基于ITCM-MOGWO-PSO的钻机滚筒钢丝绳张力控制分析OA

To address the strong nonlinearity,large disturbances,and slow response inherent in drilling winch drum wire rope tension control systems,this study proposes an ITCM-MOGWO-PSO algorithm that integrates Tent chaotic mapping and a dual-chaotic learning mechanism to optimize PID parameters,thereby achieving high-precision and robust dynamic tension regulation of wire rope.First,a multi-physics field coupled Simulink simulation system was constructed based on the dynamic model of winch wire rope tension.Then,PID parameters were optimized using ITCM-MOGWO-PSO algorithm with the objectives of enhancing tension control accuracy,improving energy consumption smoothness,and reducing tension fluctuation.Simulation results demonstrate that,compared with MOPSO,MOGWO,and MOGWO-PSO,the optimized controller parameters obtained via ITCM-MOGWO-PSO reduce overshoot by 97.7%,91.7%,and 95.9%,shorten the settling time by 23.9%,4.1%,and 7.2%,and decrease steady-state error by 1.18%,0.91%,and 1.09%,respectively.Furthermore,the proposed algorithm achieves faster convergence,yields the lowest average fitness value,and produces a more concentrated solution set distribution,thereby significantly improving the response speed,control accuracy,and robustness of the tension control system,and offers an effective method for intelligent optimization and control of rig hoisting system.