一类高阶次随机非线性系统的输出反馈镇定

针对一类高阶次随机非线性系统,研究其输出反馈镇定问题．通过选择有效的观测器和李雅普诺夫函数,所设计的光滑输出反馈控制器保证了闭环系统的平衡点是依概率全局渐近稳定的,输出几乎处处调节到零．数值仿真验证了控制方案的有效性．     

一类上三角随机非线性系统的输出反馈控制

针对一类上三角随机非线性系统的输出反馈控制问题,首先利用反推技术,为其对应的标称系统设计稳定的输出反馈控制器;然后利用低增益齐次占优技术,为整个系统设计输出反馈控制器.所设计的控制器能保证闭环系统的平衡点为依概率全局渐近稳定的,并将低增益齐次占优技术推广到了随机系统,首次解决了一类上三角随机系统的镇定问题.最后通过数值仿真验证了所提出控制方案的有效性.     

一类高阶次随机非线性系统的输出反馈镇定

针对一类高阶次随机非线性系统,研究其输出反馈镇定问题．通过选择有效的观测器和李雅普诺夫函数,所设计的光滑输出反馈控制器保证了闭环系统的平衡点是依概率全局渐近稳定的,输出几乎处处调节到零．数值仿真验证了控制方案的有效性．

     

量子力学系统的输出反馈控制

研究量子系统输出反馈控制问题建模以及控制律设计问题.首先讨论了量子力学VonNeumann测量原理与连续测量模型的一致性;然后在连续测量模型的基础上总结了已有量子反馈模型的结果,归纳出量子输出反馈控制系统模型;最后针对单比特振幅退相干抑制问题,利用线性直接输出反馈控制设计反馈控制律,指出利用最优控制的方法设计线性输出反馈控制的比例系数,可以得到较好的结果.     

一类高次随机非线性系统的自适应动态面控制

针对一类含非线性参数高次随机非线性系统的输出跟踪控制问题,基于自适应增加幂次积分方法,利用参数分离技术和动态面技术,给出了一种自适应光滑状态反馈控制器设计方法。利用Sigmoid函数设计参数自适应律,保证了其导数连续。将低通滤波器引入控制器设计过程,避免了“微分爆炸”现象。通过构造适当形式的控制Lyapunov函数进行稳定性分析,证明了系统输出能被依概率地调节至参考信号的邻域范围。仿真结果验证了所提控制器设计方案的有效性。     

一类线性时变系统的输出反馈控制

基于线性时不变系统能控能观标准型变换及非线性系统高增益观测器方法,本文研究了一类线性时变系统 的输出反馈控制问题. 通过引入时变的状态变量坐标变换,分别设计了线性时变系统的状态反馈控制器、状态观测器以及基于 状态观测器的输出反馈控制器. 进一步地,本文分别证明了观测器动态误差是渐近收敛于零的,而状态反馈控制器以及输出反馈控制器可以 保证闭环系统的渐近稳定性.     

基于LMI方法的T-S模糊系统的H∞输出反馈控制器设计

研究了一类T-S模糊系统的H∞控制问题,给出了T-S模糊系统一个新的H∞输出反馈控制器设计方法.该方法充分考虑了模糊子系统间的相互作用.H∞输出反馈控制器可通过求解一组线性矩阵不等式获得.最后通过数值仿真例子,说明所提出的设计方法的可行性.     

基于Razumikhin 方法的随机时变时滞非线性系统的状态反馈

采用Razumikhin 方法研究一类随机时变时滞非线性系统的状态反馈镇定问题. 利用随机系统的Razumikhin-Mao 理论和反推设计方法, 设计系统的状态反馈控制器, 所设计的控制器能保证闭环系统的平衡点为依概率全局渐近稳定的. 所提出的方法能够彻底地去掉关于随机时变时滞非线性系统传统结果中所要求的时滞导数的限制. 仿真示例验证了所提出状态反馈控制器的有效性.

     

基于Razumikhin方法的时变时滞非线性系统的输出反馈镇定

针对一类时变时滞非线性系统,采用Razumikhin方法研究其输出反馈控制问题.利用时滞系统的Razumikhin定理和反推设计方法,通过设计有效的观测器和选取适当的Lyapunov函数,构造系统的输出反馈控制器.所设计的控制器能够保证闭环系统的平衡点是全局渐近稳定的,所给出的方法无需考虑时滞导数的限制,改进了以前所得结果.仿真示例验证了所设计输出反馈控制器的有效性.     

不确定离散时滞系统的输出反馈鲁棒预测控制

对一类输入输出受限的不确定离散时滞系统,研究了使得闭环系统渐近稳定且滚动时域性能指标在线最小化的鲁棒预测输出反馈控制器设计问题.基于预测控制的滚动优化原理,给出了输出反馈控制器存在的充分条件.采用锥补线性化思想将控制器的设计转化为一个受线性矩阵不等式(LMI)约束的非线性规划问题,并利用该线性矩阵不等式的可行解给出了输出反馈控制器的构造方法.最后通过仿真验证了该方法的有效性.     

Output-feedback control of a class of stochastic nonlinear systems with power growth conditions

This paper investigates the problem of output-feedback stabilization for a class of stochastic nonlinear systems in which the nonlinear terms depend on unmeasurable states besides measurable input. We extend linear growth conditions to power growth conditions and reduce the control effort. By using backstepping technique, choosing a high-gain parameter, an output-feedback controller is designed to ensure the closed-loop system globally asymptotically stable in probability. The efficiency of the output-feedback controller is demonstrated by a simulation example.     

Output-feedback stabilization for stochastic nonlinear systems whose linearizations are not stabilizable

This brief paper investigates the problem of output-feedback stabilization for a class of high-order stochastic nonlinear systems which are neither necessarily feedback linearizable nor affine in the control input. Based on the ideas of the homogeneous systems theory and the adding a power integrator technique, an output-feedback controller is constructed to ensure that the equilibrium at the origin of the closed-loop system is globally asymptotically stable (GAS) in probability. The efficiency of the output-feedback controller is demonstrated by a simulation example.     

Output-feedback control of a class of high-order stochastic nonlinear systems

This article investigates the problem of output-feedback stabilisation for a class of high-order stochastic non-linear systems in which the diffusion terms depend on unmeasurable states besides the output. By introducing a new rescaling transformation, adopting an effective observer and choosing the appropriate Lyapunov function, an output-feedback controller is constructed to ensure that the equilibrium at the origin of the closed-loop system is globally asymptotically stable in probability, the output can be regulated to the origin almost surely, and the problem of inverse optimal stabilisation in probability is solved. The efficiency of the output-feedback controller is demonstrated by several simulation examples.     

Global adaptive control for a class of uncertain stochastic nonlinear systems with unknown output gain

This paper addresses the global adaptive control problem for a class of uncertain stochastic nonlinear systems in the output-feedback form. Due to the unknown output gain, we construct a full-order homogeneous observer instead of using the system output. Then, by adding a power integrator technique, an output-feedback controller is designed, as well as an adaptive law to deal with the unknown nonlinear growth rates. Based on the generalized stochastic Lyapunov stability theorem, it can be proved that all the signals of the closed-loop system are bounded in probability, and the system states converge to the origin almost surely.     

Output-feedback stabilization for stochastic high-order nonlinear systems with time-varying delay

This paper investigates output-feedback control for a class of stochastic high-order nonlinear systems with time-varying delay for the first time. By introducing the adding a power integrator technique in the stochastic systems and a rescaling transformation, and choosing an appropriate Lyapunov-Krasoviskii functional, an output-feedback controller is constructed to render the closed-loop system globally asymptotically stable in probability and the output can be regulated to the origin almost surely. A simulation example is provided to show the effectiveness of the designed controller.     

Continuous output-feedback stabilization for a class of stochastic high-order nonlinear systems

This paper is concerned with the global stabilization via output-feedback for a class of high-order stochastic nonlinear systems with unmeasurable states dependent growth and uncertain control coefficients. Indeed, there have been abundant deterministic results which recently inspired the intense investigation for their stochastic analogous. However, because of the possibility of non-unique solutions to the systems, there lack basic concepts and theorems for the problem under investigation. First of all, two stochastic stability concepts are generalized to allow the stochastic systems with more than one solution, and a key theorem is given to provide the sufficient conditions for the stochastic stabilities in a weaker sense. Then, by introducing the suitable reduced order observer and appropriate control Lyapunov functions, and by using the method of adding a power integrator, a continuous (nonsmooth) output-feedback controller is successfully designed, which guarantees that the closed-loop system is globally asymptotically stable in probability.     

Global output-feedback stabilization for a class of stochastic non-minimum-phase nonlinear systems

In this paper, the problem of output-feedback stabilization is investigated for the first time for a class of stochastic nonlinear systems whose zero dynamics may be unstable. Under the assumption that the inverse dynamics of the system is stochastic input-to-state stabilizable, a stabilizing output-feedback controller is constructively designed by the integrator backstepping method together with a new reduced-order observer design and the technique of changing supply functions. It is shown that, under small-gain type conditions for small signals, the resulting closed-loop system is globally asymptotically stable in probability. The obtained results extend the existing methodology from deterministic systems to stochastic systems. An example is given to demonstrate the main features and effectiveness of the proposed output-feedback control scheme.     

Global finite-time stabilisation for a class of stochastic nonlinear systems by output feedback

In this paper, the problem of global finite-time stabilisation by output feedback is considered for a class of stochastic nonlinear systems. First, based on homogeneous systems theory and the adding a power integrator technique, a homogeneous reduced order observer and control law are constructed in a recursive manner for the nominal system. Then, the homogeneous domination approach is used to deal with the nonlinearities in drift and diffusion terms; it is shown that the proposed output-feedback control law can guarantee that the closed-loop system is global finite-time stable in probability. Finally, simulation examples are carried out to demonstrate the effectiveness of the proposed control scheme.