【摘要】 针对传统电动叉车液压系统能耗高的问题，为解决泵阀协同系统控制复杂度高与参数整定难度大等关键技术瓶颈，引入线性自抗扰控制器以优化系统动态性能，并结合改进大蔗鼠优化算法实现控制参数的自适应寻优。首先，基于系统原理分析，构建泵阀协同电液伺服控制系统的数学模型；其次，设计控制策略，分别为泵控、阀控子系统配置线性自抗扰控制器，并开发压力指令控制器，实现多子系统的协同调控；再次，将改进大蔗鼠优化算法应用于线性自抗扰控制器的参数整定；最后，搭建AMESim和Simulink联合仿真模型并进行验证。仿真结果表明，所设计的控制策略能有效调节伺服阀的开度和液压泵的输出流量和压力，对比PID控制的泵阀协同控制系统，提高了液压系统的响应速度和控制精度，将位置误差稳定控制在0.003 m以内；与传统阀控系统相比，显著减少节流和溢流损失，节能率达到41.78%。更多还原

【Abstract】 To tackle the high energy consumption and control complexity in traditional electric forklift hydraulic systems, this study proposes a novel control strategy for pump-valve coordinated system. The strategy employs a linear active disturbance rejection controller to enhance dynamic performance and utilizes an improved greater cane rat algorithm for adaptive parameter optimization. Firstly, a mathematical model of the electro-hydraulic servo system is established. Then, the control strategy is designed: linear active disturbance rejection controllers are applied to both the pump and valve subsystems, and a pressure command controller is developed for coordination. Subsequently, the improved greater cane rat algorithm tunes the controller parameters. Finally, verification is conducted through a co-simulation model built in AMESim and MATLAB/Simulink. Simulation results demonstrate that the proposed strategy effectively regulates the servo valve opening and the pump’s output flow and pressure. Compared with a PID-controlled system, it achieves faster response, higher accuracy, and maintains a position error within 0.003 m. Moreover, it significantly reduces throttling and overflow losses compared to traditional valve control systems, yielding an energy-saving rate of 41.78%.更多还原