Identification of feedback nonlinear systems with time delay based on chaotic decreasing weight sparrow search algorithm

This paper considers the identification of feedback nonlinear systems with unknown time delay (FNTD) by the chaotic decreasing weight sparrow search algorithm (CWSSA). The CWSSA algorithm uses the improved circle chaos to map the sparrow population, which avoids the problems of clustering and low coverage in the solution space of the initial solution. Thus, the global search ability and convergence speed of the algorithm are improved. By introducing a linear decreasing weight, the risk of the sparrow search algorithm being prone to premature maturity is reduced, and the oscillation phenomenon that is easy to occur near the global optimal solution in the later stage of the algorithm is avoided. Using the search capability of CWSSA and the iterative identification technology, all parameters and the unknown delay of the FNTD system are estimated simultaneously. Finally, the identification results of CWSSA, SSA and PSO are compared through a numerical example. The results show that CWSSA is superior to SSA and PSO in terms of convergence speed and estimation accuracy. The effectiveness of the CWSSA is also verified by the identification of the electro-hydraulic servo position system.