Observer-based wheelbase preview control of active vehicle suspensions

Optimal observer-based wheelbase preview regulator problem is investigated for active vehicle suspension systems. It is shown that the problem reduces to the classical linear quadratic Gaussian problem, whose solution is well defined, by augmenting dynamics of system and road inputs. The resulting optimal controller is in the form of augmented state feedback controller and this augmented state is estimated by Kalman-Bucy filter using dynamics of the augmented system. Numerical examples of a half car model are given to verify the performance improvement achievable with the proposed controller.     

State observability and condition observability for a class of interacting discrete event systems

This paper introduces the concepts of state observability and condition observability for condition systems, a class of systems composed of discrete state components which interact via discrete binary signals called conditions. Given a set of externally observed conditions, state observability implies that the state of the system can be determined from the observations, and condition observability implies that all unobserved input and output conditions of the system can be determined from the observations. In this paper, we present a class of systems which is state observable and condition observable. We present a method to synthesize an observer system to provide state and condition signal estimates for a single component subsystem.     

Adaptive control of permanent magnet synchronous machines with disturbance estimation

In this paper,an adaptive control scheme is introduced for permanent magnet synchronous machines (PMSMs)as an alternative to classical control techniques.The adaptive control strategy capitalizes on the machine’s inverse dynamics to achieve accurate tracking by using an observer to approximate disturbance in the form of friction and load torque.The controller’s output is then fed to a space vector pulse width modulation(SVPWM)algorithm to produce duty cycles for the inverter.The control scheme is validated through a set of simulations on an experimentally validated PMSM model.Results for different situations highlight its high speed tracking accuracy and high performance in compensating for friction and load disturbances of various magnitudes.     

基于滑模观测器的永磁同步电机无位置传感器控制

本文提出了一种基于滑模变结构控制原理的无位置传感器控制方法。通过分析永磁同步电机的模型,应用滑模变结构控制原理,提出了一种针对永磁同步电机的无位置传感器控制策略。它利用电机中容易测得的定子电流、直流母线电压,通过滑模变结构控制原理来估算转子位置。利用Matlab／Simulink对系统进行了仿真,仿真结果表明,转子位置估算结果基本与实际位置一致。     

柔性结构系统的观测器型鲁棒最优保性能控制

通过简要分析柔性直线系统结构,给出3自由度高阶直线柔性系统的数学模型。根据实际直线柔性控制过程滑动质量块位置状态信息易得、但速度状态信息不易得的特点,构造了速度状态观测器。同时针对柔性结构系统对于干扰激发的振动具有难以迅速稳定的特点,设计了基于观测器的直线柔性系统的鲁棒最优保性能控制。实验结果表明:对于直线柔性系统,所设计的观测器型鲁棒最优保性能控制是有效的。     

新型动磁式直线振荡执行器的动子位移自传感

针对一种新型无内定子动磁式直线振荡执行器,在建立其机电系统数学模型的基础上,提出一种基于全维状态观测器的动子位移自传感算法。通过对执行器输入电压和输出电流信号的处理和计算来估算动子位移。仿真和实验结果均表明:在变压变频控制方式下,该算法能实现不同电气驱动频率下的动子位移自传感;采用该算法进行行程估算的绝对误差最大值为0.32 mm,相对误差最大值为2.6%。此算法可以满足直线压缩机和直线泵类负载的变行程控制要求。     

State estimation for high-dimensional chemical processes

The application of conventional observer designs for high-dimensional systems may not always be practical due to high computational requirements or the resulting observers being too sensitive to measurement noise. In order to address these issues, this paper presents two observer design techniques for state estimation of high-dimensional chemical processes. One technique is used for systems with inputs, whereas the other one is specifically geared towards systems that are not excited from the outside. Both of these observers are applicable to linear and with a modification to non-linear systems.The main idea behind the presented observer designs is that a reduced-order observer is implemented instead of a conventional state estimator. The motivation is that subspaces, which are close to being unobservable, cannot be correctly reconstructed in a realistic setting due to measurement noise and inaccuracies in the model. The presented approaches make use of this observation and only reconstruct the parts of the system where accurate state estimation is possible. The observer designs are illustrated on a 30-tray distillation column model. Additionally, it has been shown that the location of process measurements has a major effect on the performance of the presented reduced-order observers.     

Observer设计模式在手机导航软件中的应用

该文探讨了观察者（Observer）设计模式的概念及在手机导航软件中的应用。通过实例证明了该模式下导航软件的性能得到了进一步的提升,提供了实现手机导航的Java程序代码,并总结该模式在软件设计过程中的优点。     

An homogeneous space geometry for simultaneous localisation and mapping

Simultaneous Localisation and Mapping (SLAM) is the archetypal chicken and egg problem: Localisation of a robot with respect to a map requires an estimate of the map, while mapping an environment from data acquired by a robot requires an estimate of the robot localisation. The nonlinearity and co-dependence of the SLAM problem has made it an ongoing research problem for more than thirty years. The present paper details recent advances in understanding the SLAM problem, specifically the existence of an underlying geometry and symmetry structure that provides significant insight into the difficulties that have plagued many SLAM algorithms. To demonstrate the power of the geometric insight we derive a constant gain observer for the SLAM problem that; that does not depend on linearisation, has globally asymptotically stable error dynamics, is very robust, and operates in dynamic environments (estimating the landmark velocities as states in the observer).     

Tool wear detection and fault diagnosis based on cutting force monitoring

In metal cutting processes, an effective monitoring system, which depends on a suitably developed scheme or set of algorithms can maintain machine tools in good condition and delay the occurrence of tool wear. In this paper, an approach is developed for fault detection and diagnosis based on an observer model of an uncertain linear system. A robust observer is designed, using the derived uncertain linear model, to yield the necessary and key information from the system. Subsequently, it is used as a state (tool wear) estimator, and fault detection is carried out by using the observed variables and cutting force. The developed approach is applied to milling machine center. Several linear models are identified based on different working conditions. A dominant model plus uncertain terms is derived from these model set and used as an observer. Threshold values are proposed for detecting the fault of the milling machine. Examples taken from experimental tests shown that the developed approach is effective for the fault detection. The approach can be used for fault detection of failures arising from sensor or actuator malfunction.