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作 者:张继光 丁正红 李腾飞 ZHANG Jiguang;DING Zhenghong;LI Tengfei(Shaanxi Hydropower Development Group Co.,Ltd.,Xi’an 710065,China)
机构地区:[1]陕西省水电开发集团股份有限公司,西安710065
出 处:《自动化与仪表》2024年第2期60-64,70,共6页Automation & Instrumentation
摘 要:为提高水轮机的调节性能和稳定性,满足日益增长的清洁能源需求和能源利用效率,研究基于免疫粒子群的水轮机调节系统的动态滑模控制系统。构建水轮机调节系统动态滑模控制系统结构,分析水轮机调节系统运行状态,通过动态滑模控制器对水轮机的运行状态进行预测和控制,使水轮机的运行状态能够平滑、稳定地跟踪给定的参考轨迹,并采用免疫粒子群算法优化动态滑模控制器的参数,将优化后的控制结果作用于电液伺服系统,控制油缸位置,保障对水轮机状态稳定和精确调节,及时跟踪和响应系统状态变化。实验结果可知,该系统在锯齿波信号和阶跃信号下具有适应性强、鲁棒性好,并有效解决了系统的抖振问题,且控制误差小。In order to improve the regulation performance and stability of hydraulic turbine and meet the increasing demand for clean energy and energy utilization efficiency,the dynamic sliding mode control system of hydraulic turbine regulation system based on immune particle swarm optimization is studied.The structure of dynamic sliding mode control system of hydraulic turbine governing system is constructed,and the running state of hydraulic turbine governing system is analyzed.The running state of hydraulic turbine can be predicted and controlled by dynamic sliding mode controller,so that the running state of hydraulic turbine can track the given reference trajectory smoothly and stably.The parameters of dynamic sliding mode controller are optimized by immune particle swarm optimization,and the optimized control results are applied to electro-hydraulic servo system to control the position of oil cylinder,ensure the stable and accurate regulation of hydraulic turbine state,and track and respond to system state changes in time.The experimental results show that the system has strong adaptability and good robustness under sawtooth signal and step signal,and effectively solves the chattering problem of the system with small control error.
分 类 号:TP273[自动化与计算机技术—检测技术与自动化装置]
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