An On-line Identification Method for Control System Based on Improved BP Neural Network Algorithm

The identification methods based on dynamic performance testing are discussed focusing on the features of control systems. In order to realize the online identification for the control system in a computer virtual instrument, a dynamic testing and identification system is designed, using Delphi language for several identification modules. The hardware platform of dynamic testing and system identification with the virtual instrument being used as its core component is built. In the nonlinear aspect, this paper studies the identification algorithm based on Back Propagation (BP) Neural Network algorithm, and proposes an identification algorithm named MBP Neural Network and a Wavelet Neural Network algorithm to reduce the sensitivity of the network. Finally, the real- time wavelet algorithm is simulated to verify the above conclusion. The MBP Neural Network algorithm and the Wavelet Neural Network algorithm are simulated on the three-axis platform of the partial simulating system for an anti-aircraft weapon.