CMAC改进算法在电动负载模拟器的应用

在电动负载模拟器的控制系统设计中,其参数优化一般需要大量试验.根据负载模拟器的工作原理建立了伺服电机的数学模型,在分析CMAC神经网络控制结构的基础上,引入了更新系数和补偿环节,提出了一种基于CMAC神经网络的改进算法.对各控制参数进行了寻优,获得了参数的选择域.通过对系统的数字仿真表明,该方法可稳定地跟踪非线性输入,...     

主蒸汽温度的串级CMAC学习控制策略

结合CMAC学习控制器和串级控制系统,提出了主蒸汽温度的串级CMAC学习控制策略,其自适应性强,非常适合于计算机实时控制。仿真研究表明,该策略的控制品质良好,远远优于PID控制。     

伺服系统的高斯基函数CMAC学习控制研究

在高精度伺服系统中,由于摩擦力及负载扰动等因素的影响,常规PID控制难以满足越来越高的控制精度、跟踪性能等指标要求。本文提出了基于商新基函数CMAS在线学习的控制方案,并给出了相应的学习算法。仿真结果表明．该方法不仅有较好的控制精度,而且具有学习速度快等优点。     

基于PSO算法的FCMAC控制器及其在主汽温控制中的应用

模糊CMAC神经控制器能反映人脑认知的模糊性和连续性,它采用高斯函数作为模糊隶属函数,利用CMAC神经网络实现模糊推理,并可对隶属函数进行实时调整,从而使它具有自适应和学习能力.文中讨论了这种控制器参数的PSO学习算法,对电厂锅炉主蒸汽温度控制的仿真表明了FCMAC控制器及其PSO学习算法的可行性和有效性.     

Risk probability predictions for coal enterprise infrastructure projects in countries along the Belt and Road Initiative

The Belt and Road Initiative has significantly promoted the construction and development of coal enterprises along the Belt and Road through the building of a new platform that encourages global economic cooperation. This study examines problems caused by the uncertainty of risk occurrence during the process of coal enterprise construction as part of the Belt and Road Initiative. Consequently, the study identifies and classifies various risk factors. In total, 11 types of risks and 39 risk factors involved in the construction process are summarized. These include natural, cultural, religious, marketing, and outsourcing-related risks. A prediction indicator system was also established to apply to the risk occurrence probability related to coal mine construction along the Belt and Road. In this regard, the study embedded an improved artificial fish swarm algorithm (IAFSA) into a cerebellar model articulation controller (CMAC) neural network model and collected risk probability details for the construction of the Barapukuria Coal Mine in Bangladesh from 2013 to 2018 as sample data. By researching the model and sample, this study obtained various risk occurrence probability intervals. Moreover, diversified risk probabilities were verified and predicted. Finally, this study empirically proves that an IAFSA–CMAC parallel coupling algorithm is able to achieve precise predictions about risks. This finding has great significance for risk management and control in the coal enterprises of countries along the Belt and Road.     

脱硫系统吸收塔浆液PH值控制与仿真

电站湿式石灰石/石膏脱硫系统中,为保证较高的脱硫效率(95％以上),吸收塔内浆液PH的控制是其中最重要的控制参数之一.目前,电站中广泛采用石灰石浆液PH值为反馈信号,引入锅炉负荷信号和FGD进口S02含量作为石灰石浆液的前馈信号,进行石灰石浆液给料调节的方法,虽然提高了控制水平,但是由于吸收塔内化学反应过程的强非线性和...     

基于CMAC和PID复合控制的气动位置伺服系统研究

该文以气动机械手为例对气动位置伺服系统进行了分析。首先建立了气动位置伺服系的数学模型,分析了系统的特性,然后介绍了CMAC与PID复合控制策略的原理及其特点。对采用该控制策略的系统进行了仿真研究。通过与只采用PID控制的气动位置伺服系统的性能对比得知,基于CMAC和PID复合控制的气动位置伺服系统有更高的精确性。     

自组织小脑神经网络算法研究

针对神经网络逼近非线性函数问题,提出一种在线的自组织小脑神经网络,其不需要预先确定存储空间的大小。该网络可以根据输入数据自适应地改变神经网络节点数和相对应的权值,具有良好的智能性;针对挠性卫星姿态控制,将自组织小脑神经网络用于不确定项的补偿中,提高系统的鲁棒性。仿真结果表明,该方法神经网络性能良好,实现了卫星姿态控制。     

Optimal design of motion control for scan tracking measurement: A CMAC approach

This paper is concerned with the optimal design of motion control for scan tracking measurement using Cerebellar Model Articulation Controller (CMAC) neural networks in order to improve the measuring efficiency while maintaining the measurement accuracy, and to achieve friction compensation. Aiming at the effect of geometric shape and material friction of the model surface on the precision and efficiency of scan tracking measurement, technologies of model surface geometric and friction feature identification and quantification are researched. A novel optimal motion controller for scan tracking measurement is designed and realized, which automatically predicts the surface features (including geometric feature and friction feature) and adjusts the scan tracking velocity in advance. The approach to friction quantification and compensation in measuring process is given specifically. Finally, through Matlab simulation experiments, the realizability and application effect of the studied optimal motion control method for scan tracking measurement are verified, and the measuring efficiency is increased by 123.33%. Simulation results show that the proposed motion controller is an effective way to enhance the measurement efficiency remarkably compared with the traditional control strategy.     

机械手分散CMAC控制器

针对机械手动力学模型未知情况 ,采用类似于计算力矩法的控制器结构 ,设计了基于 CMA C神经网络分散控制器作为非线性估计器、PD控制器作为跟踪外环的机械手控制方案。分析了该控制方案的稳定性 ,通过仿真验证了该控制方法的有效性。结果表明 ,在未知机械手动力学的情况下 ,控制系统的运行仍是有效的 ,并且不同于传统的自适应控制器 ,不需要计算回归矢量 ,也不必对系统参数做任何线性假设。由于采用分散CMAC结构 ,简化了控制器实现的复杂度 ,易于采用大规模可编程数字逻辑阵列和 ASIC数字电路予以硬件实现。