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作 者:诸定生 徐文辉 陈一旻 ZHU Ding-sheng;XU Wen-hui;CHEN Yi-min(Zhejiang Tailun Electric Power Group Co.,Ltd.,Huzhou 313000,China)
机构地区:[1]浙江泰仑电力集团有限责任公司,湖州313000
出 处:《自动化与仪表》2023年第4期19-23,共5页Automation & Instrumentation
摘 要:针对单位阶跃扰动所引起的静态误差、电压与功率波动较大的问题,该文提出带电作业工器具清洗机械设备的自动化高精度控制方法。分析机械化清洗设备烘干柜结构,针对噪声影响控制的因素进行信号去噪,建立设备信号的滑动窗口,提取运行特征向量;根据固定时段内提取的小波包时间熵,设计PID控制器,结合BP神经网络,整定自动化控制参数,引入粒子群算法,求解控制器最优解,实现机械化清洗设备自动化控制。实验结果表明,经该方法参数整定后,适应度值明显降低,控制误差曲线幅度变小,单位阶跃扰动所引起的静态误差被消除,经该方法控制后的机械化设备测试出的输出电压值与实际输出电压相接近,设备无功功率输出值与实际机械化设备无功功率输出值相接近。可实现机械设备的自动化、高精度控制,具有较好应用前景。In view of the static error caused by unit step disturbance and the large fluctuation of voltage and power,an automatic high-precision control method for cleaning machinery and equipment of live working tools and instruments is proposed.Analyze the structure of the drying cabinet of the mechanized cleaning equipment,de noise the signal according to the factors affecting the control of noise,establish the sliding window of the equipment signal,and extract the operating feature vector.According to the wavelet packet time entropy extracted in a fixed period of time,a PID controller is designed.Combined with BP neural network,the automatic control parameters are adjusted.Particle swarm optimization algorithm is introduced to solve the optimal solution of the controller,and the automatic control of mechanized cleaning equipment is realized.The experimental results show that after the parameters of this method are adjusted,the fitness value is significantly reduced,the amplitude of the control error curve becomes smaller,and the static error caused by the unit step disturbance is eliminated.The output voltage measured by the mechanized equipment controlled by this method is close to the actual output voltage,and the reactive power output value of the equipment is close to the reactive power output value of the actual mechanized equipment.It can realize the automation and high-precision control of mechanical equipment,and has a good application prospect.
关 键 词:机械化清洗设备 自动化控制 特征提取 单位阶跃扰动
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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