A novel closed loop identification method and its application of multivariable system

Motivated by the fact that many classical identification methods cannot be directly used for closed loop control system for the excitation signal without the strict requirement, a novel identification method is proposed to simultaneously estimate model parameter and the structure. To improve the optimizing efficiency of the particle swarm, the global best particles are further optimized via a nonlinear stochastic search during the certain iteration of PSO and the novel method is denoted NPSO. On the basis, the frequency response estimation is introduced to provide a rough initial for the presented algorithm to improve the validity and accuracy. We simplify the complexity of the closed loop identification via the equivalent input and output. Simulation examples of SISO systems and MIMO systems are given to demonstrate the effectiveness and accuracy of the proposed algorithm.

► We present a novel algorithm NPSO better than PSO and NLJ in terms of accuracy and robustness.
► We introduce a frequency response method to provide the initial parameters for NPSO.
► Simplifying the closed-loop identification complexity via the equivalent input and output.
► Applying the NPSO in the multivariable closed-loop system.