一类随机非线性系统的输出反馈全局镇定

将基于增益观测器的非线性系统输出反馈全局镇定控制器设计方法推广到随机情形,使之适用于一般的随机非线性系统.与已有基于反步法设计的镇定控制器相比,该方法不要求该随机非线性系统满足严格反馈条件,对其噪声向量函数也不要求满足光滑性条件.基于李亚普诺夫第二方法,讨论了所设计的控制器稳定的条件.一个二阶仿真算例表明该控制器设计方法是有效的.     

Fixed-Order l_1-Control for Systems with Time-Delay

1. INTRODUCTIONPhysical plaaes are inevitably affected by exogenous disturbance, hence rejecting disturbanceis important. Ffor example, HOO-control systems can reject the LZ disturbance. But in factthere are maily species of disturbances: some are LZ-attenuation; some are stochastic; andsome are Loo(loo) [6]. If the exogenous disturbance is modeled as the energy-bounded signal, and the performance is the output energyt that is Hoo problem. If the performance isoutput energy, that is p…     

Adaptive NN stabilization for stochastic systems with discrete and distributed time-varying delays

A new adaptive neural network(NN) output-feedback stabilization controller is investigated for a class of uncertain stochastic nonlinear strict-feedback systems with discrete and distributed time-varying delays and unknown nonlinear functions in both drift and diffusion terms.First,an extensional stability notion and the related criterion are introduced.Then,a nonlinear observer to estimate the unmeasurable states is designed,and a systematic backstepping procedure to design an adaptive NN output-feedback controller is proposed such that the closed-loop system is stable in probability.The effectiveness of the proposed control scheme is demonstrated via a numerical example.     

Robust output-feedback stabilization of a class of nonlinear systems with the nonlinearities of varied form

1 .INTRODUCTIONThe problem of global stabilization of nonlinearsystems by output feedback has received much at-tention. Unlike in the case of linear systems ,theseparation principle generally does not hold fornonlinear systems . This is one of the reasons whythe problemis more difficult . As investigated byRef .[1] ,some extra growth conditions onthe un-measurable states of the systemare usually neces-sary for the global stabilization of nonlinear sys-tems via output feedback. For exampl…     

一类随机非线性系统的输出反馈镇定

针对一类随机非线性系统的输出反馈镇定问题,首先利用反推技术和设计有效的观测器,为其对应的标称系统设计稳定的输出反馈控制器;然后通过有效的坐标变换,并选择恰当的高增益参数,利用高增益齐次占优技术,为整个系统设计了光滑的输出反馈控制器,所设计的控制器能够保证闭环系统的平衡点是依概率全局渐近稳定的,上述过程的主要贡献是将现有...     

一类不确定离散切换模糊时滞系统的鲁棒输出反馈控制

针对状态不可观测的情况,重构系统状态,提出了一类不确定离散切换模糊时滞系统的鲁棒镇定问题.考虑每个切换子系统都是模糊系统的切换系统模型,利用切换技术,对于系统状态采用多Lyapunov函数方法,对于观测器误差采用共同Lyapunov函数方法,给出了切换律设计.利用平行分布补偿算法(PDC),给出了基于观测器的切换模糊反馈控制器设计,使得闭环系统对所有允许的不确定性,在所设计的反馈控制器和切换律下具有鲁棒性.最后通过数值仿真例子验证了该设计方法的有效性和可行性.     

极点和输出方差约束下的低成本输出反馈控制器设计

本文先给出问题的BMI描述,然后借鉴求解区域极点约束下输出反馈低成本控制的方法,设计静态输出反馈低成本控制器,使得系统同时满足区域极点指标和稳态输出方差指标,并给出了相应的满足条件的迭代求解算法。     

基于无源性分析的鲁棒输出反馈控制设计

基于无源系统理论,该文讨论了一类不确定非线性系统的鲁棒输出反馈控制问题。通过虚拟串联微分多项式到系统的输入端,回避了无源化方法所需的相对阶为1的条件,并进一步利用切换控制完成了虚拟串联后的控制器实现。仿真结果证明了本文算法的有效性。     

Output-feedback adaptive stochastic nonlinear stabilization using neural networks

For the first time, an adaptive backstepping neural network control approach is extended to a class of stochastic nonlinear output-feedback systems. Different from the existing results, the nonlinear terms are assumed to be completely unknown and only a neural network is employed to compensate for all unknown nonlinear functions so that the controller design is more simplified. Based on stochastic LaSalle theorem, the resulted closed-loop system is proved to be globally asymptotically stable in probability....     

Adaptive output-feedback control for MIMO nonlinear systems with time-varying delays using neural networks

An adaptive neural network output-feedback regulation approach is proposed for a class of multi-input-multi-output nonlinear time-varying delayed systems. Both the designed observer and controller are free from time delays. Different from the existing results, this paper need not the assumption that the upper bounding functions of time-delay terms are known, and only a neural network is employed to compensate for all the upper bounding functions of time-delay terms, so the designed controller procedure is more simplified. In addition, the resulting closed-loop system is proved to be semi-globally ultimately uniformly bounded, and the output regulation error converges to a small residual set around the origin. Two simulation examples are provided to verify the effectiveness of control scheme.