一类增长率依赖输出的非线性系统的输出反馈输出跟踪控制

研究一类增长率依赖输出非线性系统的输出反馈输出跟踪控制问题.利用系统结构特点,构造出系统实现输出跟踪时内部状态的渐近轨迹.通过建立状态与渐近轨迹偏差的动态方程,将输出跟踪问题转化为偏差系统的镇定问题,然后通过设计偏差系统的输出反馈镇定控制器给出输出反馈输出跟踪控制器.最后以仿真实例验证本文结论.     

一类不确定系统的动态输出反馈镇定

考察同时含有匹配和非匹配不确定性的一类非线性系统的输出反馈镇定问题。首先讨论仿射非线性的情形,然后讨论一类非仿射非线性情形。分别为所论系统构造了输出反馈动态补偿器,该补偿器可以实现对所论非线性不确定系统的动态输出反馈指数的镇定。     

广义系统输出反馈严格正实控制器设计

研究连续广义系统的正实控制问题。目的是设计静态输出反馈和动态输出反馈严格正实控制器使得闭环系统容许且扩展严格正实。基于广义系统严格正实引理，利用线性矩阵不等式和广义代数Riccati不等式，给出了广义系统静态输出反馈和动态输出反馈严格正实控制器存在的充要条件及设计方法。对动态输出反馈情形，给出了一个数值算例说明控制器设计方法的有效性及可行性。     

一类非线性MIMO不确定系统的动态输出反馈镇定

考察其标称系统的相对阶大于{1,1,…,1}同时含匹配和非匹配不确定性的MIMO 非线性系统的动态输出反馈镇定问题.文中直接用Lyaunov方法构造一类输出反馈动态补 偿器,该补偿器可以实现对所论非线性不确定系统的动态输出反馈渐近镇定.     

基于输出加微分反馈的广义二阶动力学系统跟踪设计

考虑了基于输出及其微分反馈的广义二阶动力学系统输出渐近跟踪设计．主要给出了如下结果： 广义二阶动力学系统基于输出及其微分反馈的特征结构配置;广义二阶动力学系统基于输出及其微分反馈的 输出渐近跟踪控制律存在的充分条件以及该控制律增益阵的完全参数化表达式．仿真结果说明本文所给出的 算法是有效的．     

广义系统在一般状态反馈下的输出稳定化

１　引言对于正常系统,输出稳定化的问题已在文［１］中得到了完满的论述;对于广义系统,文［２］首先讨论了脉冲能控情形下的输出稳定化问题;文［３］利用ＭＰＤ反馈,讨论了广义系统的输出稳定化问题,但此种反馈由于含有状态的导数,故对噪声有很大的放大作用;文［４］讨论了通过一般状态反馈的输出稳定化问题,但没有考虑闭环系统的正则性,这就是说,闭环系统解的唯一性不能保证,所以对一般状态反馈下广义系统的输出稳定化问题远没有得到解决．本文对广义系统,利用几何方法,通过一般状态反馈,保证闭环系统正则,在容许初值条件…     

基于双增益方法的不确定非线性系统的输出反馈调节问题

研究一类具有多种不确定性的非线性系统的全局输出反馈调节问题.所研究系统的一个显著特点是非线性项被未知增长率和多项式形式的输出函数的乘积界定,难点是在输出受不确定参数摄动的情况下如何抑制非线性项.提出一种改进的双增益方法来设计输出反馈控制器,可以确保闭环系统所有信号全局一致有界并且原系统状态收敛到零.最后,采用质量弹簧机械系统的输出反馈镇定问题来说明控制策略的有效性.     

一类线性不可观非线性系统的动态输出反馈镇定

本文研究一类不可观非线性系统的动态输出反馈镇定,基于逼近渐近稳定性的概念,给出了动态输出反馈可镇定的充分条件,本文主要结果的直接推论是零动太逼近渐近稳定的最小相位系统能用动态输出反馈镇定,本文的方法也能处理非最小相位系统。     

离散时间部分状态反馈模型参考自适应控制

本文针对线性不确定性系统, 给出了部分状态反馈直接模型参考自适应控制设计方案以及详细的系统稳 定性、输出跟踪性能分析. 控制器设计基于降维观测器和参数化方法. 此方案采用反馈控制, 反馈信号不仅仅依赖 全状态信息或者输出信号, 而是任意不超过系统维数的可测信号. 因此, 部分状态反馈控制是包含状态反馈、输出 反馈控制的新的控制方案, 缓解了状态反馈对状态信息的限制, 降低了输出反馈控制结构的复杂性. 通过引入辅助 信号, 本文证明了输出匹配条件的存在性、所有闭环系统信号的有界性以及渐近输出跟踪性能. 仿真结果验证了该 方案的有效性.     

时滞系统基于离散GM(1,2,τd)模型的新型控制算法

本文采用系统的输出反馈,通过引进趋近律,提出了一种基于离散GM(1,2,τd)模型的分数时滞系统的滑模控制(SME)算法。在设计控制器时,仅仅利用了系统的输出反馈而非系统的状态反馈,故该算法既实用,又易于实现。     

一类欠驱动机械系统的全局鲁棒控制

针对具有质心参数不确定性的Acrobot系统,提出一种全局的鲁棒控制方法.首先,给出系统具有质心参数不确定的系统模型;其次在摇起区,分析系统不确定性条件下的能量变化情况,基于能量不断增加的思想设计出摇起控制器;在平衡区,把系统的不确定性转化为模型状态矩阵的不确定性,引入H标准设计方法,得出存在H状态反馈控制器的充要条件,通过求解线性矩阵不等式使系统有效地克服不确定性的影响实现二次稳定;最后通过仿真实验验证了所提方法的有效性.     

非线性系统基于HM模型的自适应鲁棒跟踪控制

研究了非线性系统的跟踪控制问题，基于HM模型对非线性系统进行描述，并将全局模糊模型表示成不确定系统形式。在满足匹配条件下，针对未知不确定界，采用自适应鲁棒控制器，利用自适应变量信息来补偿系统的不确定性信息，实现了非线性系统的渐近跟踪控制。一级倒立摆仿真实验，验证了方案的有效性。控制器结构简单，规则少，具有应用价值。     

不确定未知界的相似组合系统分散自适应输出反馈控制

研究一类具有加性振动的不确定相似组合大系统的分散自适应输出反馈镇定问题,给出了该系统输出反馈镇定的条件。受控系统的不确定项可以是非线性的或时变的,输入通道不确定性满足一般限制,系统的不确定项的界是存在的但却是未知的。所设计的确定性非线性控制器能保证受控系统渐近收敛于系统的平衡点,并且自适应律保持有界。最后进行了仿真研究,表明所得结论是正确脯效的。     

Exponential stability of singularly perturbed systems with time delay and uncertainties

Recently, there are several studies on singularly perturbed systems with time delay and uncertainties. However, the existing results show only the limited results on either time delay or uncertainties. For time delay, small time delay or time delay only on the slow state are considered while, for uncertainties, the uncertain linear singularly perturbed system or the uncertain nonlinear singularly perturbed system with the conservative condition on uncertainties are considered. In this paper, the exponential stability of singularly perturbed systems with both time delay and uncertainties is investigated in the general form.     

On active disturbance rejection control for nonlinear systems with multiple uncertainties and nonlinear measurement

The paper proposes a novel control design for nonlinear systems with multiple uncertainties and nonlinear measurement. The output linearization is utilized to handle the nonlinearities in system dynamics and measurement. Firstly, the integrator chain for nonlinear systems with multiple uncertainties is analyzed. Based on the fundamental integrator chain form, the equivalent total effect of multiple uncertainties is summarized as total disturbance. By timely estimating and compensating for the total disturbance, an active disturbance rejection control design to handle both multiple uncertainties and nonlinear measurement is proposed. Moreover, the transient performance of the corresponding closed‐loop system is rigorously studied, which theoretically reveals the high consistence of the tracking performance despite various multiple uncertainties.     

Propagation of uncertainties in deterministic systems

This paper addresses the propagation of uncertainties in deterministic systems, i.e. the system definition is known but the system parameters and input to the system contain uncertain information. The effect of the uncertain information on the system response is to be assessed. Three models of uncertainties corresponding to differing degrees of knowledge about the uncertainty are considered: interval, fuzzy and random. A method to propagate uncertainties expressed as intervals is described; the method, called the Vertex method, is based on a generalization of combinatorial interval analysis techniques. It is shown how the Vertex method can be extended naturally to treat the propagation of uncertainties modeled as fuzzy sets. Finally, propagation of random uncertainties is described using the classical probabilistic technique of derived distribution functions. The computational implications of the three models of uncertainties and the corresponding methods of propagation are contrasted. It is suggested that when the available information is too crude to support a random definition, the interval or fuzzy model should be used to take advantage of the expediency with which interval and fuzzy uncertainties can be propagated and processed.     

Servo controller design using neural networks

The dynamics of a physical plant may be difficult to express as concise mathematical equations. In practice there exist uncertainties that cannot be modeled with the system equations. Hence, robustness against system uncertainties is essential in a control system design. In this article, multilayered neural networks (MNNs) are used to compensate for model uncertainties of a dynamical system. Neural network models are used along with a classical linear servo controller derived from the linear state space equations. These models are trained so that system uncertainties are compensated. The design of a servo system indicates the enhanced performance of the neural-network-based servo controller as compared to the classical servo controller.     

Decentralized robust controller design for a class ofinterconnected uncertain systems: with unknown bound of uncertainty

In this paper, a simple decentralized robust control scheme is proposed for a class of interconnected time-varying systems with uncertainties. The uncertainties may appear in the interconnections between the subsystems and also within the subsystems, and they are possibly nonlinear and time-varying. The uncertainties are bounded, but the bounds of the uncertainties are unknown in controller design. When certain matching conditions are satisfied for the uncertain interconnections and the uncertainties within the subsystems, the proposed decentralized control scheme guarantees the controlled system to converge exponentially with a prescribed degree toward the equilibrium of the system, or a residual ball around the equilibrium     

Robust dichotomy of the Lur'e system with structured uncertainties

This paper is concerned with the problem of robust dichotomy of a Lur'e system with norm constraint structured uncertainties, which represent numerous kinds of uncertainties, including mixed real/complex dynamic uncertainties. Leonov's frequency-domain dichotomy condition for Lur'e systems is generalized to the situation where the linear part of the system includes structured uncertainties. By applying the structured singular value of an operator to structured uncertainty, the results on robust dichotomy analysis of the Lur'e system are obtained. Finally a numerical example is included to demonstrate the validity and the applicability of the proposed approach.     

飞行制导控制一体化设计方法综述

从系统模型和控制设计方法两个方面综述了飞行器制导控制一体化设计方法的研究现状. 论述了制导控制一体化设计中的关键问题, 即系统具有较高的阶数和系统存在大量不确定性. 提出了基于自抗扰控制的三维制导控制一体化设计方法. 该控制方法具有简明的线性结构, 并且可以对飞行控制系统中的非线性时变不确定性进行实时估计和补偿. 仿真结果表明该方法可以对付大范围的不确定性, 具有很好的鲁棒性.