Regional pole assignment for uncertain delta-operator systems

The pole assignment in a specified disk by state feedback for uncertain delta-operator systems is studied. By making use of algebra Riccati equations, a sufficient and necessary condition of pole assignment for a kind of parameter uncertain delta-operator system in a specified disk by state feedback is presented. And the design method of state feedback controller is also developed. The proposed method can unify some previous related results of continuous and discrete time systems into the delta framework. The efficiency of the design method is illustrated by a numerical example.

A Pole Assignment Design Method of Process Control System for Tubular Heat Exchanger

This Paper has first studied the simplified model of tubular heat exchanger which is widely used in the industry and other field.On the basis of reference 2,a new pole assignment design method of pro-cess control system with derivative control action is found.For the above system,the method and the for-mation which calculate the feedback matrix K and gain matrix L is given,and the simulation of the system is made.

Simplified Methods for Eigenvalue Assignment

A state feedback method of reduced order for eigenvalue assignment is developed in this paper. It offers immediate assignment of m eigenvalues, with freedom to assign the remaining n-m eigenvalues. The method also enjoys a systematic one-step application in the case where the system has a square submatrix. Further simplification is also possible in certain cases. The method is shown to be applicable to uncontrollable systems, offering the simplest control law when having maximum uncontrollable eigenvalues.

脱模机转动系统极点配置控制器设计

为了提高混凝土试块脱模质量,研发了一款全新的全自动化实验设备-混凝土试块脱模机,为了提高脱模机的工作效率和质量,以脱模机转动系统为例,提高其脱模机转动系统的角度控制。该文基于极点配置理论设计了一种脱模机转动控制器,并通过仿真实验验证其有效性。结果显示,在6 s的时间内系统可以达到稳定状态。该文采用了遗传算法优化加权系数,通过实验仿真,将系统稳定时间缩短到0.5 s。研究结果表明,采用基于极点配置控制理论的脱模机转动控制器,结合遗传算法进行优化,可以提高脱模机转动系统的角度控制,缩短稳定时间,提高设备运行效率。

Neuromorphic Continuous-Time State Space Pole Placement Adaptive Control

A neuromorphic continuous-time state space pole assignment adaptive controller is proposed, which is particularlyappropriate for controlling a large-scale time-variant state-space model due to the parallely distributed nature ofneurocomputing. In our approach, Hopfield neural network is exploited to identify the parameters of a continuous-timestate-space model, and a dedicated recurrent neural network is designed to compute pole placement feedback control law inreal time. Thus the identification and the control computation are incorporated in the closed-loop, adaptive, real-timecontrol system. The merit of this approach is that the neural networks converge to their solutions very quickly andsimultaneously.

双柔性机械臂伺服系统PI控制策略

柔性机械臂系统中的负载柔性、关节柔性会导致输出转速波动,故使用PI控制策略对伺服系统进行控制.根据连续体振动理论和拉格朗日方程建立同时考虑负载和关节两种柔性的动力学模型,并分析了两种柔性对系统传动特性的影响.使用Arnoldi方法对传递函数进行降阶,并对降阶误差进行评价.采用极点配置方法设计控制器参数,讨论了极点阻尼系数、自然频率等对系统动态特性的影响.最后进行双柔性机械臂的仿真分析和转动控制实验,结果表明:适当调整控制器参数可以有效减弱柔性机械臂伺服传动系统末端的转速波动,进而抑制机械谐振现象,使系统趋于稳定.

直流微电网暂态自适应虚拟惯性控制策略及其参数可行域研究

附加虚拟电容控制能够挖掘直流微电网隐藏的惯性,从而缓解新能源渗透下直流母线电压对功率波动敏感的问题,但其无法满足系统在动态调节过程中灵活的惯性需求。为了向直流微电网提供灵活惯性支撑能力,通过在源侧换流器控制中耦合电压参数与惯性参数改变系统电量积累进程,提出一种能够实时响应微电网运行工况变化并投入可变虚拟电容的暂态自适应虚拟惯性控制策略。借助系统小信号模型和根轨迹分析,揭示惯性参数变化对系统稳定性的影响。在此基础上,采用控制理论配置极点的方法为参数选取提供有效约束,实现控制参数的优化设计。搭建五端直流微电网仿真系统,验证暂态自适应虚拟惯性控制提供的动态虚拟电容灵活的暂态自适应能力。

比例-时滞控制器作用下自主车辆队列系统的最右侧极点配置方法

现有关于时滞作用下自主车辆队列控制的研究,多侧重于分析与遏制时滞对队列控制的负面效应,却忽视了时滞的正面作用.针对如何有效利用时滞提升同构自主车辆队列系统控制性能的问题,引入时滞设计了一种比例-时滞(Proportional-Retarded,PR)控制器,利用柯西-黎曼方程分析PR控制器作用下车辆队列系统的特征方程,提出了基于该控制器的最右侧极点配置方法 .在此基础上,使用劳斯判据和严格的导数分析,证明了最右侧极点不可任意配置,并推导了其可配置范围,构建了可最大化提升自主车辆队列响应速度的最右侧极点配置策略,给出了关于控制器增益的设计指导规则.仿真结果表明:相比于其他极点配置方案,所提出的最右侧极点配置方案大幅度提升了系统响应速度;对比比例-微分(Proportional-Derivative,PD)控制器和协作自适应巡航控制算法,PR控制器在抑制高频干扰方面具有显著优势,且将乘客乘坐舒适度提高了两个数量级.

基于极点配置和椭球分析的传感器故障检测

针对具有未知扰动与测量噪声的线性离散时间系统,提出了一种传感器故障检测方法.首先,将传感器故障视为增广状态,将原始系统转化为一个等效的新线性动态系统.然后,基于鲁棒观测器设计和极点配置方法构造了一个故障检测观测器,使得生成的残差能够同时满足对扰动与噪声的鲁棒性和对故障的敏感性.此外,设计了一种基于椭球分析的残差评价方法,该方法可通过判断残差是否被无故障残差椭球包含来检测故障.最后,通过一个二阶RC电路模型的仿真算例验证了所提出方法的有效性与优越性.

自适应比例–积分H_(2)滑模观测器设计

传统的龙伯格观测器的观测精度极易受到未知外部扰动的影响.为了解决这个问题,本文设计了一种基于径向基神经网络的自适应比例–积分H2滑模观测器,实现了参数不确定性和外部扰动下非线性系统的鲁棒确切估计.首先,利用径向基神经网络自适应逼近系统模型的复杂非线性项;其次,设计基于误差的线性滑模面,将比例–积分滑模项注入观测器中,使得滑模动态在有限时间内收敛于滑模面,实现对外部扰动和系统模型非线性的完全补偿;最后,基于H2次优控制和区域极点配置,提出观测器参数自整定方法.通过对单连杆机器人的仿真结果表明,该方法能够保证非线性系统具有较好的鲁棒性和自适应性.

一种三回路过载自动驾驶仪设计方法

从三回路过载驾驶仪的模型出发,给出形式统一的系统开环传函、闭环传函及闭环特征方程,然后依据闭环传函确定系统控制增益与闭环极点、开环截止频率的关系。通过引入舵偏角速度约束、开环截止频率约束、稳定裕度指标约束及高频部件约束,进而给出最小化闭环系统等效时间常数的目标函数。形成典型的约束条件下参数寻优范式,通过求解系统最优解,实现系统开环截止频率、相位裕度的精确设计,形成一种可工程化的极点配置设计方法,算例检验了方法的有效性。

超空泡航行器极点配置变结构控制方法研究

超空泡航行器在航行过程中,尾部会周期性拍打空泡壁而表现出强烈的“尾拍”现象,尾部空泡是由空化器经历的历史位置形成,呈现强烈的时滞特性,动力学建模和稳定控制是制约其发展的核心难题;针对泡体耦合问题,建立了空泡/刚体相对几何关系一体化实时解算的动力学模型;针对后体非线性特性,采用分段线性化方法,在保留后体尾拍非线性特性的基础上,建立了面向控制的简化模型;为了解决超空泡航行器非线性时滞控制问题,针对弹体运动极其敏感、操纵效率高等特点,采用极点配置的方式将控制模型配置到理想状态;针对尾拍过程非线性和不确定极大的特点,建立了面向扰动的变结构控制器,实现超空泡航行器扰动运动控制;采用极点配置变结构控制方法,分别设计了滚转通道和俯仰通道控制律;利用泡体耦合动力学模型进行6 DOF控制闭环轨迹仿真,稳定巡航过程中深度控制误差小于0.1 m,滚转角控制误差小于4°,表明该控制方法能够对航行器滚转角和深度实现稳定控制,控制效果较好,能够满足超空泡航行器航行要求。

基于熵值修正G2法的改进多指标河流健康评价

河流健康评价是合理开发、利用、管理、保护河流资源与环境的前提与依据。随着中国国情与水情发展,对河流健康的科学评价方法有待进一步完善。在已有研究基础上,新增文化建设程度和岸线植被保有指数两项指标,运用熵值G2赋权法计算指标权重,完善了河流健康评价指标体系,并以浙江松阴溪流域为例进行河流健康评价。结果表明:准则层权重排序为社会服务>生物>“水”>“盆”;松阴溪流域总体属于“健康”水平;影响河流健康的主要制约因子包括水资源的过度开发利用、水污染排放等;从严格管控河流岸线开发利用、加强水生生物多样性保护力度和合理提高河流防洪能力3个方面,提出了河流健康管理和生态修复的对策建议。

On the Role of Zeros in the Pole Assignment of Scalar High-Order Fully Actuated Linear Systems

It is well known that for a linear system in state space form,controllability is equivalent to arbitrary pole assignment by state feedback.This brief points out that for a scalar high-order fully actuated linear system,the pole assignment problem is solvable if and only if the desired pole set of the closed-loop system should not include the zero set of the open-loop system if the implementation issue of the controller is taken into account,that is,controllability cannot guarantee arbitrary pole assignment by state feedback.

基于Gridsearch-SVM梯形区域极点分类的故障诊断

针对一类线性定常系统,基于梯形区域极点配置,给出了执行器部件故障诊断的一种方法。首先,利用极点观测器,通过测量系统的状态,得到极点的动态信息;其次,根据模拟各通道执行器故障,实时采集闭环系统的极点信息,形成极点分类数据库;最后,利用支持向量机算法(Support Vector Machine,SVM)根据不同通道发生故障时极点所处位置不同,设计极点分类器,对极点进行分类,实现对系统的故障诊断。针对SVM中惩罚因子和核宽度系数需要依靠先验知识的缺陷,采用Grid search优化其参数,缩小寻优范围。仿真结果表明设计方案的可行性以及故障诊断的有效性。

一种抑制共振模态影响的伺服系统控制器设计新方法

伺服控制系统的控制性能会受到机械共振的影响,导致实际应用时控制器参数需要进行额外的调整。为了提高PID参数设计的准确性,减小共振模态对控制系统的影响,在设计伺服系统位置环控制器前,建立共振模态的数学模型,并将共振模态看成伺服系统位置环被控对象的一部分。然后,根据已包含了共振模态的被控对象的数学模型来设计伺服系统的二自由度控制器,其中前馈控制器通过不变性原理设计,反馈控制器通过提出的五阶极点配置的方法进行设计。结果表明:提出的伺服系统设计新方法能够有效提高控制系统的性能,减小机械共振的影响。因此,对于已知共振模态的伺服控制系统,该设计方法得到的控制器参数更加适用,能有效减小实际调试的难度。

THE POLE ASSIGNMENT OF LINEAR SYSTEMS

In this paper the pole assignment problem of a time invariant linear control system issolved by using the Wu Elimination Method.In general,the questions are classified into(i)the poleassignment by using state feedback,(ii)the pole assignment by using output feedback,(iii)the poleassignment via dynamic compensator.The key point of all these problems is to solve a certaincorresponding system of polynomial equations.Based on algebraic geometry,the Wu methodprovides a mechanical algorithm for solving the system of polynomial equations.Therefore,a unifieddefinite algorithm for solving all these problems is given in this paper.During the procedure ofelimination,the unknowns are automatically separated into parameters and apparent variables.Thus,the freedom of the corresponding feedback can be defined as the number of parameters.Meanwhile,the explicit expressions of the apparent variables depending on the parameters areobtained.

Pole assignment for stochastic systems with unknown coefficients

This paper solves the exact pole assignment problem for the single-input stochastic systems with unknown coefficients under the controllability assumption which is necessary and sufficient for the arbitrary pole assignment for systems with known coefficients. The system noise is required to be mutually independent with zero mean and bounded second moment. Two approaches to solving the problem are proposed: One is the iterative learning approach which can be applied when the state at a fixed time can be repeatedly observed with different feedback gains; the other is the adaptive control approach which works when the trajectories satisfy a nondegeneracy condition. Both methods are essentially based on stochastic approximation, and the feedback gains are recursively given without invoking the certainty-equivalency-principle.

A new algorithm for pole assignment of single-input linear systems using state feedback

In this paper we present a new algorithm for the single-input pole assignment problem using state feedback. This algorithm is based on the Schur decomposition of the closed-loop system matrix, and the numerically stable unitary transformations are used whenever possible, and hence it is numerically reliable.The good numerical behavior of this algorithm is also illustrated by numerical examples.