绕地飞船的INS/GPS组合测控定位系统

根据INS和GPS的基本原理,充分利用它们各自的优点,构建了INS/GPS组合测控定位系统.研究了该系统在绕地飞船自主定位中的应用.根据绕地飞船运动的实际情况建立了误差状态方程和组合观测方程.仿真分析表明该INS/GPS组合测控定位系统模型既能保证定位的高精度,又能满足目标的高动态.     

无人机GPS/INS组合导航卡尔曼滤波技术

惯性导航(INS)和全球定位导航(GPS)是现代航空武器中应用广泛的两种导航技术.运用组合导航技术,将INS与GPS两者有机组合,能很好地克服各自缺点,形成优势互补结构.在无人机应用GPS/INS组合导航的基础上,引入卡尔曼滤波技术,能够有效提高导航的性能和精度,从而构成比较理想的组合导航系统.     

基于VxWorks系统的无人车GPS／INS组合导航

为了实现汽车自主导航,针对实时性导航,提出了一种基于VxWorks操作系统的GPS＋INS（inertial navigation system,惯性导航）组合导航。首先分析了无人车模型,布置导航的总体框架,确定CAN网络为整车通讯网络;然后研究了GPS导航,利用高精度GPS设备得到无人车坐标值,进而实现了GPS导航;接着研究了INS导航,利用一定精度INS的两个加速度计来积分推算无人车的航位,实现导航;再通过VxWorks结合两种导航方式,互相弥补信号的丢失与不可用。同时,开发了基于Windows的可视化导航界面,直观地观察导航效果和进行后台操控。实验验证了此导航的可行性和实时性。     

抗电磁干扰的无人机GPS/INS组合导航方法

无人机应用于电力巡线时,高压电力故障导致的异常放电可能会产生复杂而且强大的电磁场,会严重影响GPS的信号质量和定位精度,影响无人机的正常导航,因此必需考虑电磁环境对GPS信号和无人机导航性能的影响。提出一种根据GPS数据可信度进行加权的自适应卡尔曼滤波导航算法,通过GPS和内部导航系统(INS)的数据偏差幅度反映GPS数据可信度,利用模糊逻辑算法计算加权值,分配GPS在组合导航中的权重,研发出一种结合GPS和INS的模糊组合导航方法。仿真和实验结果显示,该算法在GPS数据受电磁干扰失真的情况下,调整GPS数据在组合导航中的权重,使组合导航输出的位置和速度误差控制在可行范围内,保证了组合导航的精度。     

采用EKF状态观测器及滑模算法结合的半车主动悬架控制

针对主动悬架控制可能面临的平顺性、悬架动挠度及车轮动载性能冲突,以及考虑参数不确定与外界干扰带来的鲁棒性问题,论文基于非线性滤波方法设计了滑模控制器以综合改善悬架性能;根据控制算法所需实时而准确的车辆状态信息需求,采用扩展卡尔曼滤波方法设计了状态观测器。分别进行随机路面激励、正弦路面激励和凸块路面激励仿真分析,结果显示所设计控制器具有良好的路面适应性,在不牺牲悬架动挠度的情况下,可以有效改善车辆平顺性及轮胎抓地力,有利于综合提升车辆的乘坐舒适性和操纵稳定性。     

采用扩展滑模观测器的数控机床永磁同步电机鲁棒控制方法

为了实现对数控机床永磁同步电机转速的高精度控制,考虑负载转矩扰动、电路和磁路扰动等因素,采用扩展滑模观测器设计了鲁棒控制方法.首先建立了带有复合干扰的永磁同步电机模型,然后将复合干扰作为扩展状态,设计了扩展滑模观测器,实现了对转速、转动加速度和复合干扰的精确估计,并进行了收敛性和稳定性分析,最后提出了一种新型滑模趋近律...     

面向室内行人的Range-only UWB/INS紧组合导航方法

为了提高室内行人组合导航系统的精度和灵活性,提出了一种Range-only超宽带(UWB)/惯性导航系统(INS)紧组合导航方法。该方法将锚点的位置信息引入到系统状态变量中并通过数据融合滤波器进行预估,以克服传统UWB/INS紧组合导航模型中需要预先获取锚点位置信息的缺点,减少锚点位置信息精度对组合导航系统的影响。在此基础上,利用迭代扩展卡尔曼滤波(IEKF)来完成组合导航系统的数据融合滤波,以提高对目标行人导航信息的预估精度。实验结果显示,所提方法的平均绝对位置误差与传统UWB/INS紧组合方法相比降低了11.69%,算法对锚点位置信息的依赖程度也显著降低。     

基于模糊滑模控制和两级滤波滑模观测器的PMSM改进控制策略

针对传统带有滑模观测器的永磁同步电机控制系统中转矩脉动大、抖振明显、反电动势估计精度差等问题,提出基于模糊滑模控制和两级滤波滑模观测器的PMSM改进控制策略.首先,在速度环提出基于双曲正弦函数的新型趋近率,结合模糊控制思想对趋近率参数实现自整定,设计了一种基于新型趋近率的模糊积分滑模速度环控制器,并且对新型趋近率的抖振抑制效果给出严格分析.其次,提出基于变截止频率低通滤波器和修正反电动势观测器的两级滤波结构,抑制反电动势中的高频分量和测量噪声,并对转子位置进行合理补偿,继而设计了两级滤波滑模观测器;通过Lyapunov判据对本文提出控制策略的稳定性进行了推导证明.仿真和实验结果表明,与传统滑模观测器相比,改进的控制器使电机在启动和受到外部扰动时系统响应良好,有效改善了转矩脉动、抖振、反电动势的估计精度等问题.     

GPS与惯性导航系统的组合应用研究

文章对GPS与惯性导航系统的优缺点进行了比较说明,针对各自的特点提出了组合应用的设计方案,实验结果表明该方案应用可靠、误差较小能够满足实际需要。     

基于GPS／INS／Lidar的无人车导航

为了实现无人车的自主导航,提出了一种基于GPS和INS的组合导航,并辅以激光雷达实现避障功能。首先确立整车的控制架构,确定基于SAE—J1939协议的整车CAN总线通信网络;然后研究了GPS导航,利用GPS的载波差分获得较高的位置精度,同时整合惯导的输出数据;最后通过激光雷达的不断扫描,获取周围物体的角度和距离,实现周边环境建模,有效规避障碍。实验验证了此导航的可行性和实时性。     

基于ARM和DSP的INS/GPS组合系统设计

为满足组合导航系统要求成本低、体积小、精度高、低功耗的特点,本文以SAMSUNG公司S3C2410型和TI公司TMS320C6713型芯片为核心器件设计了一种嵌入式导航计算机系统,此设计可提高系统的精度,更好地满足系统实时性的要求。     

A derivative UKF for tightly coupled INS/GPS integrated navigation

The tightly coupled INS/GPS integration introduces nonlinearity to the measurement equation of the Kalman filter due to the use of raw GPS pseudorange measurements. The extended Kalman filter (EKF) is a typical method to address the nonlinearity by linearizing the pseudorange measurements. However, the linearization may cause large modeling error or even degraded navigation solution. To solve this problem, this paper constructs a nonlinear measurement equation by including the second-order term in the Taylor series of the pseudorange measurements. Nevertheless, when using the unscented Kalman filter (UKF) to the INS/GPS integration for navigation estimation, it causes a great amount of redundant computation in the prediction process due to the linear feature of system state equation, especially for the case with system state vector in much higher dimension than measurement vector. To overcome this drawback in computational burden, this paper further develops a derivative UKF based on the constructed nonlinear measurement equation. The derivative UKF adopts the concise form of the original Kalman filter (KF) to the prediction process and employs the unscented transformation technique to the update process. Theoretical analysis and simulation results demonstrate that the derivative UKF can achieve higher accuracy with a much smaller computational cost in comparison with the traditional UKF.     

Anti-disturbance speed control of low-speed high-torque PMSM based on second-order non-singular terminal sliding mode load observer

This paper presents an anti-disturbance speed control of low-speed high-torque permanent magnet synchronous motor (PMSM) based on the second-order non-singular terminal sliding mode load observer. According to the coordinate transformation theory, the mathematical model of PMSM is established. Subsequently, the second-order non-singular terminal sliding mode observer (SNTSMO) is designed to observe the changes of load disturbance in the PMSM system. The SNTSMO combines the advantages of both high-order sliding mode and non-singular terminal sliding mode to achieve the fast convergence and no chattering. Next, the sliding mode controller (SMC) is designed to achieve speed loop control of PMSM. Then, the anti-disturbance compound speed controller is established on the basis of SMC and SNTSMO, wherein the feed-forward compensation is used to reduce the disturbance from the load. Finally, the numerical simulations and experiments are presented according to the schematic diagram of the designed compound speed controller of PMSM. The results demonstrate that the designed SNTSMO can precisely estimate the load disturbance and suppress the effects of buffeting in the traditional sliding mode observer (SMO). Additionally, the designed compound speed controller of PMSM can achieve smooth speed control in the presence of load disturbance, achieve the purpose of anti-disturbance speed control and further improve the robustness of the control system.     

Analysis of a robust Kalman filter in loosely coupled GPS/INS navigation system

GPS/INS integrated system is very subject to uncertainties due to exogenous disturbances, device damage, and inaccurate sensor noise statistics. Conventional Kalman filer has no robustness to address system uncertainties which may corrupt filter performance and even cause filter divergence. Based on the INS error dynamic equation, a robust Kalman filter is analyzed and applied in loosely coupled GPS/INS integration system. The norm bounded robust Kalman filter, with recursive form by solving two Riccati equations, guarantees a estimation variance bound for all the admissible uncertainties, and can evolve into the conventional Kalman filter if no uncertainties are considered. This paper will analyze the suitable case for the robust Kalman filter in GPS/INS system, the filter characteristics including parameter setting, parameter meaning, and filter convergence condition are discussed simutaneously. The robust filter performance will be compared with conventional Kalman filter through simulation results.     

采用滑模观测器的机械臂故障检测与控制优化

针对复合干扰影响下机械臂的故障检测和控制精度问题,提出了一种基于滑模观测器的故障检测和控制优化方法。首先建立了带有电机故障、模型误差和机械摩擦等复合干扰的机械臂系统故障模型,然后设计了滑模观测器来实现在复合干扰下对电机故障的准确检测,最后引入滑模观测器对电机故障程度进行估计,并设计了反步容错控制方法,从而实现了对机械臂系统的精确控制。仿真结果表明,基于滑模观测器的故障检测和控制优化方法能够快速、准确检测和估计电机故障,确保机械臂系统准确跟踪指令信号,角度跟踪误差范围仅为-0.2°～0.2°,能够准确估计出复合干扰的大小,估计误差范围仅为-0.1～0.1 (°)/s²,大大改善了对机械臂的控制效果。     

A new method of seamless land navigation for GPS/INS integrated system

For the last few years, integrated navigation systems have been widely used to calculate positions and attitudes of vehicles. The strapdown inertial navigation system (SINS) provides velocity, attitudes and position information, whereas the global positioning system (GPS) provides velocity and position information. A method using neural network (NN) and wavelet-based de-noising technology is introduced into the SINS/GPS/magnetometer integrated navigation system, because system accuracy may decrease during GPS outages. When the GPS is working well, NN is trained using the velocity and position information provided by SINS as input and the corresponding errors as output. Wavelet multi-resolution analysis (WMRA) is also introduced to de-noise the errors, the desired output of NN. Test results showed that velocity accuracies improved using NN, but other accuracies remained poor. By re-training NN with WMRA, the system accuracies improved to the level of using normal GPS signal. In addition, NN trained with WMRA also improved the approximation to the actual model, further enhancing alignment accuracy.     

Adaptive sliding mode current control with sliding mode disturbance observer for PMSM drives

This paper focuses on the current control of a permanent magnet synchronous motor (PMSM) for electric drives with model uncertainties and external disturbances. To improve the performance of the PMSM current loop in terms of the speed of response, tracking accuracy, and robustness, a hybrid control strategy is proposed by combining the adaptive sliding mode control and sliding mode disturbance observer (SMDO). An adaptive law is introduced in the sliding mode current controller to improve the dynamic response speed of the current loop and robustness of the PMSM drive system to the existing parameter variations. The SMDO is used as a compensator to restrain the external disturbances and reduce the sliding mode control gains. Experiments results demonstrate that the proposed control strategy can guarantee strong anti-disturbance capability of the PMSM drive system with improved current and speed-tracking performance.     

一种新型永磁同步电机高阶滑模转速观测器的研究

针对面贴式永磁同步电机无位置传感器速度控制系统存在的速度检测延迟、检测误差较大、动态响应不够快等问题,对永磁同步电机无位置传感器速度控制系统模型和传统滑模速度观测器结构和原理进行了分析,对高阶滑模算法理论进行了推导,结合永磁同步电机数学模型,提出了一种以位置信号为滑模变量,以高阶滑模变结构算法为基础的新型滑模转速观测器,利用Simulink软件构建了基于新型滑模速度观测器永磁同步电机矢量控制系统,对电机的起动特性、速度跟踪特性、抗外界干扰性能进行了研究。研究结果表明,由于新的滑模观测器将转子位置与反电势信号的关系进行了分离,消除了反电势信号处理滤波器对速度估算的延迟,提高了速度检测精度,从而改善了系统的稳态和动态性能。     

基于滑模观测器的永磁同步电机无传感器矢量控制

为解决永磁同步电机（PMSM）控制中机械式位置传感器带来的成本及可靠性等问题,将滑模观测器技术应用到PMSM矢量控制系统中。该系统采用滑模面及滑模等效控制方法,通过选择足够大的滑模增益,在观测电流和实测电流之间的误差上构建滑模面,对电机反电势进行观测以得到转子位置角,并基于Lyapunov稳定性判据对滑模观测器的收敛性进行了分析;建立了应用滑模观测器的PMSM无传感器矢量控制实验系统,设计了位置及速度滑模控制器。进行了1500r／min稳态及正负转速切换的角度估算实验,实验结果验证了该方法的有效性。研究结果表明,基于滑模观测器的无传感器控制策略能准确估计出PMSM的转子位置角,从而得到转子速度,且系统具有较好的动、静态特性。     

基于扰动观测器的永磁同步电机电流环自适应滑模控制

针对扰动对永磁同步电机转速伺服系统性能的影响,提出了基于扰动观测器的电流环自适应滑模控制方法。设计了自适应律在线估计系统的内部参数摄动以补偿模型不确定性扰动。同时,设计了滑模扰动观测器实时估计系统外部负载扰动,并将观测值前馈补偿到电流环自适应滑模控制器,在提高系统鲁棒性的同时降低滑模控制系统的抖振。实验结果显示,采用基于扰动观测器的电流环自适应滑模控制方法,系统可快速、准确、无超调地跟踪900r/min的速度指令,调节时间为0.08s,稳态误差为±5r/min。加入0.6N·m的负载扰动,该控制方法的最大转速波动为21r/min,比PI控制方法的转速波动减小了3.4%。仿真和实验结果表明,基于扰动观测器的电流环自适应控制方法提高了永磁同步电机转速伺服系统的鲁棒性和动态响应性能,同时可有效抑制滑模控制系统的抖振。