Road curvature estimation for vehicle lane departure detection using a robust Takagi–Sugeno fuzzy observer

In this paper, a lane departure detection method is studied and evaluated via a professional vehicle dynamics software. Based on a robust fuzzy observer designed with unmeasurable premise variables with unknown inputs, the road curvature is estimated and compared with the vehicle trajectory curvature. The difference between the two curvatures is used by the proposed algorithm as the first driving risk indicator. To reduce false alarms and take into account the driver corrections, a second driving risk indicator is considered, which is based on the steering dynamics, and it gives the time to the lane keeping. The used nonlinear model deduced from the vehicle lateral dynamics and a vision system is represented by an uncertain Takagi–Sugeno fuzzy model. Taking into account the unmeasured variables, an unknown input fuzzy observer is then proposed. Synthesis conditions of the proposed fuzzy observer are formulated in terms of linear matrix inequalities using Lyapunov method. The proposed approach is evaluated under different driving scenarios using a software simulator. Simulation results show good efficiency of the proposed method.     

Estimation of land vehicle roll and pitch angles

In this article, two kinematics-based observers are proposed to estimate the vehicle roll and pitch angles by using an inertial measurement unit. The observers are mathematically proven to be stable if the vehicle yaw rate is not zero. With a design variation of the observer gains, the estimated roll or pitch angle is shown to further asymptotically converge to the true value, eliminating possible errors caused by the biases of the acceleration signals. Simulation results show that accurate estimation of both pitch and roll angles can be achieved without the help of external sensors such as global positioning systems, either by using the accelerometer-based reference pitch or roll angle as the maneuver varies, or by using an observer with zero steady-state error property.     

动力定位船舶的自适应滑模观测器设计

针对含有未知扰动等不确定性的船舶动力定位系统,在系统不确定性不满足匹配条件的情况下,提出了一种自适应滑模观测器的设计方法。首先通过构造辅助输出使匹配条件得以满足,设计高增益观测器估计含有未知变量的辅助输出;接着基于滑模变结构理论对带有辅助输出的新系统进行观测器设计,通常船舶动力定位系统的不确定性上界值未知,采用自适应律调整滑模面增益,保证系统鲁棒性的同时还可避免增益取值过大而造成的抖振问题;然后将观测器增益矩阵的设计转化为求解线性矩阵不等式约束的优化问题;最后通过仿真验证了所提方法的有效性。     

基于鲁棒二次稳定性理论的状态观测器增益矩阵求法

针对具有定子电阻不确定参数的电机模型，设计了全阶自适应状态观测器，运用具有定子电阻参数不确定系统的二次稳定性理论，推导出转子速度的自适应辨识率，同时将定子电阻和速度视作不确定参数，利用LMI工具箱中求解不确定参数系统二次稳定性的方法，得到状态观测器的增益矩阵来保证整个系统在全速度范围内的稳定运行。此方法计算量小，易满足实时性控制要求。仿真结果表明，基于鲁棒二次稳定性理论求出状态观测器增益矩阵能保证系统在全速度范围内的稳定运行，并且可抑制定子电阻不确定性对速度辨识的影响，具有很好的鲁棒性能。     

Tyre-force estimation by Kalman inverse filtering: applications to off-highway mining trucks

Kalman inverse filtering is used to develop a methodology for real-time estimation of forces acting at the interface between tyre and road on large off-highway mining trucks. The system model formulated is capable of estimating the three components of tyre-force at each wheel of the truck using a practical set of measurements and inputs. Good tracking is obtained by the estimated tyre-forces when compared with those simulated by an ADAMS virtual-truck model. A sensitivity analysis determines the susceptibility of the tyre-force estimates to uncertainties in the truck's parameters.     

基于汽车启停系统的车载网络技术研究

本论文介绍了汽车启停技术的应用背景、控制原理,并介绍了汽车车载网络的应用,结合具体车型分析了车载网络技术在汽车启停系统中的应用。     

阀控非对称缸全状态反馈位置系统研究

根据非对称缸电液位置伺服系统的组成,对系统中的阀控非对称缸的数学模型进行了研究,得出基于全状态反馈的电液伺服系统的框图和仿真模型.控制器采用全维状态观测器实现状态反馈,以二阶工程最佳为优化目标.仿真结果表明：该控制器实现了液压位置伺服系统的极点配置,完成了优化目标,验证了全状态反馈控制应用在非对称缸电液伺服系统中的可行性.     

基于观测器的船用调距桨控制系统 故障分析与仿真试验

针对船用调距桨控制系统传感器恒偏差、恒增益及液压缸完全失效三种典型故障模式,建立了相应的故障模型,并提出了相容多性能指标约束下的故障诊断观测器算法。进一步,对MCP34-C/4调距桨螺距控制系统进行了典型故障下的仿真实验和传统观测器诊断方法的对比研究。仿真表明,所提出的故障观测器诊断方法具有快速性、鲁棒性和灵敏性特点,适用于线性模型下船用调距桨控制系统的故障诊断。     

一种低成本的C语言协程实现

本文介绍了C语言中一种新的协程编程模型,即利用Timer驱动有限状态机方式,有效地解决了传统C语言协程实现的兼容性和跨平台等问题,提供了C语言下并行编程除线程之外的另一种选择。     

城市多模式公交网络出行时间可靠性模型研究

随着城市的发展,快速轨道交通和快速公交系统逐渐融入到常规公交系统中,构成了复杂的多模式公交网络,在此公交网络环境下乘客公交出行时间的稳定可靠程度直接影响到公交系统的服务性能,因此,本文以常规公交和地铁组成的典型多模式公交网络为研究对象,利用状态增广技术,建立了换乘约束条件下的出行时间可靠性模型,从而为评价和改善多模式公交网络服务性能提供决策支持。