Parameter Identification of Electro-Hydraulic Servo Systems Using Improved Butterfly Optimization

The electro-hydraulic servo system is nonlinear, time-varying, and parameter-coupled. Traditional identification methods suffer from slow convergence, low accuracy, and the tendency to get trapped in local optima. To improve the effectiveness of parameter identification for the electro-hydraulic servo system, this paper proposes an improved butterfly optimization algorithm （IBOA） and uses it to identify the system parameters. Firstly, a state-space mathematical model of the electro-hydraulic servo system is established, and the parameters to be identified and the main requirements are determined. Secondly, in view of the shortcomings of the standard butterfly optimization algorithm （BOA）, improvements are made in four aspects: chaotic initialization and adaptive perception coefficients. Then, the objective function is established, the identification process and software/hardware schemes are designed. Finally, the methods of simulation and experiment verification are used to compare with BOA, PSO, and GA. The results show that IBOA has high identification accuracy, fast convergence, and stability, and can provide reliable support for system modeling and control.