space), offering hands-on experience with matrix operations, singular value decomposition, and state-space model estimation. Additionally, the literature outlines current research hotspots in subspace identification and future development directions, providing valuable references for researchers. The code examples cover essential functions like data preprocessing, Hankel matrix construction, and model validation procedures. Overall, this resource benefits both beginners seeking to understand fundamental concepts and professionals looking for advanced implementation techniques in subspace identification.