切换非线性系统采样控制的研究现状与进展

切换非线性系统由于其广泛的工程应用背景以及重要的理论研究价值引起各行业学者的广泛关注.近年来,随着计算机技术的快速发展,切换非线性系统采样控制问题成为研究热点.对目前切换非线性系统采样控制领域的研究现状进行综述.首先介绍了切换非线性系统的基本问题,并梳理了切换非线性系统几个常用控制方法的基本思想.然后从时间触发采样控制和事件触发采样控制两个方面对切换非线性系统采样控制的国内外研究现状进行了论述.最后进行了总结并提出切换非线性系统采样控制领域未来值得关注的研究方向.     

双率系统极点配置自校正控制算法

针对控制输入频率是输出采样频率整数倍的双率系统,研究了极点配置自校正控制方法.由于双率采样数据系统存在未知的采样间输出(即损失输出),所以传统输入输出等周期单率系统极点配置自校正控制方法不适用于双率系统.为了解决这一困难,本文直接利用双率输入输出数据估算系统模型参数和采样间输出,进一步把估计的模型参数代入极点配置方程,通过求解多项式Diophantine方程.推导了被控系统控制律,给出了双率极点配置自校正控制算法.一个仿真例子说明双率系统极点配置算法的控制效果.     

一类非线性多自主体系统的实用脉冲一致性

针对一类非线性多自主体系统,研究基于实用脉冲控制的一致性协议设计问题.引入脉冲调制间歇控制策略,利用峰值很大,持续时间很短的信号代替理想脉冲信号,设计实用脉冲一致性协议.首先给出一类连续―间歇型实用脉冲协议.利用李雅普诺夫函数方法,图论和间歇控制理论,证明了在该协议下,多自主体系统可以实现渐近一致性.在连续—间歇型实用脉冲协议实施中,需在控制作用区间连续量测自主体状态.针对此局限,提出了采样―间歇型实用脉冲协议.通过采样和间歇控制理论,建立了多自主体系统实现渐近一致性的充分条件.进一步地,分析了当控制作用区间等于采样周期时,采样—间歇型实用脉冲协议退化为周期采样控制协议,而当控制作用区间趋于0时,其退化为脉冲控制协议.揭示了所提出的采样―间歇型实用脉冲协议同周期采样控制协议,脉冲控制协议之间的关系.     

含有采样反馈的二连杆系统稳定性

当今主流的控制方法大都基于采样反馈得到的离散的状态量从而进行控制参数设计,然而对于采样反馈本身对系统的影响鲜有研究.本文以采样比例-微分控制反馈作用下的二连杆系统为研究对象,研究了采样周期对于混杂系统稳定性的影响.首先,通过数值模拟,发现了二连杆非线性混杂系统可以通过近似线性系统进行定性表征;其次,构造了状态量的离散映射,以反映二连杆混杂系统在目标位置附近的动态响应;最后,提出了二连杆混杂系统的稳定性判据,并以数值仿真的结果验证了判据的准确性.     

非线性时变时延系统的模糊采样最优控制

针对非线性时变时延系统,采用输入时延和自由权重矩阵方法研究模糊采样最优控制问题.应用T-S模糊系统表征非线性系统,控制器是零阶保持采样信号.由线性矩阵不等式给出最优控制准则,所设计的模糊采样控制器在闭环系统渐近稳定意义下可保证期望最优控制性能.最后,通过卡车拖车系统实验验证模糊采样控制设计方案的可行性.     

采样非线性系统的动态神经网络稳定自适应控制

研究了一类采样数据非线性系统的动态神经网络稳定自适应控制方法.不同于静态 神经网络自适应控制,动态神经网络自适应控制中神经网络用于逼近整个采样数据非线性系 统,而不是动态系统中的非线性分量.系统的控制律由神经网络系统的动态逆、自适应补偿项 和神经变结构鲁棒控制项组成.神经变结构控制用于保证系统的全局稳定性,并加速动态神 经网络系统的适近速度.证明了动态神经网络自适应控制系统的稳定性,并得到了动态神经 网络系统的学习算法.仿真研究表明,基于动态神经网络的非线性系统稳定自适应控制方法 较基于静态神经网络的自适应方法具有更好的性能.     

非线性系统的鲁棒采样控制

研究在汽车转向控制中遇到的、具有输出约束的一类非线性不确定系统的鲁棒采样 控制和鲁棒采样最优控制问题,结果表示为一些矩阵不等式.最后基于线性矩阵不等式,给出 了一个迭代算法和算例.数值计算实例证明了该算法的有效性.     

非线性采样控制系统的稳定性

1　引言采样控制系统是一类典型的混杂系统 ,它是由非线性连续时间对象和数字控制器耦合而成 .其对象可用一阶微分方程描述 ,而控制器可用一阶差分方程描述 .对这类系统的研究引起了广泛的兴趣 .文献 [1～ 4]分别研究了关于状态 ,控制为线性或关于控制为线性的系统的定性性质 ,     

非均匀采样数据系统的新型模型描述方法

提升技术是处理非均匀采样数据（Non-uniformly sampled-data,NUSD）系统的标准工具.然而,提升状态空间模型存在因果约束问题,相应的提升传递函数模型结构复杂,且参数数目过多.因此,它们不便于非均匀采样数据系统的辨识与控制.通过引入时变后移算子,本文提出了一种输入输出表达的新型模型描述方法.该模型能够克服提升系统模型的缺点,使得传统单率系统的辨识和控制方法能够推广到非均匀采样数据系统中.仿真结果表明了新模型的优越性和有效性.     

计算机控制系统中采样周期的确定

计算机控制是一种采样离散控制,它是根据采样时刻的输入量来计算控制量.因此,采样周期在计算机控制系统中是一个重要参数,会对系统会产生多方面的影响,合理的选择采样周期就非常重要.     

非线性系统的鲁棒采样最优控制

采样系统控制作为一种数字控制的直接设计方法,近年来引起了广泛的重视,另一方面系统的时域约束在工业控制中是不可避免的。利用实用稳定性理论,研究了具有输出约束的一类非线性系统的鲁棒采样最优控制问题,结果表示为一些矩阵不等式,最后给了出了一个迭代算法。     

Constrained robust sampled‐data control for nonlinear uncertain systems

In industrial process control, computer control, which makes the closed‐loop system a sampled‐data one containing both continuous‐ and discrete‐time signals, is widely used. In contrast with traditional approximation methods, sampled‐data synthesis, a direct digital controller design procedure without approximation, has received increasing attention during the past few years. However, many of the existing results cannot be applied to sampled‐data control design for the uncertain systems. In this paper, a result of robust asymptotic stability of sampled‐data systems with constraints on the state is presented based on a result on practical stability for these systems. Then the robust sampled‐data control for a class of uncertain nonlinear systems with constraints on the output is developed. The problem is formulated from vehicle steering control with constraint on the side slip angle of body. The result is described by some matrix inequalities which could be solved by an iterative algorithm based on the linear matrix inequality technique. Finally, a numerical example is presented to demonstrate the result. Copyright © 2002 John Wiley & Sons, Ltd.     

Co-states for sliding mode design in linear systems

A control design for linear systems with uncertainties is presented where a particular time-varying sliding mode manifold is specified utilizing co-states of the plant. We introduce design methods for both continuous time and sampled data systems. It is shown that robustness of the closed-loop systems with continuous time control degrades when an equivalent sampled data control is used.     

Stability condition for sampled data based control of linear continuous switched systems

Most practical systems are continuous in nature but with discrete (sampled) feedback when digital control is utilized. This paper investigates the stabilization problem of switched linear continuous-time systems with sampled data based control. For both known and unknown arbitrary switching processes, on the basis of Lyapunov stability theory, a sufficient global exponential stability condition related to Dwell time and sampling period is established. For the latter case, on-line one-step adaptive estimation algorithm is derived and integrated with sampled feedback for control design. Validation and verification of the established result are conducted through cruise control of train systems.     

不确定时滞线性系统的采样控制

采样控制作为一种数字控制的直接设计方法,近年来引起了广泛的重视,目前采样控制不易处理模型的不确定性和时滞,本语文给不确定时滞系统的采样控制算法,结果表示为一些矩阵不等式,并给中用ＬＭＩ求解的迭代算法。     

Global decentralized sampled‐data output feedback stabilization for a class of large‐scale nonlinear systems with sensor and actuator failures

In this paper, we investigate global decentralized sampled‐data output feedback stabilization problem for a class of large‐scale nonlinear systems with time‐varying sensor and actuator failures. The considered systems include unknown time‐varying control coefficients and inherently nonlinear terms. Firstly, coordinate transformations are introduced with suitable scaling gains. Next, a reduced‐order observer is designed to estimate unmeasured states. Then, a decentralized sampled‐data fault‐tolerant control scheme is developed with an allowable sampling period. By constructing an appropriate Lyapunov function, it can be shown that all states of the resulting closed‐loop system are globally uniformly ultimately bounded. Finally, the validity of the proposed control approach is verified by using two examples.     

An impulsive‐switched‐system approach to aperiodic sampled‐data systems with time‐delay control

This paper devotes to the stability of aperiodic sampled‐data systems with time‐delay control, where the delays can impose a positive effect on the stability of the systems. The systems are modeled as impulsive switched systems with fixed switching laws. A novel separation theorem is presented to determine the Schur property of a matrix product and then used to obtain a less conservative stability criterion for the impulsive switched systems with fixed switching laws. By the separation theorem and a loop‐functional approach, some new stability and stabilization criteria for aperiodic sampled‐data systems with time‐delay control are provided in terms of linear matrix inequalities. Finally, the stability and stabilization results are tested on some classical numerical examples to illustrate the efficiency of the proposed method.     

Network‐based H∞ control for stochastic systems

This paper investigates the problem of network‐based control for stochastic plants. A new model of stochastic time‐delay systems is presented where both network‐induced delays and packet dropouts are taken into consideration for a sampled‐data network‐based control system. This model consists of two successive delay components in the state, and we solve the network‐based H_∞ control problem based on this model by a new stochastic delay system approach. The controller design for the sampled‐data systems is carried out in terms of linear matrix inequalities. Finally, we illustrate the methodology by applying these results to an air vehicle control problem. Copyright © 2008 John Wiley & Sons, Ltd.     

Global sampled‐data output‐feedback stabilization for nonlinear systems with unknown measurement sensitivity

This paper investigates the problem of global output‐feedback stabilization by sampled‐data control for nonlinear systems with unknown measurement sensitivity. By employing the technique of output‐feedback domination, a sampled‐data output‐feedback control law together with a sampled‐data state observer is explicitly constructed. By an exquisite selection of both the domination gain and sampling period, the resultant control law is a globally asymptotic stabilizer even in the presence of unknown measurement sensitivity. The novelty of this paper is the development of a distinct approach which can tackle the problem of output‐feedback stabilization for the nonlinear systems with unknown measurement sensitivity.