不确定跳变系统鲁棒L 2-L ∞滤波

针对既有连续时间演化,又含Markov事件驱动的一类混杂动态跳变系统,研究L2-L∞性能指标下的鲁棒滤波问题,只要系统遭受的外部干扰是能量有界的,便可保证一定的预设滤波误差峰值水平.在有限时间域内定义L2-L∞增益,利用随机稳定性分析获得了若干主要结果.鲁棒滤波器的分析和设计,不仅考虑了各模态下凸多面体形式描述的动态系统参数不确定性,更考虑了各模态间跳变转移概率的不确定性,使得滤波器对模态跳变机理具备了一定的鲁棒性.鲁棒滤波器的存在条件及设计方法可直接利用耦合线性矩阵不等式.最后用数值示例对结果进行了验证.     

不确定系统具有圆盘区域极点约束的鲁棒控制

对一类不确定线性系统,提出了存在状态反馈控制律,使得闭环系统的所有极点均位 于一给定圆盘中的一个充分必要条件.结合控制律反馈增益参数极小化的要求,建立了一个具 有线性矩阵不等式约束的凸优化问题,通过该问题的解,可以构造一个具有较小反馈增益参数 和给定要求的控制律.所提出的方法既可应用到连续系统,也可应用到离散系统.     

基于扩张观测器的欠驱动船舶轨迹跟踪低频学习自适应动态面输出反馈控制

针对速度不可测的三自由度欠驱动船舶轨迹跟踪控制问题,考虑船舶存在模型参数不确定项以及外界环境干扰未知情况,提出一种基于扩张观测器的欠驱动船舶轨迹跟踪低频学习自适应动态面输出反馈控制策略.该策略构造扩张观测器估计船舶速度向量,利用神经网络算法逼近模型参数不确定项,然后采用动态面控制技术避免对虚拟控制律直接求导,简化控制律计算过程,并引入低频增益学习技术消除外界扰动导致控制信号产生高频振荡,最后选取李雅普诺夫函数证明该控制律能够保证船舶跟踪闭环系统中所有误差信号一致最终有界.仿真结果表明,本文所设计控制器对船舶模型参数不确定项及外界环境干扰具有较强的鲁棒性,能够实现对船舶轨迹的有效跟踪.     

基于离散时变趋近律的准滑模控制

针对不确定离散时间系统,提出一种基于离散时变趋近律的准滑模控制方法.该方法不仅能够加快系统趋近模态的趋近速度,缩短到达时间,而且能够减小准滑动模态带宽,有效改善系统动态品质,增强系统鲁棒性,并无控制抖振和稳态抖振产生.控制律形式简单、利于实现.仿真结果表明了所提出方法的有效性.     

不确定跳变系统反馈预测控制

针对一类受限不确定离散Markov跳变系统,提出一种反馈预测控制器设计方法.为便于工程应用,该方法考虑了各模态下的动态系统参数存在多胞不确定性,以及各模态间的跳变转移概率部分未知的情形.通过优化无穷时域的二次型性能指标来确定预测控制器及其对应的椭圆不变集,控制器保证了闭环系统鲁棒均方稳定.同时,用所求得的控制增益在线构造了一组渐近稳定的多面体不变集,在一定程度上扩大了系统状态可行集的范围.数值示例验证了所提方法的可行性和有效性.     

具有参数不确定性的非线性系统的鲁棒输出跟踪

研究具有非线性参数化的非线性系统的输出跟踪问题.采用时变状态反馈控制律, 指数镇定输出跟踪误差,并保证非线性系统的所有状态是有界的.为了实现时变状态反馈控 制律,设计高增益鲁棒观测器观测构造该控制律所需要的状态,使得整个闭环系统的输出能 渐近跟踪期望输出,且该闭环系统中所有信号都是有界的.     

不确定离散半马尔可夫跳变系统的有限时间鲁棒$H_infty$控制

研究一类不确定离散时间半马尔可夫跳变系统的有限时间鲁棒H_∞控制问题.首先,应用半马尔可夫核方法建模离散时间系统的半马尔可夫跳变过程,其中驻留时间的概率密度函数依赖系统当前模态和下一模态,使得所提出理论可考虑不同的驻留时间概率分布类型,针对随机跳变系统有限时间分析中的跳变次数问题,提出估计跳变次数最大值的方法;然后,考虑系统模态驻留时间的上下界,提出新的有限时间有界概念,并保证基于半马尔可夫核方法给出的不确定离散时间半马尔可夫随机跳变系统有限时间有界判据数值可解;接着,在此基础上,分析系统的H_∞性能指标,设计模态依赖的状态反馈控制律保证闭环系统的有限时间鲁棒H_∞性能;最后,通过2个算例仿真验证所提出理论的可行性和有效性.     

挠性卫星姿态跟踪自适应L2增益控制

针对在轨挠性卫星姿态跟踪时存在参数不确定、外部干扰以及控制输入受限等问题,提出了一种自适应L2增益控制方法.首先利用神经网络来逼近系统中的未知非线性动态特性,设计自适应控制律来处理系统中的不确定参数:其次设计了一鲁棒控制器使得干扰力矩对系统性能输出具有L2增益,从而实现对干扰的抑制控制.最后通过引入附加的输入误差系统,...     

时变时滞不确定系统的鲁棒输出反馈控制

研究了时变时滞不确定系统基于状态观测器的动态输出反馈实现鲁棒镇定的分 析和综合问题.所研究的系统不仅同时包含时变状态时滞和时变控制时滞,而且包含时变未 知且有界不确定参数.提出了确保该系统可通过输出反馈鲁棒镇定的充分条件,并将该充分 条件转化为线性矩阵不等式(LMI)问题,最终通过求解两个LMI来构造输出反馈控制律.     

Markov跳变系统的输出反馈鲁棒预测控制

对离散时间Markov跳变系统, 当系统状态不完全可测时, 研究了一类基于输出反馈的鲁棒模型预测控制问题. 所研究系统为准线性参数时变的, 考虑在当前时刻系统的时变参数是已知的, 将来时刻未知的情况. 综合考虑系统存在多胞不确定性和有界噪声等因素, 通过运用线性矩阵不等式方法及变量变换思想, 将无穷时域性能指标的最小最大鲁棒预测控制问题转化为具有线性矩阵不等式约束的凸优化问题, 得到了系统的输出反馈控制律. 引入二次有界概念, 在满足输入输出约束的情况下, 保证闭环系统的随机稳定性. 数值算例验证了方法的有效性.     

线性不确定时滞系统的时滞依赖鲁棒镇定方法研究

研究一类同时存在状态和控制滞后的线性不确定时滞系统的鲁棒镇定问题。系统的不确定项参数时为未知但范数有界,其滞后项也时时变的。对此,给出一个使得系统鲁棒稳定的无记忆状态反馈控制律,所得结果与时滞相关,且相应的结果以线性矩阵不等式的形式给出。     

Robust control through piecewise Lyapunov functions for discrete time-varying uncertain systems

This paper is concerned with the robust stabilization by state feedback of a linear discrete-time system with time-varying uncertain parameters. An optimization problem involving a set of linear matrix inequalities and scaling parameters provides both the robust feedback gain and the piecewise Lyapunov function used to ensure the closed-loop stability. In the case of linear time-varying systems involving the convex combination of two matrices, only two scaling parameters constrained into the interval [0,?1] are needed, allowing a simple numerical solution as illustrated by means of examples.     

Robust stabilization of uncertain systems with time-varyingmultistate delay

The authors deal with the problem of stabilizing a class of uncertain linear systems with time-varying multi-state delay and subject to norm-bounded parameter uncertainty via memoryless linear state feedback. Some sufficient conditions for the robust stabilizability are derived fur this class of uncertain systems. If there exists a positive-definite symmetric solution satisfying the algebraic Riccati equation (or inequality), a suitable memoryless state feedback law can be derived also. Moreover, all such parametric algebraic Riccati inequalities have been transformed into some linear matrix inequality problems, so there is no tuning of the parameters to gain a stabilizing solution     

一类不确定动态时滞系统的无记忆鲁棒镇定控制

针对状态和控制均存在滞后,同时具有未知且有界的一类时变不确定线性时滞系 统,提出了一种无记忆鲁棒镇定控制器设计算法.给出了闭环系统二次稳定的充分条件,并利 用一等价线性时不变系统的H∞标准问题综合方法来构造出所需的线性状态反馈控制律,即 可通过求解一代数Riccati型方程来求得控制律静态增益阵,从而保证了解的存在性和可解 性.     

Control of Markovian jump discrete-time systems with norm boundeduncertainty and unknown delay

This paper studies the problem of control for discrete time delay linear systems with Markovian jump parameters. The system under consideration is subjected to both time-varying norm-bounded parameter uncertainty and unknown time delay in the state, and Markovian jump parameters in all system matrices. We address the problem of robust state feedback control in which both robust stochastic stability and a prescribed H_∞ performance are required to be achieved irrespective of the uncertainty and time delay. It is shown that the above problem can be solved if a set of coupled linear matrix inequalities has a solution     

基于线性矩阵不等式的分散鲁棒跟踪控制器设计

应用线性矩阵不等式（ＬＭＩ）方法研究不确定性关联大系统的分散鲁棒输出跟踪控制问题。系统中不确定项具有数值界,可不满足匹配条件。基于不确定基项的表达形式,给出了存在分散控制鲁棒跟踪控制器的ＬＭＩ条件。在此基础上,通过建立求解受ＬＭＩｓ约束的凸优化问题,提出了具有较小反馈增益ＬＭＩ设计方法,使受控系统渐近跟踪给定的参考输入。ＬＭＩ方法求解简单,最后用示例说明了该方法的应用。     

Synthesis of adaptive gain robust model-following/tracking controllers for a class of uncertain linear systems

This paper proposes a new adaptive gain robust model-following/tracking controller for a class of uncertain linear systems. The proposed adaptive gain robust controller is composed of state feedback laws with fixed gains, feedfoward inputs for the reference model and nonlinear compensation inputs with adjustable time-varying parameters. Moreover, the proposed control strategy can achieve good transient performance and avoid the excessive control input by means of the design parameter. In this paper, linear matrix inequality-based sufficient conditions for the existence of the proposed adaptive gain controller are given, and two design strategies are presented. Finally, simple illustrative examples are included to show the effectiveness of the proposed adaptive gain robust controller.     

Robust near-optimal output feedback control of non-linear systems

This work proposes a robust near-optimal non-linear output feedback controller design for a broad class of non-linear systems with time-varying bounded uncertain variables. Both vanishing and non-vanishing uncertainties are considered. Under the assumptions of input-to-state stable (ISS) inverse dynamics and vanishing uncertainty, a robust dynamic output feedback controller is constructed through combination of a high-gain observer with a robust optimal state feedback controller synthesized via Lyapunov's direct method and the inverse optimal approach. The controller enforces exponential stability and robust asymptotic output tracking with arbitrary degree of attenuation of the effect of the uncertain variables on the output of the closed-loop system, for initial conditions and uncertainty in arbitrarily large compact sets, provided that the observer gain is sufficiently large. Utilizing the inverse optimal control approach and singular perturbation techniques, the controller is shown to be near-optimal in the sense that its performance can be made arbitrarily close to the optimal performance of the robust optimal state feedback controller on the infinite time-interval by selecting the observer gain to be sufficiently large. For systems with non-vanishing uncertainties, the same controller is shown to ensure boundedness of the states, uncertainty attenuation and near-optimality on a finite time-interval. The developed controller is successfully applied to a chemical reactor example.     

Robust non-fragile guaranteed cost control of uncertain large-scale systems with time-delays in subsystem interconnections

In this paper, the robust non-fragile guaranteed cost-control problem is studied for a class of uncertain linear large-scale systems with time-delays in subsystem interconnections and given quadratic cost functions. The uncertainty in the system is assumed to be norm-bounded and time-varying. Also, the state-feedback gains for subsystems of the large-scale system are assumed to have norm-bounded controller gain variations. The problem is to design a state feedback control law such that the closed-loop system is asymptotically stable, and the closed-loop cost function value is not more than a specified upper bound for all admissible uncertainties. Sufficient conditions for the existence of such controllers are derived based on the linear matrix inequality (LMI) approach combined with the Lyapunov method. A parameterized characterization of the robust non-fragile guaranteed cost controllers is given in terms of the feasible solutions to a certain LMI. A numerical example is given to illustrate the proposed method.     

Adaptive robust tracking and model following of uncertain dynamical systems with multiple time delays

The problem of robust tracking and model following is considered for a class of linear systems with multiple delayed state perturbations, time-varying uncertain parameters, and disturbance. In this note, it is assumed that the upper bounds of the delayed state perturbations, uncertainties, and external disturbances, are unknown. An improved adaptation law with /spl sigma/-modification is proposed to estimate such unknown bounds, and on the basis of the updated values of these unknown bounds, a class of continuous memoryless state feedback controllers is constructed for robust tracking of dynamical signals. The proposed adaptive robust tracking controller can guarantee that the tracking error decreases asymptotically to zero in the presence of multiple delayed state perturbations, time-varying uncertain parameters, and disturbance. In addition, it is also shown that this improved adaptation law with /spl sigma/-modification can be applied to the general adaptive control problems to obtain some more exact control results. Finally, a numerical example is given to demonstrate the validity of the results.