基于多目标数学建模的皮革机伺服系统控制优化问题研究

Control Optimization of Leather Machine Servo System Based on Multi-Objective Mathematical Modeling

为提高皮革机伺服系统的动态性能,以最小累计跟踪误差、调节时间、输出积分等方面的参数最优化设置为伺服控制系统的优化目标,以输出峰值和超调量等指标为约束条件,对控制系统位置环和速度环的优化问题进行多目标数学建模。同时,为了更高效、高质地获取优化结果,采用量子搜索算法对NSGA-Ⅱ算法进行改进,并将改进后的NSGA-Ⅱ算法作为优化模型的求解算法。仿真结果表明,在位置环上,采用NSGA-Ⅱ算法得到的控制参数优化结果,更好地提高了系统的性能。相较于传统工程整定方法与MOGA算法,NSGA-Ⅱ算法使PID控制器的阶跃响应调节时间分别缩短了66.17%和45.91%,动态性能更好;且系统在比例系数较低的前提下,积分时间常数更小,调节效率更高,总体性能在三者之中最优。在速度环上,采用所提改进NSGA-Ⅱ算法优化后的控制系统,相较于传统工程整定方法与MOGA算法,不仅调节时间大幅缩短,且超调量分别降低了29.72%和5.65%,具有更高的响应效率和平稳性,值得进一步在皮革机伺服系统的多目标控制优化任务中研究应用。

In order to improve the dynamic performance of the servo system of leather machine,the optimization of parameters such as minimum cumulative tracking error,adjustment time and output integral was set as the optimization objectives of the servo control system,and the optimization of the position loop and speed loop of the control system was modeled with multi-objective mathematical conditions.At the same time,in order to obtain more efficient and high-quality optimization results,the quantum search algorithm is used to improve the NSGA-II algorithm,and the improved NSGA-II algorithm is used as the solution algorithm of the optimization model.The simulation results show that,on the position loop,the optimized control parameters obtained by the proposed improved NSGA-II algorithm can better improve the performance of the system.Compared with the traditional engineering tuning method and the MOGA algorithm,the step response adjustment time of the PID controller is reduced by 66.17%and 45.91%respec-tively,and the dynamic performance is better.Under the premise of lower proportional coefficient,the integral time constant is smaller,the adjustment efficiency is higher,and the overall performance is the best among the three.In the speed loop,compared with the traditional engineering tuning method and the MOGA algorithm,the optimized control system using the proposed NSGA-II algorithm not only greatly reduces the adjustment time,but also reduces the overshoot by 29.72%and 5.65%respectively,which has higher response efficiency and stability.It is worth further research and application in the multi-objective control optimization task of leather machine servo system.