五自由度磁悬浮开关磁阻电机最小二乘支持向量机自检测与逆控制
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摘要
磁悬浮电机集传统电机旋转与磁轴承悬浮功能于一体,以同时产生驱动负载的电磁转矩和支承转子的悬浮力为目标,打破了传统电机仅为了产生电磁转矩而必须保持气隙磁场平衡的思路,开辟了高速电机研究领域的新方向。磁悬浮开关磁阻电机将磁悬浮技术与开关磁阻电机相结合,在继承一般磁悬浮电机无摩擦、无磨损、轴向空间利用率高、转子临界转速大等优点基础上,充分发挥了开关磁阻电机的高速优越性以及对恶劣环境的适应性,同时通过径向力的主动控制,有效改善了开关磁阻电机因不平衡磁拉力造成的振动和噪声问题,成为目前磁悬浮电机领域一个新的研究热点。本文以一台五自由度磁悬浮开关磁阻电机为研究对象,在对其电磁-动力学特性进行精确化建模与分析基础上,针对系统内部存在的多自由度、强耦合、非线性特性以及传感器带来的价格昂贵、可靠性低、动态性能差等问题,开展了五自由度磁悬浮开关磁阻电机最小二乘支持向量机自检测与逆控制研究。论文主要研究工作及取得的成果如下：
1)给出了五自由度磁悬浮开关磁阻电机总体拓扑结构,设计了一种新型三磁极交直流供电式径向-轴向混合磁轴承,分析了该磁轴承径向和轴向悬浮工作原理；介绍了磁悬浮开关磁阻电机基本结构及其悬浮力和转矩产生机理,设计了磁悬浮开关磁阻电机和径向-轴向混合磁轴承的关键电磁结构参数,给出了设计结果并研制了一台完整的五自由度磁悬浮开关磁阻电机实验样机。
2)基于平动-转动坐标系构建了五自由度磁悬浮开关磁阻电机转子动力学模型,依据动力学模型定性分析了转子支承特性；针对磁轴承传统平衡位置附近近似线性化模型的不足,采用等效磁路法构建了径向-轴向混合磁轴承大气隙范围内精确悬浮力模型；考虑到转子径向偏心和耦合对模型的影响,结合等效磁路、有限元分析和虚位移定理构建了磁悬浮开关磁阻电机偏心耦合下的精确化悬浮力和转矩模型；并利用Matlab和Ansoft仿真软件对模型的耦合非线性进行定性和定量分析。
3)针对五自由度磁悬浮开关磁阻电机所用传感器带来的一系列问题,将最小二乘支持向量机(LS-SVM)与状态观测器设计理论相结合,研究了基于LS-SVM观测器的磁悬浮开关磁阻电机转子位移位置自检测方法。构建了磁悬浮开关磁阻电机状态空间模型,阐述了位移位置LS-SVM观测器设计原理,采用Lyapunov稳定性理论证明了位移位置观测器的稳定性,通过LS-SVM离线训练和在线学习获得了磁悬浮开关磁阻电机位移位置观测器。仿真表明LS-SVM观测器不依赖于磁悬浮开关磁阻电机精确数学模型和具体运行参数,实现简单,观测精度高,可为磁悬浮开关磁阻电机无传感器运行提供实时准确的位移和位置反馈信息。
4)为实现五自由度磁悬浮开关磁阻电机磁轴承支承端转子位移的实时高精自检测,开展了基于粒子群优化LS-SVM的磁轴承转子位移预测建模研究。借助径向-轴向混合磁轴承大气隙范围内的精确悬浮力模型进行闭环采样仿真,通过采集具有代表性和遍历性的输入输出样本数据,离线训练LS-SVM获得了磁轴承转子位移预测模型,针对LS-SVM超参数选取问题,采用粒子群优化算法对其进行自动寻优,以提高转子位移预测模型的预测能力：对比仿真结果验证了所建位移预测模型实现了五自由度磁悬浮开关磁阻电机磁轴承支承端转子径向和轴向位移的自检测。
5)针对磁悬浮开关磁阻电机电磁转矩和悬浮力模型的耦合非线性,将LS-SVM辨识建模方法与逆系统线性化解耦控制原理相结合,研究了基于LS-VM逆系统的磁悬浮开关磁阻电机解耦控制。分析了磁悬浮开关磁阻电机电磁转矩和悬浮力模型的可逆性,采用自适应遗传算法优化LS-SVM构建了磁悬浮开关磁阻电机逆辨识模型：将遗传优化的LS-SVM逆模型与对象串联构造伪线性复合系统,实现了磁悬浮开关磁阻电机电磁转矩与悬浮力的线性化和解耦；在此基础上,对线性化解耦后的伪线性复合系统设计了内模控制器,提高了控制系统的鲁棒性和抗干扰能力。
6)为解决磁轴承现有控制方法只适合于平衡位置附近线性化模型的局限性,进一步将LS-SVM逆系统方法用于五自由度磁悬浮开关磁阻电机支承磁轴承的大气隙范围内非线性解耦控制中。分析了磁轴承大气隙范围内悬浮力模型的可逆性；给出了遗传优化LS-SVM的逆模型辨识步骤；将辨识得到的LS-SVM逆模型作为前馈补偿环节,通过引入改进的PID反馈控制环节,构建了磁轴承复合解耦控制系统；对比仿真结果表明所提LS-SVM逆系统方法具有较好的动、静态性能,可实现五自由度磁悬浮开关磁阻电机支承磁轴承大气隙范围内高性能非线性解耦控制。
7)针对五自由度磁悬浮开关磁阻电机高速运行控制需要,分别以dSPACE和DSP为控制核心设计了两套高速数字控制系统,并对数字系统结构、功率变换器拓扑、驱动与缓冲电路、位移与位置检测电路、电流与电压检测电路进行了设计和器件选型,为五自由度磁悬浮开关磁阻电机高性能控制算法的实现创造了硬件条件。
Bearingless motor combines the functions of a motor and a magnetic bearing together within the same stator frame. It can produce the driving torque and suspension force on the rotor simultaneously so that there is no mechanical contact between the stator and rotor. Therefore, it pioneers a new field in the study of high-speed motor. Bearingless switched reluctance motor (BSRM) is a novel bearingless motor, which integrates the bearingless technology to the switched reluctance motor (SRM). It not only inherits the advantages of bearingless motor, but also enhances the high-speed performance and adaptability to atrocious surroundings of the SRM. Moreover, by the actively control of rotor radial displacement, it also provides a new approach to solve the problem of vibration and noises caused by asymmetric magnetic pull in the SRM. Therefore, BSRM becomes a worldwide research hotspot in the study of bearingless motor.
The dissertation focuses mainly on the theory and realization of a five degree of freedom BSRM (5-DOF-BSRM), including the working principle and experimental prototype, the accurate analytical expression of torque and suspension force, the self-sensing algorithm of rotor position and displacement, the nonlinear decoupling control method and the digital control system design. The main researches and the corresponding results are as follows:
1) The topological structure of5-DOF-BSRM is introduced, and a novel AC-DC3-DOF radial-axial hybrid magnetic bearing (HMB) is designed and the working principle of radial-axial HMB is introduced. Then, the stracture of three phase12/8pole double windings BSRM is introduced and the principle of torque and radial force production in BSRM is analyzed. Besides, the major electromagnetic and structure parameters of5-DOF-BSRM are designed and the experimental prototype of integrated5-DOF-BSRM is presented.
2) The rotor dynamics model of5-DOF-BSRM is built in translational and rotational coordinate system and the rotor support characteristics are analyzed. The nonlinear suspension force model of radial-axial HMB in large air gap is deduced by equivalent magnetic circuit. Meanwhile, the torque and radial force model of BSRM in the case of eccentric and coupling is deduced based equivalent magnetic circuit, finite element analysis and virtual displacement principl. In addition, the coupling and nonlinear features are analyzed qualitatively and quantitatively in Matlab and Ansoft.
3) To realize the self-sensing control for BSRM, a designing method of rotor displacement and position observers using least squares support vector machine (LS-SVM) is proposed. The state space model of BSRM is built and the design principle of LS-SVM observer is described. the stability of LS-SVM observer is proved by Lyapunov stability theory. Through offline training and online learning, the observers of BSRM are obtained. The findings show that the proposed method can observe the actual rotor displacement and position accurately, independent of mathematical model and specific parameters.
4) To realize the rotor displacement self-sensing for radial-axial HMB, a predictive modeling method of rotor displacement for radial-axial HMB using LS-SVM optimized by particle swarm optimization (PSO) is presented. Through the collection of representative input/output data based on the nonlinear force model, the prediction model of radial-axial HMB is obtained by training LS-SVM. PSO is used to optimize LS-SVM parameters to improve the performance of the prediction model. The findings show that the prediction model can accurately predict the rotor displacement.
5) In view of the coupling and nonlinear characteristic in model of BSRM, LS-SVM inverse model identification and decoupling control approach is proposed. The reversibility of the BSRM model is analyzed, and the adaptive genetic algorithm (AGA) is adopted to optimize LS-SVM to build the inverse model of BSRM. Then through the combining of LS-SVM inverse model and BSRM, BSRM is realized linearization and decoupling. Besides, the internal model controller is designed to achieve strong robustness and anti-interference ability for the decoupling control system.
6) LS-SVM inverse-control method is employed to large air gap nonlinear control of radial-axial HMB. The reversibility of radial-axial HMB model is proved, and identification procedures of LS-SVM inverse model are elaborated, and the identification performance of LS-SVM inverse model is tested. Then the linearization and decoupling of radial-axial HMB is realized to series the LS-SVM inverse model with radial-axial HMB. On this basis, an improved PID controller is designed to achieve closed-loop feedback control, which improves the dynamic and static performance of LS-SVM inverse-control method.
7) Two experimental systems for5-DOF-BSRM are presented based on digital control platform using dSPACE and DSP respectively. The control platform structure, power converter, drive and buffer circuit, displacement and position detection circuit, current and voltage detection circuit are introduced detailly, which establishes a solid foundation for developing the high performance control of the5-DOF-BSRM further.
1)给出了五自由度磁悬浮开关磁阻电机总体拓扑结构,设计了一种新型三磁极交直流供电式径向-轴向混合磁轴承,分析了该磁轴承径向和轴向悬浮工作原理；介绍了磁悬浮开关磁阻电机基本结构及其悬浮力和转矩产生机理,设计了磁悬浮开关磁阻电机和径向-轴向混合磁轴承的关键电磁结构参数,给出了设计结果并研制了一台完整的五自由度磁悬浮开关磁阻电机实验样机。
2)基于平动-转动坐标系构建了五自由度磁悬浮开关磁阻电机转子动力学模型,依据动力学模型定性分析了转子支承特性；针对磁轴承传统平衡位置附近近似线性化模型的不足,采用等效磁路法构建了径向-轴向混合磁轴承大气隙范围内精确悬浮力模型；考虑到转子径向偏心和耦合对模型的影响,结合等效磁路、有限元分析和虚位移定理构建了磁悬浮开关磁阻电机偏心耦合下的精确化悬浮力和转矩模型；并利用Matlab和Ansoft仿真软件对模型的耦合非线性进行定性和定量分析。
3)针对五自由度磁悬浮开关磁阻电机所用传感器带来的一系列问题,将最小二乘支持向量机(LS-SVM)与状态观测器设计理论相结合,研究了基于LS-SVM观测器的磁悬浮开关磁阻电机转子位移位置自检测方法。构建了磁悬浮开关磁阻电机状态空间模型,阐述了位移位置LS-SVM观测器设计原理,采用Lyapunov稳定性理论证明了位移位置观测器的稳定性,通过LS-SVM离线训练和在线学习获得了磁悬浮开关磁阻电机位移位置观测器。仿真表明LS-SVM观测器不依赖于磁悬浮开关磁阻电机精确数学模型和具体运行参数,实现简单,观测精度高,可为磁悬浮开关磁阻电机无传感器运行提供实时准确的位移和位置反馈信息。
4)为实现五自由度磁悬浮开关磁阻电机磁轴承支承端转子位移的实时高精自检测,开展了基于粒子群优化LS-SVM的磁轴承转子位移预测建模研究。借助径向-轴向混合磁轴承大气隙范围内的精确悬浮力模型进行闭环采样仿真,通过采集具有代表性和遍历性的输入输出样本数据,离线训练LS-SVM获得了磁轴承转子位移预测模型,针对LS-SVM超参数选取问题,采用粒子群优化算法对其进行自动寻优,以提高转子位移预测模型的预测能力：对比仿真结果验证了所建位移预测模型实现了五自由度磁悬浮开关磁阻电机磁轴承支承端转子径向和轴向位移的自检测。
5)针对磁悬浮开关磁阻电机电磁转矩和悬浮力模型的耦合非线性,将LS-SVM辨识建模方法与逆系统线性化解耦控制原理相结合,研究了基于LS-VM逆系统的磁悬浮开关磁阻电机解耦控制。分析了磁悬浮开关磁阻电机电磁转矩和悬浮力模型的可逆性,采用自适应遗传算法优化LS-SVM构建了磁悬浮开关磁阻电机逆辨识模型：将遗传优化的LS-SVM逆模型与对象串联构造伪线性复合系统,实现了磁悬浮开关磁阻电机电磁转矩与悬浮力的线性化和解耦；在此基础上,对线性化解耦后的伪线性复合系统设计了内模控制器,提高了控制系统的鲁棒性和抗干扰能力。
6)为解决磁轴承现有控制方法只适合于平衡位置附近线性化模型的局限性,进一步将LS-SVM逆系统方法用于五自由度磁悬浮开关磁阻电机支承磁轴承的大气隙范围内非线性解耦控制中。分析了磁轴承大气隙范围内悬浮力模型的可逆性；给出了遗传优化LS-SVM的逆模型辨识步骤；将辨识得到的LS-SVM逆模型作为前馈补偿环节,通过引入改进的PID反馈控制环节,构建了磁轴承复合解耦控制系统；对比仿真结果表明所提LS-SVM逆系统方法具有较好的动、静态性能,可实现五自由度磁悬浮开关磁阻电机支承磁轴承大气隙范围内高性能非线性解耦控制。
7)针对五自由度磁悬浮开关磁阻电机高速运行控制需要,分别以dSPACE和DSP为控制核心设计了两套高速数字控制系统,并对数字系统结构、功率变换器拓扑、驱动与缓冲电路、位移与位置检测电路、电流与电压检测电路进行了设计和器件选型,为五自由度磁悬浮开关磁阻电机高性能控制算法的实现创造了硬件条件。
Bearingless motor combines the functions of a motor and a magnetic bearing together within the same stator frame. It can produce the driving torque and suspension force on the rotor simultaneously so that there is no mechanical contact between the stator and rotor. Therefore, it pioneers a new field in the study of high-speed motor. Bearingless switched reluctance motor (BSRM) is a novel bearingless motor, which integrates the bearingless technology to the switched reluctance motor (SRM). It not only inherits the advantages of bearingless motor, but also enhances the high-speed performance and adaptability to atrocious surroundings of the SRM. Moreover, by the actively control of rotor radial displacement, it also provides a new approach to solve the problem of vibration and noises caused by asymmetric magnetic pull in the SRM. Therefore, BSRM becomes a worldwide research hotspot in the study of bearingless motor.
The dissertation focuses mainly on the theory and realization of a five degree of freedom BSRM (5-DOF-BSRM), including the working principle and experimental prototype, the accurate analytical expression of torque and suspension force, the self-sensing algorithm of rotor position and displacement, the nonlinear decoupling control method and the digital control system design. The main researches and the corresponding results are as follows:
1) The topological structure of5-DOF-BSRM is introduced, and a novel AC-DC3-DOF radial-axial hybrid magnetic bearing (HMB) is designed and the working principle of radial-axial HMB is introduced. Then, the stracture of three phase12/8pole double windings BSRM is introduced and the principle of torque and radial force production in BSRM is analyzed. Besides, the major electromagnetic and structure parameters of5-DOF-BSRM are designed and the experimental prototype of integrated5-DOF-BSRM is presented.
2) The rotor dynamics model of5-DOF-BSRM is built in translational and rotational coordinate system and the rotor support characteristics are analyzed. The nonlinear suspension force model of radial-axial HMB in large air gap is deduced by equivalent magnetic circuit. Meanwhile, the torque and radial force model of BSRM in the case of eccentric and coupling is deduced based equivalent magnetic circuit, finite element analysis and virtual displacement principl. In addition, the coupling and nonlinear features are analyzed qualitatively and quantitatively in Matlab and Ansoft.
3) To realize the self-sensing control for BSRM, a designing method of rotor displacement and position observers using least squares support vector machine (LS-SVM) is proposed. The state space model of BSRM is built and the design principle of LS-SVM observer is described. the stability of LS-SVM observer is proved by Lyapunov stability theory. Through offline training and online learning, the observers of BSRM are obtained. The findings show that the proposed method can observe the actual rotor displacement and position accurately, independent of mathematical model and specific parameters.
4) To realize the rotor displacement self-sensing for radial-axial HMB, a predictive modeling method of rotor displacement for radial-axial HMB using LS-SVM optimized by particle swarm optimization (PSO) is presented. Through the collection of representative input/output data based on the nonlinear force model, the prediction model of radial-axial HMB is obtained by training LS-SVM. PSO is used to optimize LS-SVM parameters to improve the performance of the prediction model. The findings show that the prediction model can accurately predict the rotor displacement.
5) In view of the coupling and nonlinear characteristic in model of BSRM, LS-SVM inverse model identification and decoupling control approach is proposed. The reversibility of the BSRM model is analyzed, and the adaptive genetic algorithm (AGA) is adopted to optimize LS-SVM to build the inverse model of BSRM. Then through the combining of LS-SVM inverse model and BSRM, BSRM is realized linearization and decoupling. Besides, the internal model controller is designed to achieve strong robustness and anti-interference ability for the decoupling control system.
6) LS-SVM inverse-control method is employed to large air gap nonlinear control of radial-axial HMB. The reversibility of radial-axial HMB model is proved, and identification procedures of LS-SVM inverse model are elaborated, and the identification performance of LS-SVM inverse model is tested. Then the linearization and decoupling of radial-axial HMB is realized to series the LS-SVM inverse model with radial-axial HMB. On this basis, an improved PID controller is designed to achieve closed-loop feedback control, which improves the dynamic and static performance of LS-SVM inverse-control method.
7) Two experimental systems for5-DOF-BSRM are presented based on digital control platform using dSPACE and DSP respectively. The control platform structure, power converter, drive and buffer circuit, displacement and position detection circuit, current and voltage detection circuit are introduced detailly, which establishes a solid foundation for developing the high performance control of the5-DOF-BSRM further.
引文
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