基于自适应模糊滑模控制的主动队列管理算法

针对TCP这样大型复杂的网络系统的拥塞问题,考虑系统中存在的不确定因素是未知非线性的情况,设计了一种采用自适应模糊滑模控制理论的主动队列管理算法。该算法基于网络模型的特殊性,构造了Lyapunov-Krasovskill函数,设计了滑动模面,并基于线性矩阵不等式的方法给出该系统鲁棒渐近稳定的充分条件,所设计的自适应模糊控制律能够使系统的状态轨迹在有限时间内到达滑动模面。仿真结果表明,该算法在网络条件变化的情况下,能实现准确的跟踪目标队列长度,避免网络拥塞的发生。     

End-to-end rate-based congestion control with random loss: convergence and stability

The convergence and stability analysis for two end-to-end rate-based congestion control algorithms with unavoidable random loss in packets are presented, which can be caused by, for example, errors on wireless links. The convergence rates of these two algorithms are analyzed by linearizing them around their equilibrium points, since they are globally stable and can converge to their unique equilibrium points. Some sufficient conditions for local stability in the presence of round-trip delay are obtained based on the general Nyquist criterion of stability. The stability conditions can be considered to be more general. If random loss in the first congestion control algorithm is not considered, they reduce to the local stability conditions which have been obtained in some literatures. Furthermore, sufficient conditions for local stability of a new congestion control algorithm have also been obtained if random loss is not considered in the second congestion control algorithm.     

一类多状态时滞不确定系统的鲁棒预测控制

针对一类多状态时滞多面体不确定对象,提出了一种鲁棒预测控制算法。基于参数相关的李亚普诺夫函数,给出了系统稳定的充分条件。通过求解满足若干线性矩阵不等式条件的上界值的最优化问题,获得了约束范围内满足系统鲁棒性能的最优控制律。优化问题的可行性保证了算法的鲁棒稳定性。仿真实例证明了该算法的有效性。     

Fault-tolerant control of linear uncertain systems using H∞ robust predictive control

The robust fault-tolerant control problem of linear uncertain systems is studied. It is shown that a solution for this problem can be obtained from a H∞ robust predictive controller (RMPC) by the method of linear matrix inequality (LMI). This approach has the advantages of both H∞ control and MPC: the robustness and ability to handle constraints explicitly. The robust closed-loop stability of the linear uncertain system with input and output constraints is proven under an actuator and sensor faults condition. Finally, satisfactory results of simulation experiments verify the validity of this algorithm.     

基于不确定时滞模型的鲁棒AQM控制器设计

针对网络环境的不确定性和网络参数的时变性,采用不确定时滞系统模型对网络拥塞控制问题进行了研究。给出了利用线性矩阵不等式方法判定主动队列管理(active queue management,AQM)系统稳定的充分条件,以及基于求解非线性矩阵不等式的AQM控制器参数设计方法,设计了基于线性矩阵不等式的含时滞静态输出反馈控制器。仿真结果表明,利用该方法所得到的控制器是有效的,在变化的网络环境下,其动态响应更快,稳态波动更小。     

两类不确定奇异时滞系统鲁棒稳定的相关型判据

研究了不确定奇异时滞系统的鲁棒稳定性问题。首先以线性矩阵不等式的形式给出了奇异时滞系统正则,无脉冲模且零解渐近稳定的一种新的时滞相关型判据。通过引入新的参数避免了利用不等式处理交叉项,从而使该判据具有较小的保守性。最后,利用研究结果,给出了两类不确定奇异时滞系统新的时滞相关型鲁棒稳定性判据。     

一类Markov跳变神经网络的时滞相关鲁棒稳定性

针对一类Markov跳变神经网络,研究了其在系统参数不确定情况下的全局鲁棒稳定性。利用Leibniz Newton公式对原系统进行等价变换,基于Lyapunov 稳定性理论,并结合Moon不等式得到了此类Markov跳变神经网络时滞相关均方鲁棒稳定性的判别条件。所得结果以线性矩阵不等式(linear matrix inequality, LMI)的形式给出,容易被Matlab中的LMI工具箱验证。最后,通过一个算例验证了所得结论的有效性。     

Fault-tolerant control of linear uncertain systems using H∞ robust predictive control

The robust fault-tolerant control problem of linear uncertain systems is studied. It is shown that a solution for this problem can be obtained from a H∞ robust predictive controller （RMPC） by the method of linear matrix inequality （LMI）. This approach has the advantages of both H∞ control and MPC： the robustness and ability to handle constraints explicitly. The robust closed-loop stability of the linear uncertain system with input and output constraints is proven under an actuator and sensor faults condition. Finally, satisfactory results of simulation experiments verify the validity of this algorithm.     

AQM中基于T-S模型的滑模控制及仿真

针对TCP(Transmission Control Protocol, 传输控制协议)网络的拥塞控制问题,基于T-S (Takagi-Sugeno)模糊模型,采用滑模控制理论提出了一种新的AQM(Active Queue Management, 主动队列管理)算法.考虑到TCP网络中存在的不确定和时变时滞因素,首先利用T-S模糊模型对网络进行建模,然后利用线性矩阵不等式设计了一个渐近稳定的滑模面,而且还给出了一种能够明显减小滑模面附近抖振的趋近律,基于该趋近律设计的控制律能够有效地抑制路由器中队列长度的振荡,并使其快速收敛于期望值.仿真结果表明,该算法与普通的滑模控制算法相比具有更好的稳定性和鲁棒性,能够很好地适应复杂多变的TCP网络环境.     

时间滞后系统鲁棒控制方法及在飞控中的应用

给出了一种时间滞后系统的鲁棒控制方法。通过对系统鲁棒稳定性条件不等式的等价变形，得到了该不等式可解的条件并且大大简化了不等式；从而得到了包含复极点的时间滞后系统的鲁棒稳定性判据。针对系统具有多个时间滞后问题，运用系统单个滞后的鲁棒稳定性不等式判据，给出了包含复极点的简明鲁棒稳定性判别式。该方法接近于普通的状态反馈设计，便于工程实现。飞行器控制设计的仿真计算结果表明，采用新方法可以得到满意的设计结果。     

New results on the robust stability analysis of neural networks with discrete and distributed time delays

Delay-dependent robust stability of cellular neural networks with time-varying discrete and distributed time-varying delays is considered. Based on Lyapunov stability theory and the linear matrix inequality （LMIs） technique, delay-dependent stability criteria are derived in terms of LMIs avoiding bounding certain cross terms, which often leads to conservatism. The effectiveness of the proposed stability criteria and the improvement over the existing results are illustrated in the numerical examples.     

不确定线性时滞系统时滞相关状态反馈鲁棒镇定

利用Lyapunov-Krasovskii泛函方法,基于积分不等式,讨论了不确定线性时变时滞系统时滞相关状态反馈鲁棒镇定问题。采用线性化处理技术将非线性矩阵不等式（nonlinear matrix inequality, NLMI）转化为线性矩阵不等式（linear matrix inequality, LMI）,获得的鲁棒镇定准则只有一个易于选择的待定参数,避免了参数选择不当带来的保守性,数值例子说明本文方法的有效性。     

基于迭代学习-未知输入观测器的卫星姿控系统鲁棒故障重构

针对卫星姿控系统出现执行机构故障,提出一种基于迭代学习-未知输入观测器(iterative learning unknown input observer, IL-UIO)的鲁棒故障重构方法。首先,考虑卫星出现空间干扰力矩、模型不确定性以及陀螺漂移,建立小角度机动时的非线性姿控系统模型。其次,采用UIO干扰解耦原理和H_∞控制思想,设计IL-UIO估计卫星姿态欧拉角和角速度的同时,利用IL算法实现执行机构鲁棒故障重构。并利用Lyapunov稳定性理论证明了IL-UIO稳定性和动态故障偏差最终有界, 通过线性矩阵不等式(linear matrix inequaliry, LMI)工具箱求解了观测器部分参数矩阵。最后,建立卫星闭环姿控系统并进行仿真,仿真结果验证了此方法的有效性。     

Robust passive control for discrete-time T-S fuzzy systems with delays

This article deals with the robust stability analysis and passivity of uncertain discrete-time Takagi-Sugeno (T-S) fuzzy systems with time delays. The T-S fuzzy model with parametric uncertainties can approximate nonlinear uncertain systems at any precision. A sufficient condition on the existence of robust passive controller is established based on the Lyapunov stability theory. With the help of linear matrix inequality (LMI) method, robust passive controllers are designed so that the closed-loop system is robust stable and strictly passive.  urthermore, a convex optimization problem with LMI constraints is formulated to design robust passive controllers with the maximum dissipation rate. A numerical example illustrates the validity of the proposed method.     

T-S模糊系统的鲁棒局部稳定

研究一类不确定T-S模糊系统的鲁棒局部稳定及鲁棒局部镇定问题。首先给出T-S模糊系统局部稳定的定义,并利用一种非二次Lyapunov函数得到T-S模糊系统鲁棒局部稳定的充分条件,然后给出一种新的非PDC控制器,进而利用非二次Lyapunov函数得到基于这种非PDC控制器的局部鲁棒镇定控制器设计方法。该方法基于线性矩阵不等式(LMI),结构简单,且具有较低的保守性。仿真算例证明了所提方法的可行性。     

一类非线性中立型时滞系统的稳定性判据

考虑了一类具有非线性扰动的中立型时滞系统的鲁棒稳定性问题.系统状态的时滞是时变的.基于增广Lyapunov-Krasovskii泛函和自由权矩阵的方法,推导出保证系统在非线性扰动作用下渐近稳定的时滞依赖条件.所得到的判据以线性矩阵不等式的形式给出.由于在估计Lyapunov泛函导数上界的过程中既没有进行模型变换,也没有引入不等式放缩技术,所以得到的结果有较小的保守性.最后,通过一个数值算例验证了所提方法的有效性以及较已有工作的改进.     

基于T-S模型的非线性系统离散时间滑模控制

基于T-S模糊模型,讨论了一类非线性离散时间系统的控制问题。采用T-S模糊模型来描述非线性系统的动态模型,再将非线性系统的全局T-S模糊模型转化为线性不确定系统的模型。这样复杂的非线性系统的稳定问题就转化为线性不确定系统的鲁棒镇定问题。采用离散时间滑模控制方法实现线性不确定系统的鲁棒镇定。利用用线性矩阵不等式技术设计稳定的滑动模面,以降低非匹配不确定对系统的影响。给出了线性矩阵不等式形式的稳定滑动模面存在的充分条件。此外还给出了滑模控制律的设计方法。所给设计方法可保证系统鲁棒镇定,并且在滑动模面附近的抖振可明显减弱。最后,给出了truck-trailer的仿真算例,证明了所给方法的可行性和有效性。     

区间时滞相关不确定奇异系统的鲁棒稳定性和镇定性

研究区间时滞相关的不确定时变时滞奇异系统的鲁棒稳定性和镇定性问题,不确定参数假设是范数有界的。充分利用时滞的下界信息构造Lyapunov函数,用严格的矩阵不等式给出系统对所有的容许不确定满足正则、无脉冲、稳定的新判据。基于这个判据,设计状态反馈控制器使得系统鲁棒稳定。数值例子说明所得结果具有更小的保守性。     

变体飞行器有限时间收敛LPV鲁棒控制

以一类翼展可变的飞行器模型为对象,研究了一种针对参数不确定的线性变参数(linear parameter varying, LPV)系统的滑模变结构鲁棒控制问题。首先,通过Jacobian线性化和模型张量积转化将变体过程中的非线性模型最终简化为多胞体LPV系统。然后将鲁棒滑模控制技术拓展到此LPV模型中,给出了以线性矩阵不等式(linear matrix inequality, LMI)为形式的降阶滑动模态的存在性及鲁棒稳定性定理,以此为基础所设计的参数依赖的趋近律控制器能够使具有不匹配不确定性的LPV系统在有限时间内收敛至滑模切换面。仿真结果表明,上述滑模控制器在模型存在不确定性的情况下能够保证变体过程的全局稳定性。     

Traffic control based on dahlin algorithm and neural network prediction in TAM networks

The propagation delay in networks has a great adverse effect on rate-based traffic control. This paper proposes the composite control based on Dab lin algorithm feedback control and neural network feedforward predictive compensation online for ABR (available bit rate) communication in ATM (asynchronous transfer mode) networks, which can overcome the adverse effect caused by the delay on the control rapidity and stability better. The theoretical analysis and simulation research show that the scheme can make sources respond to the changes of network status rapidly, avoid the congestion effectively and utilize the bandwidth sufficiently. Compared with PID (proportional-integral-derivative) control, cell loss rate is much lower, link utilization rate is much higher, and required buffer capacity is much smaller.