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关键词： 架空输电线路   远距离喷漆   模糊PID控制   人机交互   参数寻优  

摘要： 架空输电线路受到电力负载等因素影响,喷漆控制状态参数不同步,提出架空输电线路塔杆远距离喷漆自动控制系统。通过人机交互接口控制油漆桶与电动喷枪,结合模糊PID控制方法,以电力负载、角速度偏差、灵敏度等为约束参数,构建喷漆自动控制的约束参数模型;通过参数自动化辨识和系统性调节,进行协同控制和自适应调节,通过调节喷漆流量,实现状态参数寻优,完成自动控制系统设计。系统测试结果表明,远距离喷漆自动控制系统稳定性较好,电机控制的输出可靠性较强。

关键词： 自动控制   升降台   取书  

摘要： 作为小孩子,我经常因为身高不够而遇到麻烦。比如,要从衣柜的高处取衣物,要从书橱的顶层取书,怎么也够不着。

关键词： 自动控制   PLC技术   钢铁企业   电气自动化控制  

摘要： 阐述钢铁冶金生产线上使用自动化技术,科学合理地使用PLC技术在钢铁企业生产中实现自动化控制。探讨钢铁企业电气自动化控制中的PLC技术应用策略。

关键词： 自动控制理论  

ISBN: (纸本)9787111682004

摘要： 本书原版在2013年获得日本计测与自动控制学会著作奖,是日本大学广泛采用的自动控制教科书.是一本面向本科和专科层次的、结合当今控制技术发展的经典控制理论教科书.为便于初学者理解,译著对原书部分内容进行了编排,进而突出了重点,对各种数学公式的表达方式和含义进行了详尽的说明.特别对微分方程式与经典控制论的关联性、与控制学相关的数学内容进行了充实,并且结合实际应用对PID等控制方法进行了剖析.本书取材新颖、阐述严谨、内容丰富、重点突出、推导详尽、思路清晰、深入浅出、富有启发性,便于教学与自学. 本书还提供习题的详细题解,欢迎选用教材的教师联系策划编辑索要,具体联系方式如下:李小平,电话010-88379764;邮箱lixiaoping91142@***.

关键词： Discrete wavelet transform (DWT)   Water gate   Electricity   Automatic control   Fault processing  

摘要： In view of the poor error control performance of the traditional electric automatic control system for water gate, a kind of electric automatic control system for water gate based on discrete wavelet transform is proposed. The hardware structure of the system includes the local control module and communication module of the sluice gate. The local control module of the sluice gate consists of the gate opening meter, water level sensor, PLC, manual control box, etc., and the communication module consists of RS232 serial communication interface and communication server. The software consists of the main program module and the signal processing module. The main program module mainly includes the following software units: startup initialization unit, gate lifting unit, gate closing unit, gate automatic recovery unit, gate normal working state judgment unit, and alarm and fault processing unit. The signal processing module mainly uses the discrete wavelet transform to make discrete processing of the operation signal of the water gate. Through the combination of hardware and software, the electric automatic control of water gate is realized. In order to verify the strong error control performance of the system, the traditional electrical automatic control system for water gate is compared with the proposed system. The experimental results show that the error control performance of the system is better than the traditional electrical automatic control system for water gate, and more suitable for the electrical automatic control of water gate.

关键词： air compressor   automatic control technology   analysis  

摘要： Air compressor is an important engineering equipment that is often used. On this basis, we mainly analyze the automatic control technology of air compressor, and introduce and study the actual control effect of air compressor and its monitoring equipment. The related technical characteristics of the machine automatic control system provide the basic automation guarantee for the efficient and reliable operation of the air compressor system.

关键词： Simulated moving bed   Reinforcement learning   Deep neural network   Optimal control  

摘要： Optimal control of a simulated moving bed (SMB) process is challenging because the system dynamics is represented as nonlinear partial differential-algebraic equations combined with discrete events. In addition, product purity constraints are active at the optimal operating condition, which implies that these constraints can be easily violated by disturbance. Recently, artificial intelligence techniques have received significant attention for their ability to address complex problems, involving a large number of state variables. In this study, a data-based deep Q-network, which is a model-free reinforcement learning method, is applied to the SMB process to train a near-optimal control policy. Using a deep Q-network, the control policy of a complex dynamic system can be trained off-line as long as a sufficient number of data is provided. These data can be efficiently generated by performing numerical simulations in parallel on multiple machines. The on-line computation of the control input using a trained Q-network is fast enough to satisfy the computational time limit for the SMB process. However, because the Q-network does not predict the future state, it is not possible to explicitly impose state constraints. Instead, the state constraints are indirectly imposed by providing a relatively large penalty (negative reward) when the constraints are violate. Furthermore, logic-based switching control is utilized to limit the ranges of the extract and raf-finate purities, which helps to satisfy the state constraints and reduce the regions in the state space for reinforcement learning to explore. The simulation results demonstrate the advantages of applying deep reinforcement learning to control the SMB process. (C) 2021 Elsevier B.V. All rights reserved.