超空泡航行体H2/H∞状态反馈鲁棒控制

针对超空泡航行体纵平面运动时受到的强非线性滑行力以及存在外界干扰的问题,提出了一种H2/H∞状态反馈鲁棒控制方法.首先,利用线性变参数(linear parameter variyng,LPV)的方法将航行体模型转换成LPV镇定模型;其次,将LPV镇定模型转换成LPV跟踪模型,在考虑外界干扰的情况下,设计了H2/H∞状态反馈鲁棒控制器;最后进行仿真分析,结果表明,所设计的控制器能够使系统快速、准确地跟踪期望值,同时对外界干扰具有良好的抑制作用.     

速度测量不确定性影响下的无人车路径跟踪预瞄控制EI北大核心CSCD

预瞄距离是无人车路径跟踪预瞄控制系统设计中的一个关键参数,其选取往往依赖于车辆行驶速度.然而,车速的测量不可避免存在偏差,这必将影响系统的预瞄控制性能.本文针对这一问题,在充分考虑车速测量不确定性对预瞄距离选取影响的基础上,提出一种基于线性参数变化(LPV)系统的鲁棒H∞路径跟踪预瞄控制算法.首先,选取车速和预瞄距离为调度变量,将原系统转化为一种具有可变权重因子的LPV系统.然后,针对无人车系统状态的不完全可测性,设计一种基于观测器的鲁棒H∞控制器.最后,给出保证闭环系统鲁棒H∞性能的凸优化求解条件.仿真结果验证了本文提出控制算法的有效性.     

基于LM I方法的机器人L PV 鲁棒H ∞控制器设计

对平面两关节直接驱动机器人,提出一种同时将闭环极点配置到满足动态响应区域内的变增益LPV鲁棒H∞控制器设计新方法,利用LPV的凸分解方法,将机器人模型化为具有凸多面体结构的LPV模型,然后利用LMI技术对凸多面体各顶点分别设计满足H∞性能和闭环极点配置的反馈增益,再利用各顶点设计的反馈控制器综合得到具有凸多面体结构的LPV控制器,仿真结果验证了该控制器可使机器人随关节位置变化始终具有良好的控制性能。     

变参考轨迹下的鲁棒迭代学习模型预测控制

迭代学习模型预测控制是针对间歇过程的先进控制方法.它能通过迭代高精度跟踪给定参考轨迹,并保证时域上的闭环稳定性.然而,现有的迭代学习模型预测控制算法大多基于线性/线性化系统,且没有考虑参考轨迹变化的情况.本文基于线性参变系统提出一种能有效跟踪变参考轨迹的鲁棒迭代学习模型预测控制算法.首先,采用线性参变模型准确涵盖原始非线性系统的动态特性.然后,将鲁棒H_∞控制与传统迭代学习模型预测控制相结合,抑制变参考轨迹带来的跟踪误差波动,通过优化线性矩阵不等式约束下的目标函数求得控制输入.深入分析了鲁棒迭代学习模型预测控制的鲁棒稳定性和迭代收敛性.最后,通过对数值例子和连续搅拌反应釜系统的仿真验证了所提出算法的有效性.     

机器人LFT变增益H∞控制

针对平面两关节直接驱动机器人,基于LMI技术提出一种设计能保证在整个运动范围内始终具有很好动态性能的LFT变增益H∞控制器的新方法.将机器人系统转化为以两关节夹角余弦值为变参数的LPV模型并表示为关于变参数的LFT结构,利用变参数的测量值设计具有相同LFT结构的LPVH∞控制器,将此控制器的设计等价为以变参数为不确定项的LTI鲁棒控制器的设计并给出控制器可解的LMIs条件,然后归纳出获得控制器的求解方法.此控制器既克服了传统变增益控制器的缺陷,又利用变参数的测量值降低了控制器设计的保守性.实验结果验证了此控制器的有效性和先进性.     

过驱动飞行器线性参变鲁棒预测跟踪控制策略

针对飞行包线内过驱动飞行器参数线性时变、控制量多增益调度难的问题,基于约束动态控制分配提出了一种主环线性参变鲁棒预测跟踪控制器.采用飞行状态增量以及跟踪指令误差为增广变量,建立了过驱动飞行器的多面体线性参变离散控制模型.引入H∞性能指标,通过参变量转换将无穷时域min-max非线性鲁棒预测控制优化问题约简为线性矩阵不等式凸优化问题.以操纵面偏转跟踪误差和偏转变化量为混合二次型指标,建立了包含执行器动态性能的无约束控制分配模型.进而考虑操纵面的物理约束,设计了级联动态控制分配策略.仿真结果表明,该方法能够生成合理的操纵面控制指令,实现参考指令的有效跟踪.     

基于鲁棒可靠性的不确定时滞系统最优H∞控制器设计

用区间变量描述控制系统参数的不确定性,提出了不确定时滞系统鲁棒H_∞控制的鲁棒可靠性方法,基于鲁棒可靠性的不确定时滞系统最优状态反馈H_∞控制器设计方法,将系统的最优控制器设计归结为基于线性矩阵不等式(LMI)的优化问题．所设计的控制器可以在满足对所有不确定性鲁棒可靠的前提条件下,具有最优的H_∞鲁棒性能,并能在控制系统的设计中综合考虑控制性能、控制代价和鲁棒可靠性．数值算例说明了所提方法的有效性和可行性．     

连续时间多胞线性变参数系统变增益H∞/H2输出反馈控制

针对一类同时具有参数不确定性和外界干扰的非线性系统,提出了一种连续时间多胞线性变参数(LPV)系统变增益H_∞/H_2输出反馈控制方法.首先,对连续时间多胞LPV系统的变增益混合目标(H_∞/H_2指标和区域极点约束)输出反馈控制器综合方法进行了数学描述;其次,引入新的结构化松弛矩阵变量和参数依赖Lyapunov函数,将满足期望性能的混合目标鲁棒动态输出反馈控制问题转化为线性矩阵不等式框架内的有限维凸优化问题,进一步降低了所设计LPV控制器的保守性.最后,以四分之一车辆模型主动悬架系统为研究对象进行仿真,仿真结果验证了本文控制器的有效性.     

鲁棒H∞滤波器在AUV航向控制中的应用仿真

研究设计了一个鲁棒H∞滤波器来解决自治水下机器人（AUV）航向控制系统中部分难以测量状态变量的估计问题，并将其应用在AUV的航向控制系统中．建立了自治水下机器人在体坐标系下水平面运动的运动方程，并在特定的工作点对方程进行了线性化处理，得到了自治水下机器人的控制设计模型．基于线性矩阵不等式（LMI）方法对AUV航向控制系统设计了一个鲁棒H∞滤波器,并对该滤波器应用于AUV航向控制系统进行了仿真试验．仿真结果表明，该鲁棒H∞滤波器能够较好地抑制测量噪声的影响，较准确地估计出系统的状态变量，能够提高AUV航向控制系统的控制品质．     

鲁棒H∞滤波器在AUV航向控制中的应用仿真

研究设计了一个鲁棒H^∞滤波器来解决自治水下机器人（AUV）航向控制系统中部分难以测量状态变量的估计问题，并将其应用在AUV的航向控制系统中．建立了自治水下机器人在体坐标系下水平面运动的运动方程，并在特定的工作点对方程进行了线性化处理，得到了自治水下机器人的控制设计模型．基于线性矩阵不等式（LMI）方法对AUV航向控制系统设计了一个鲁棒H^∞滤波器，并对该滤波器应用于AUV航向控制系统进行了仿真试验．仿真结果表明，该鲁棒H^∞滤波器能够较好地抑制测量噪声的影响，较准确地估计出系统的状态变量，能够提高AUV航向控制系统的控制品质．     

机器人LFT变增益∞控制

针对平面两关节直接驱动机器人, 基于LMI技术提出一种设计能保证在整个运动范围内始终具有很好动态性能的LFT变增益H_∞ 控制器的新方法. 将机器人系统转化为以两关节夹角余弦值为变参数的LPV模型并表示为关于变参数的LFT结构, 利用变参数的测量值设计具有相同LFT结构的LPVH_∞ 控制器, 将此控制器的设计等价为以变参数为不确定项的LTI鲁棒控制器的设计并给出控制器可解的LMIs条件, 然后归纳出获得控制器的求解方法. 此控制器既克服了传统变增益控制器的缺陷,     

Control of nonlinear systems represented by Galerkin models using adaptation-based linear parameter-varying models

This paper studies the control of nonlinear Galerkin systems, which are an important class of nonlinear systems that arise in reduced-order modeling of infinite-dimensional systems. A novel approach is proposed in which a linear parameter-varying (LPV) model representing the Galerkin model is built, where the parameter variation is dictated by a specially designed adaptation scheme. The controller design is then carried out on the simpler LPV model, instead of dealing directly with the complicated nonlinear Galerkin system. An automatically scheduled H-infinity controller is designed using the LPV model, and it is proven that this controller will indeed achieve the desired stabilization when applied to the nonlinear Galerkin model. The approach is illustrated with an example on cavity flow control, where the design is seen to produce satisfactory results in suppressing unwanted oscillations.     

基于LPV观测器的永磁同步电机反推控制

针对永磁同步电机(Permanent Magnet Synchronous Motor,PMSM)无速度传感器转速跟踪控制精度问题,提出了一种基于线性变参数(Lineeo Parameteo Varying,LPV)转速观测器的永磁同步电机反推控制方法。该方法首先根据PMSM的LPV模型,推导出电机的凸胞形顶点方程;然后利用Lyapunov稳定性理论,获得了基于线性矩阵不等式(Lineeo Matrix Inequality,LMI)的观测器设计方法,构造了PMSM的LPV观测器,实现对电机转速及定子交轴电流的重构;最后运用反推控制策略,设计电机闭环系统控制器,实现对电机转速的高精度跟踪控制。仿真结果表明,该方法相较与传统PI矢量控制,跟踪精度高、响应快、抗负载扰动强,对实现PMSM的无速度传感器高精度转速跟踪控制具有重要意义。     

Model and robust gain‐scheduled PID control of a bio‐inspired morphing UAV based on LPV method

In this paper, a linear parameter‐varying (LPV)‐based model and robust gain‐scheduled structural proportion integral and derivative (PID) control design solution are proposed and applied on a bio‐inspired morphing wing unmanned aerial vehicle (UAV) for the morphing process. In the LPV model method, the authors propose an improved modeling method for LPV systems. The method combines partial linearization and function substitution. Using the proposed method, we can choose the varying parameters simply, thus creating a model that is more flexible and applicable. Then, a robust gain‐scheduled structural PID control design method is given by introducing a structural matrix to design a structural PID controller, which is more consistent with the structure of the PID controller used in practice and has a simpler structure than representative ones in the existing literature. The simulation results show that the developed LPV morphing UAV model is able to catch the response of the original nonlinear model with a smaller error than the existing Jacobian linearization method and the designed controller can maintain stable flights in practice with satisfactory robustness and performance.     

Design of adaptive robust guaranteed cost controller for wind power generator

According to the increasing requirement of the wind energy utilization and the dynamic stability in the variable speed variable pitch wind power generation system, a linear parameter varying (LPV) system model is established and a new adaptive robust guaranteed cost controller (AGCC) is proposed in this paper. First, the uncertain parameters of the system are estimated by using the adaptive method, then the estimated uncertain parameters and robust guaranteed cost control method are used to design a state feedback controller. The controller’s feedback gain is obtained by solving a set of linear matrix inequality (LMI) constraints, such that the controller can meet a quadratic performance evaluation criterion. The simulation results show that we can realize the goal of maximum wind energy capture in low wind speed by the optimal torque control and constant power control in high wind speed by variable pitch control with good dynamic characteristics, robustness and the ability of suppressing disturbance.     

机器人多胞变增益输出反馈H∞控制

针对n类关节的刚性机器人,提出一种设计包含极点配置的多胞变增益输出反馈H_∞控制器的新方法.利用平衡族附近的线性化,机器人系统可化为一关于平衡族的连续线性变参数系统,通过引入滤波器得到易于设计变增益控制器的增广对象,并将其凸分解为多胞表示,基于二次D 稳定和二次H_∞性能概念,利用多胞特性将整个控制器设计转化为对胞体顶点控制器的设计,然后利用LMI方法,对多胞的各顶点分别设计满足H_∞∞性能和动态特性的输出反馈控制器,最后综合顶点控制器得到具有同     

H Robust servo problem with H∞ norm constraint

A robust servo problem with an H-infinity norm constraint is investigated based on the LMI (Linear Matrix Inequality) approach to the H-infinity control problem. The following results are obtained. (1) A necessary and sufficient condition for the existence of an H-infinity controller with robust tracking property is derived. It consists of the following two indepent conditions: (i) the existence of an H-infinity controller; (ii) a boundary constraint at the reference mode. (2) If there exists an H-infinity controller with robust tracking performance, there exists one whose order equals the sum of an H-infinity controller and the internal model.     

Wind turbine integrated structural and LPV control design for improved closed-loop performance

An iterative redesign algorithm is proposed to integrate the design of the structural parameters and a linear parameter-varying (LPV) controller for a three-bladed horizontal-axis wind turbine. The LPV controller is designed for an eighth-order lumped model of the wind turbine consisting of blades, drive-train and the tower. The lumped model response is matched with detailed open-loop numerical simulations using the Fatigue, Aerodynamics, Structures and Turbulence (FAST) code. The controller is scheduled in real-time based on the mean wind speed to account for the varying system dynamics. The objective is to track the operating trajectory meanwhile minimise the H _∞ performance index from the wind turbulence to the controlled output vector consisting of pitch angle, blade tip deflection, and the generator speed and torque. Sensitivity analysis of the closed-loop performance index with respect to the structural parameters of the system is examined. The integrated design problem is formulated as an iterative sequential controller/structure redesign to obtain the structural parameters and controller matrices corresponding to a local optimal performance index. Each step of the iterative procedure is formulated as a linear matrix inequality (LMI) optimisation problem that can be solved efficiently using available LMI solvers. The evolution of the structural parameters and performance index through the integrated design is illustrated. The FAST closed-loop simulations for two selected designs with the smallest values of the performance index demonstrate the improved performance of the overall system through the integrated structure/control redesign in both minimising the effect of the wind disturbance on the generator output power, and reducing the structural loads on the wind turbine.     

Discretization and event triggered digital output feedback control of LPV systems

This paper investigates the problem of discretization and digital output feedback control design for continuous-time linear parameter-varying (LPV) systems subject to a time-varying networked-induced delay. The proposed discretization procedure converts a continuous-time LPV system into an equivalent discrete-time LPV system based on an extension of the Taylor series expansion and using an event-based sampling. The scheduling parameters are continuously measured and modeled as piecewise constant. A new transmission of the measured output to the controller is triggered by significant changes in the parameters, yielding time-varying transmission intervals. The obtained discretized model has matrices with polynomial dependence on the time-varying parameters and an additive norm-bounded term representing the discretization residual error. A two step strategy based on linear matrix inequality conditions is then proposed to synthesize a digital static scheduled output feedback control law that stabilizes both the discretized and the LPV model. The conditions can also be used to provide robust (i.e., independent of the scheduling parameter) static output feedback controllers. The viability of the proposed design method is illustrated through numerical examples.