双马达模糊神经网络速度同步控制实现方法研究

摘要

针对内嵌式溢油回收机扫油臂与卷筒双马达电液驱动速度同步控制问题,对扫油臂和卷筒驱动系统的组成、工作原理和控制要求进行了阐述;基于"等同控制"策略,引入模糊神经网络控制理论,建立了双马达模糊神经网络控制器;运用Matlab软件对模糊神经网络控制系统与PID控制系统进行了仿真,获得了阶跃响应对比曲线和线速度同步误差对比曲线,探讨了速度同步控制系统的稳定性,分析了线速度同步误差特点与形成原因.研究结果表明:模糊神经网络控制系统几乎无超调、调节时间为5.2 s,PID控制系统超调量为23%、调节时间为8 s,速度达到稳定时,模糊神经网络控制系统线速度差为7 mm/s,PID控制系统线速度差为16 mm/s;与PID控制相比,模糊神经网络控制具有更好的动态响应特性和稳态特性,同步误差更小、同步精度更高.%Aiming at the problem of the sweep arm of the oil for the embedded type oil spill recovery machine and fence reel dual-motor elec-tro-hydraulic driving speed synchronous control, the constitution, working principle and control requirement of the drive system consisting of the sweep arm of the oil and fence reel were expounded. The dual-motor fuzzy neural network controller was established basing on equivalent control strategy and introducing the fuzzy neural network control theory. The simulation of the fuzzy neural network control system and the PID control system was carried out and the contrast curve of step response and linear speed synchronization error was also obtained using the Mat-lab software. The stability of the speed synchronous control system was discussed and the characteristics of linear speed synchronization error and its causes were also analyzed. The results indicate that the fuzzy neural network control system has no overshoot almost and the adjust-ment time is 5. 2 s, the PID control system overshoot is 23% and the adjustment time is 8 s. When the speed achieves stability the linear ve-locity difference of the fuzzy neural network control system is 7 mm/s and that of the PID control system is 16 mm/s. Therefore the dynamic response and steady-state characteristics of the fuzzy neural network control are better compared to the PID control. Besides, the synchroniza-tion error and the synchronization precision of the fuzzy neural network control is smaller and higher compared to the PID control.