Applied Research. Subspace Methods In System Identification Of Hot Air Reflow Machine

This thesis focuses on the applications of subspace identification methods to the complex structure system (hot air reflow machine), based on the basic theory of subspace-based state-space system identification.The basic theory of subspace identification algorithms is summarized systematically, including the geometry foundation and space projection theory of subspace identification, the representation of system state-space, the composition of subspace data matrix, the parameter identification theory and algorithm of subspace for deterministic system, random system, and united system.Regarding to this complex system of hot air reflow machine, firstly, the identification experiments are designed and carried out; secondly, the experimental data are preprocessed, including removing the abnormal values and the noise and smoothing the data.At the basis of measured data, the system parameters of hot air reflow machine are identified by means of subspace parameter identification method. The detailed parameters of system matrix are provided which is gained from identification. The implementation procedure is illustrated, including input-output Hankel matrix, line space projection algorithm, and deterministic system matrix algorithm.Finally, the validity of model is tested by the measured data and the satisfied results are obtained. Which show that the subspace methods have the advantages of simple operation and good numerical stability, and prove that it is an excellent method for the identification of high order and multivariable complicated system.