Aiming at the shortcomings of the classical differential evolution(DE)algorithm

such as low population diversity and slow optimization speed

an elite enhanced DE(EEDE)algorithm is proposed.The DE algorithm is improved by introducing random scaling vector and random global variation

and using the idea of pattern search to improve the elite enhancement operator of the algorithm

which improves the global

optimization speed and precision of the improved algorithm.Then

the improved algorithm is used to identify the higher-order model as a first-order time-delay model

and the proportion integration differentiation(PID)parameters of the identified model are optimized and adjusted by the ITAE evaluation index

and the tuning parameters are applied to the original system control to test the model identification and control problems.Finally

the PID tuning of this algorithm is compared with that of Ziegler-Nichols(ZN)method by MATLAB experiment platform

and the experimental results prove that this algorithm is feasible and effective in system model identification and control parameter optimization.