基于比较原理的非线性组合系统的输出反馈镇定

综合运用比较原理和LMI方法，通过构造一比较系统，将原组合系统的稳定性问题转化为维数较低的比较系统的稳定性问题，并利用M矩阵特性导出了比较系统稳定的一个充分条件．为了求取输出反馈增益，建立了等价稳定条件的QLMI表示形式．这一方法的特点是使大系统的稳定控制器设计的复杂度保持在子系统一级的水平上．数值实例说明了所提出算法在实际工程应用中的可行性和有效性．     

非线性最小相位系统输出反馈镇定的一个注记

讨论了单输入单输出非线性最小相位系统的动态输出反馈镇定.通过加积分器和非 线性变换将系统化为一种标准形式,并基于标准形式的线性部分提出了动态补偿器的设计方 法.然后根据得到的中心流形的表达式和稳定性定理,在零动态流形为一维时,证明了闭环系 统的渐近稳定性,最后给出了一个零动态不具有齐次渐近稳定性但仍能动态输出反馈镇定的 非线性最小相位系统的例子.     

一类开关切换系统的输出反馈镇定

对一类子系统为线性的开关切换系统进行观测器设计，并给出系统动态输出反馈可镇定的充分条件。在所设计的观测器基础上，以系统状态的观测值为依据设计各子控制器和切换方案，使整个闭环系统是指数渐近稳定的。对于切换时间间隔受限制的情况，给出了相应的动态输出反馈可镇定条件和镇定控制方案。实例仿真结果表明，所给出的设计方案是可行的。     

基于状态观测器的非理想输入不确定组合大系统的输出反馈分散镇定

基于状态观测器,讨论了不确定相似组合系统的鲁棒分散输出反馈镇定问题,系统的输入是非理想的,不确定项存在于系统内部和各子系统的关联项中,它们可能是非线性或时变的,且满足通常的匹配条件,使用变结构原理设计控制器,所设计的控制器保证系统渐近稳定,研究结果表明,系统的相似性有助于简化对系统的分析和设计;仿真结果表明,本文的方法是有效的。     

不确定内联系统的二次稳定性和分散反馈镇定

文中首先讨论了系统x(t)={A0+k∑i=1DiFi(t)Ei}x(t)的二次稳定性,给出以H∞小 增益条件表示的该系统是二次稳定的充分必要条件.然后讨论了一类不确定内联系统的二次 稳定性和分散反馈镇定问题,给出用"集结"后的子系统的一组H∞小增益条件表示的不确定 内联系统二次稳定和可分散反馈镇定的充分条件.分散控制可通过求一组子系统阶数的Riccati 不等式得到.     

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。     

带时滞的双时间尺度系统反馈镇定

研究带时滞的双时间尺度系统的反馈镇定问题,首先,给出子系统稳定的一个充分条件.然后,利用两个子系统稳定性得到带时滞的双时间尺度系统稳定的一个充分条件,最后,利用线性反馈分析得到两个子系统的稳定设计,从而使得整个系统稳定.给出一个数值例子验证了可行性和有效性.     

离散时间非线性最小相位系统的动态输出反馈镇定

研究了离散时间非线性最小相位系统的动态输出反馈镇定.首先对离散时间非线性系 统引入了逼近渐近稳定性的概念.基于此概念,提出了一种动态补偿器设计的新方法.主要结果 是,如果一非线性系统的零动态是逼近渐近稳定的,则能用动态输出反馈镇定.动态补偿器的设 计是构造性的.     

一类非线性系统的控制器和观测器设计

研究一类非线性系统的全状态反馈控制问题、观测器设计问题及输出反馈控制设计问题.首先设计出非线性全状态反馈控制器,获得了系统指数镇定的充分条件.然后提出了非线性观测器,并证明了该观测器是指数稳定观测器.进一步,在控制器和观测器问题的充分条件满足的假设下,证明了提出的带估计状态的反馈控制能达到指数镇定.最后,仿真实例验证了所得结果的有效性.     

系统的增速依赖于不可测状态非线性系统全局输出反馈渐近镇定

研究了一类非线性增长速度依赖于不可测状态且有稳定零动态非线性系统的全局输出反馈渐近稳定控制问题. 因所研究的系统隐含有零动态, 所以首先定义了一系列新的线性变换, 从而成功地分离出原系统的零动态, 得到了便于输出反馈设计的新系统. 然后给出了变换后系统的较为简洁的输出反馈控制设计过程, 并且, 闭环系统的渐近稳定性可由所导出矩阵的正定性来保证. 最后, 仿真算例验证了文中理论结果的正确性.     

Output feedback decentralized stabilization: ILMI approach

In this paper, the static output feedback decentralized stabilization problem is addressed using a linear matrix inequality approach. A necessary and sufficient condition for static output feedback decentralized stabilizability is derived for linear time-invariant large-scale systems. It is proven that the existence of a stabilizing decentralized gain is equivalent to that of the solution of a quadratic matrix inequality. The extension of the result to control is studied. An iterative LMI algorithm based on the linear matrix inequality technique is proposed to obtain the decentralized feedback gain. Examples show the effectiveness of the algorithm.     

Optimization of static output feedback using substitutive LMI formulation

This note proposes a new design tool for optimizing static output feedback using a linear matrix inequality (LMI) formula called substitutive LMI. A matrix inequality derived from static output feedback is not usually linear. Adding a positive definite term including auxiliary variables, the matrix inequality is transformed into an LMI with respect to the positive definite matrix and the static output feedback gain. An iterative calculation algorithm is given to solve the substitutive LMI. In this note, designs of the static output feedback gain are shown in the frame of H/sub /spl infin// and H/sub 2/ syntheses. A numerical example is shown to demonstrate the effectiveness of the proposed technique.     

Static Output Feedback Stabilization: An ILMI Approach

In this note, the static output feedback stabilization problem is addressed using the linear matrix inequality technique. A necessary and sufficient condition for static output feedback stabilizability for linear time-invariant systems is derived in the form of a matrix inequality. The extension of the result to H_∞ control is studied. An iterative LMI (ILMI) algorithm is proposed to compute the feedback gain. Numerical examples are employed to demonstrate the effectiveness and the convergence of the algorithm.     

L1 synthesis of a static output controller for positive systems by LMI iteration

An approach to find a static output feedback gain that makes the feedback system positive and minimizes the L₁ gain is proposed. The problem of finding a static output feedback gain has 3 aspects: stabilizing the system, making the system positive, and then minimizing the L₁ gain. Each subproblem is described by bilinear matrix inequality with respect to the feedback gain and the Lyapunov matrix or vector. Linear matrix inequality (LMI) that is sufficient to satisfy bilinear matrix inequality is derived using a convex‐concave decomposition, and the feedback gain sequence is calculated by an iterative solution of LMI. The sequence of the upper bounds on the design parameter is guaranteed to be monotonically nonincreasing for each algorithm. Similarly, 2 other LMIs are derived for each subproblem using another convex‐concave decomposition and PK iteration. The effectiveness of these algorithms is illustrated via several numerical examples.     

Stability analysis for linear systems under State constraints

This note revisits the problem of stability analysis for linear systems under state constraints. New and less conservative sufficient conditions are identified under which such systems are globally asymptotically stable. Based on these sufficient conditions, iterative linear matrix inequality (LMI) algorithms are proposed for testing global asymptotic stability of the system. In addition, these iterative LMI algorithms can be adapted for the design of globally stabilizing state feedback gains.     

严格正则多输入多输出对象同时镇定

使用逆LQ方法讨论了r个严格正则多输入多输出对象的同时镇定问题,基于矩阵 不等式方法得到了静态输出反馈可同时镇定的充要条件,本文证明,r个对象静态输出反馈同 时镇定等价于r个耦合LQ控制问题的解.然后,基于迭代线性矩阵不等式技术给出了一种 迭代求解方法,并给出了算例.     

Output feedback MPC with guaranteed robust stability

This paper focuses on the issues of robust stability of model predictive control (MPC). The control problem is formulated as linear matrix inequalities (LMI) optimization problem. A suboptimal solution for the output feedback control problem is proposed. The size of the resulting MP controller is reduced by using a suitable state-space representation of the process. Guaranteed stability conditions for the output feedback MPC are enforced via a Lyapunov type constraint. An iterative algorithm is developed resulting in a pair of coupled LMI optimization problems which provide a robustly stable output feedback gain. Model uncertainties are considered via a polytopic set of process models. The methodology is illustrated with the simulation of the control problem of two chemical processes. The results show that the proposed strategy eliminates the need to detune the MP controller improving the performance for most of the cases considered.     

网络控制系统的最大允许时延界

提出确定多输入多输出网络控制系统的最大允许时延界的新方法. 由于网络诱导时延的分布特性, 整个多输入多输出网络控制系统实际上是一个多时延系统. 利用李雅普诺夫第二方法, 得到网络控制系统时延相关渐近稳定性判据. 最大允许时延界和输出反馈镇定控制器均可通过求解矩阵不等式(LMI)得到. 仿真比较说明了本文结果的正确性和可行性.     

New iterative linear matrix inequality based procedure for H2 and H∞ state feedback control of continuous‐time polytopic systems

This article provides new linear matrix inequality (LMI) sufficient conditions for a generalized robust state feedback control synthesis problem for linear continuous‐time polytopic systems. This generalized problem includes the robust stability, H₂ ‐norm, and H_∞ ‐norm problems as special cases. Using a novel general separation result, which separates the state feedback gain from the Lyapunov matrix but with the state feedback gain synthesized from the slack variable, then allows the formulation of LMI sufficient conditions for the generalized problem. Compared to existing parameterized LMI based conditions, where auxiliary scalar parameters are introduced in order to include the quadratic stability conditions (ie, assuming a constant Lyapunov matrix) as a special case, the proposed new conditions are true LMIs and contain as a particular case the optimal quadratic stability solution. Utilizing any initial solution derived by the quadratic or some existing methods as a starting solution, we propose an algorithm based on an iterative procedure, which is recursively feasible in each update, to compute a sequence of nonincreasing upper bounds for the H₂ ‐norm and H_∞ ‐norm. In addition, if no feasible initial solution can be found for some uncertain systems using any existing methods, another algorithm is presented that offers the possibility of obtaining a robust stabilizing gain. Numerical examples from the literature demonstrate that our algorithms can provide less conservative results than existing methods, and they can also find feasible solutions where all other methods fail.