This paper proposes an adaptive nonlinear proportional-derivative(ANPD)controller for a two-wheeled self-balancing robot(TWSB)modeled by the Lagrange equation with external forces.The proposed control scheme is design...This paper proposes an adaptive nonlinear proportional-derivative(ANPD)controller for a two-wheeled self-balancing robot(TWSB)modeled by the Lagrange equation with external forces.The proposed control scheme is designed based on the combination of a nonlinear proportional-derivative(NPD)controller and a genetic algorithm,in which the proportional-derivative(PD)parameters are updated online based on the tracking error and the preset error threshold.In addition,the genetic algorithm is employed to adaptively select initial controller parameters,contributing to system stability and improved control accuracy.The proposed controller is basic in design yet simple to implement.The ANPD controller has the advantage of being computationally lightweight and providing high robustness against external forces.The stability of the closed-loop system is rigorously analyzed and verified using Lyapunov theory,providing theoretical assurance of its robustness.Simulations and experimental results show that the TWSB robot with the proposed ANPD controller achieves quick balance and tracks target values with very small errors,demonstrating the effectiveness and performance of the proposed controller.The proposed ANPD controller demonstrates significant improvements in balancing and tracking performance for two-wheeled self-balancing robots,which has great applicability in the field of robot control systems.This represents a promising solution for applications requiring precise and stable motion control under varying external conditions.展开更多
针对滚动轴承故障诊断过程中样本处理、故障识别等技术问题,提出一种基于Morlet小波和分类回归树(Classification and Regression Tree,CART)的滚动轴承故障诊断方法。首先,利用Morlet小波分析方法和移动窗方法对轴承振动信号进行样本...针对滚动轴承故障诊断过程中样本处理、故障识别等技术问题,提出一种基于Morlet小波和分类回归树(Classification and Regression Tree,CART)的滚动轴承故障诊断方法。首先,利用Morlet小波分析方法和移动窗方法对轴承振动信号进行样本处理。其次,对提取的短样本进行变分模态分解与特征提取,完成训练集和测试集的构建。然后,使用训练集训练CART决策树分类模型,同时引入随机搜索和K折交叉验证用于模型关键参数优化,以获取理想的轴承故障分类模型。测试集验证结果表明,该方法不但能实现多种轴承故障的有效诊断、在含噪测试集中表现良好,而且单个样本的数据长度和采样时长的缩短效果明显。展开更多
分布式光伏受天气影响较大,测算110kV供电区域的分布式光伏承载能力,对区域供电来说意义重大。基于此,提出基于分类与回归树(calssification and regression tree,CART)的110kV供电区域分布式光伏承载能力测算模型。该模型以分布式电源...分布式光伏受天气影响较大,测算110kV供电区域的分布式光伏承载能力,对区域供电来说意义重大。基于此,提出基于分类与回归树(calssification and regression tree,CART)的110kV供电区域分布式光伏承载能力测算模型。该模型以分布式电源输出功率、区域分布式电源发电量占比、局部分布式电源线损增量等数据为基础,利用CART决策树建立110kV供电区域分布式光伏承载能力测算模型,并使用改进鲸鱼优化算法求解测算结果。经实验测试发现,该模型对分布式光伏承载能力的测算精准度较高,可有效测算不同实验区域在不同季节时的分布式光伏承载能力,具有较高的应用价值。展开更多
针对预警中空间群目标反演精度不高、鲁棒性较差的问题,提出了一种基于分类回归树(classification and regression tree,CART)算法的空间目标本体反演方法。首先构建分类与回归决策树,并将空间目标的入射角、光谱辐射亮度、温度等特征...针对预警中空间群目标反演精度不高、鲁棒性较差的问题,提出了一种基于分类回归树(classification and regression tree,CART)算法的空间目标本体反演方法。首先构建分类与回归决策树,并将空间目标的入射角、光谱辐射亮度、温度等特征数据作为决策树的输入;再基于基尼系数评估数据纯度,对目标在不同温度、不同入射角下的光谱辐射亮度进行分割;最后通过在每个节点处对数据集进行划分,实现对空间目标本体的有效反演。数值对比实验表明,3种典型空间目标的决策树模型反演结果与实际情况一致,验证了所提方法的有效性。展开更多
文摘This paper proposes an adaptive nonlinear proportional-derivative(ANPD)controller for a two-wheeled self-balancing robot(TWSB)modeled by the Lagrange equation with external forces.The proposed control scheme is designed based on the combination of a nonlinear proportional-derivative(NPD)controller and a genetic algorithm,in which the proportional-derivative(PD)parameters are updated online based on the tracking error and the preset error threshold.In addition,the genetic algorithm is employed to adaptively select initial controller parameters,contributing to system stability and improved control accuracy.The proposed controller is basic in design yet simple to implement.The ANPD controller has the advantage of being computationally lightweight and providing high robustness against external forces.The stability of the closed-loop system is rigorously analyzed and verified using Lyapunov theory,providing theoretical assurance of its robustness.Simulations and experimental results show that the TWSB robot with the proposed ANPD controller achieves quick balance and tracks target values with very small errors,demonstrating the effectiveness and performance of the proposed controller.The proposed ANPD controller demonstrates significant improvements in balancing and tracking performance for two-wheeled self-balancing robots,which has great applicability in the field of robot control systems.This represents a promising solution for applications requiring precise and stable motion control under varying external conditions.
文摘针对滚动轴承故障诊断过程中样本处理、故障识别等技术问题,提出一种基于Morlet小波和分类回归树(Classification and Regression Tree,CART)的滚动轴承故障诊断方法。首先,利用Morlet小波分析方法和移动窗方法对轴承振动信号进行样本处理。其次,对提取的短样本进行变分模态分解与特征提取,完成训练集和测试集的构建。然后,使用训练集训练CART决策树分类模型,同时引入随机搜索和K折交叉验证用于模型关键参数优化,以获取理想的轴承故障分类模型。测试集验证结果表明,该方法不但能实现多种轴承故障的有效诊断、在含噪测试集中表现良好,而且单个样本的数据长度和采样时长的缩短效果明显。
文摘分布式光伏受天气影响较大,测算110kV供电区域的分布式光伏承载能力,对区域供电来说意义重大。基于此,提出基于分类与回归树(calssification and regression tree,CART)的110kV供电区域分布式光伏承载能力测算模型。该模型以分布式电源输出功率、区域分布式电源发电量占比、局部分布式电源线损增量等数据为基础,利用CART决策树建立110kV供电区域分布式光伏承载能力测算模型,并使用改进鲸鱼优化算法求解测算结果。经实验测试发现,该模型对分布式光伏承载能力的测算精准度较高,可有效测算不同实验区域在不同季节时的分布式光伏承载能力,具有较高的应用价值。
文摘针对预警中空间群目标反演精度不高、鲁棒性较差的问题,提出了一种基于分类回归树(classification and regression tree,CART)算法的空间目标本体反演方法。首先构建分类与回归决策树,并将空间目标的入射角、光谱辐射亮度、温度等特征数据作为决策树的输入;再基于基尼系数评估数据纯度,对目标在不同温度、不同入射角下的光谱辐射亮度进行分割;最后通过在每个节点处对数据集进行划分,实现对空间目标本体的有效反演。数值对比实验表明,3种典型空间目标的决策树模型反演结果与实际情况一致,验证了所提方法的有效性。
