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基于模糊PID的矫直机液压控制系统研究
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摘要
随着我国经济的快速发展,各行业对高品质和高强度的钢板需求越来越大。为了保证钢板的高性能,矫直机在现代钢铁企业中已成为不可缺少的设备,它在板材质量的控制中起着十分重要的作用。在过去的几十年中,矫直机的矫直理论己经十分成熟,目前对矫直机的研究主要集中在它的液压调整装置,采用先进的控制算法的矫直机调整装置可以取得更好的控制效果。
     本文以矫直机压下调整装置的液压伺服控制系统为研究对象,从控制策略方面对液压压下调整装置控制系统进行研究。详细分析了矫直机各部件的数学模型,对压下调整装置的恒力控制系统建立了简化模型,通过时域分析和频域分析研究了系统的动态特性。借助MATLAB中的Simulink和Fuzzy工具箱,对矫直机调整装置的常规PID控制、模糊控制和模糊自适应PID控制进行仿真分析。仿真结果表明当采用常规PID控制策略时,系统的超调量与响应时间均不能满足技术要求;当采用模糊控制,响应时间较常规PID控制没有明显的改善,而且系统出现了较大的稳态误差;当采用模糊自适应PID控制,超调量、响应时间与误差虽然能够满足要求,但系统性能还有待进一步提高。根据己建立控制模型的响应曲线,有针对性地采用了基于人工免疫的改进型模糊自适应PID控制策略来提高系统性能。试验表明该控制策略非常明显的优化了系统性能。
     通过对仿真结果的研究和分析,本课题在实验室的仿真是比较成功的。在保证控制系统精度和稳定性的前提下改进型控制策略提高了系统的响应时间,使得系统的动态性能较经典控制方案的动态性能有很好的改善。
With the rapid development of our country's economy, the demands of high-quality and high-strength steel plates are rising fast in various sectors. In order to guarantee the steel plate's high performance, straightening machine has become the essential equipment in the modern iron-steel corporation. It plays an important role in quality control of the plate. In the past decades, the leveling technology is already very mature. At present, the study of the Straightening machine is concentrated on the hydraulic adjustment installment. The adjustment installment of straightening machine with advanced control algorithm can reach much better effect of control.
     This dissertation is mainly study on the hydraulic servo-control system of adjustment installment in straightening machine, and emphatically makes a study of control system of hydraulic adjustment installment at electro-hydraulic servo-control. In this dissertation, it analyzes various parts' mathematical model, and it has established the simplified model of constant-force control system of adjustment installment, and analyze the dynamic characteristic of the control system in straightening machine. Then the conventional PID controller, fuzzy controller and fuzzy self-tuning PID controller of adjustment installment in straightening machine are simulated by using fuzzy-logic toolbox and Simulink in MATLAB. The experimental results illustrate that the conventional PID controller is used in the system, overshoot and response time always cannot achieve the specification. When uses the fuzzy controller, there are not obviously optimization compare with conventional PID, and the system presented the steady-state error. When uses the fuzzy self-tuning PID controller, the overshoot, response time and error can meet the requirements, but the system performance remains to be further enhancing. According to the former response curve of established model, we selected the advanced fuzzy self-tuning PID controller which based on artificial immune algorithm to enhance the system performance. The experiment indicated that this algorithm obviously optimized the system parameters of the impact of changes in the system.
     After studying and analyzing simulated result, this subject simulation is more successful when doing in the laboratory. While guaranteeing precision of control system, advanced control algorithm improves the system capacity of resisting disturbance, and the dynamic performance of system has much better improvement compared with the classic method.
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