马尔可夫跳变系统的有限时间保性能控制

本文主要研究具有时变时滞的脉冲随机马尔可夫跳变系统的有限时间保性能控制问题.通过选取模态相关的李雅普诺夫泛函,使用线性矩阵不等式(LMI)、平均驻留时间方法等技术,得到一些新的充分条件来确保系统有限时间稳定,并给出了系统的上界性能指标.基于该充分条件设计了系统的状态反馈保性能控制器.最后,利用Matlab的LMI工具箱进行数据仿真,得到相应的均方轨迹图.数值例子结果表明,得到的仿真结果和理论结果一致,验证了文中理论的有效性.

非线性广义时滞Markov跳变系统的H_(∞)滑模控制

研究了一类转移速率部分未知的广义时滞Markov跳变系统的H_(∞)滑模控制问题.首先,对广义时滞Markov跳变系统设计了积分型滑模面,并求出对应的等效控制器.之后,构建Lyapunov泛函,通过线性矩阵不等式方法得到闭环系统随机容许且满足H_(∞)性能γ的充分条件,运用加减项方法以及引入自由权矩阵,使得到的结果降低了保守性;对滑模力学分析,设计了滑模控制器,使得系统能在有限时间内到达滑模面上.最后,通过数值算例与仿真验证了理论的可行性.

运动性疲劳对收腹起跳阶段下肢肌肉协同特征的影响

目的量化运动性疲劳(exercise-induced fatigue,EIF)前后运动员进行收腹起跳阶段中的下肢肌肉协同特征,揭示EIF对运动员收腹起跳阶段下肢肌肉协同特征的影响。方法比较10名田径专项班二级男性运动员EIF干预前后收腹起跳阶段的下肢表面肌电数据,分析EIF前后肌肉协同结构,采用配对样本t检验方法比较EIF前后协同参数的差异。结果EIF前后均提取出2个协同元,且存在肌肉协同结构的交替激活。EIF后,协同元2的激活程度显著下降,从53.21±7.90降至43.44±10.23,协同元1无显著变化。EIF后协同元1的股直肌贡献度显著增加,从0.37±0.04增至0.44±0.07,半腱肌贡献度显著降低,从0.13±0.05降至0.08±0.05。结论在收腹起跳中,随EIF增加,下肢各肌肉协同元的激活程度降低,协同元1中吸收地面反作用力的股直肌贡献程度增加,提示股直肌存在拉伤风险,应加强预防股直肌损伤。

中立型半马尔科夫跳跃系统可达集边界估计

研究了具有分布时滞且有界扰动的中立型半马科夫跳跃系统和不确定中立型半马科夫跳跃系统的可达集边界问题.考虑系统中立时滞项的影响,利用Lyapunov方法,结合改进的积分不等式、自由权矩阵思想和时滞拆分技巧,得到了以线性矩阵形式表示的具有分布时滞且有界扰动的中立型半马尔科夫跳跃系统和不确定中立型半马尔科夫跳跃系统可达集边界的判定条件.

基于事件触发的奇异semi-Markov跳变系统的有限时间控制

为减少不必要的网络资源传输,解决实际复杂系统的有限时间问题,提出一种基于事件触发方案的奇异semi-Markov跳变系统的有限时间控制器设计方法。在事件触发方案下,用系统的时滞表示网络诱导时延,闭环系统可以建模为一个时滞系统。首先,通过构造合适的Lyapunov-Krasovskii泛函,以严格矩阵不等式的形式给出充分条件,以使事件触发方案下的闭环系统正则、无脉冲、随机有限时间有界;然后,通过求解矩阵不等式,得到状态反馈控制器的参数;最后,给出一个数值示例,通过仿真证明所提方法的有效性。

Delay-dependent Stability Analysis for Markovian Jump Systems with Interval Time-varying-delays

This paper proposes improved stochastic stability conditions for Markovian jump systems with interval time-varying delays. In terms of linear matrix inequalities （LMIs）, less conservative delay-range-dependent stability conditions for Markovian jump systems are proposed by constructing a different Lyapunov-Krasovskii function. The resulting criteria have advantages over some previous ones in that they involve fewer matrix variables but have less conservatism. Numerical examples are provided to demonstrate the efficiency and reduced conservatism of the results in this paper.

Robust H_∞ control for uncertain Markovian jump systems with mixed delays

We scrutinize the problem of robust H∞control for a class of Markovian jump uncertain systems with interval timevarying and distributed delays. The Markovian jumping parameters are modeled as a continuous-time finite-state Markov chain. The main aim is to design a delay-dependent robust H∞control synthesis which ensures the mean-square asymptotic stability of the equilibrium point. By constructing a suitable Lyapunov–Krasovskii functional（LKF）, sufficient conditions for delay-dependent robust H∞control criteria are obtained in terms of linear matrix inequalities（LMIs）. The advantage of the proposed method is illustrated by numerical examples. The results are also compared with the existing results to show the less conservativeness.

Robust H-infinity filter design for uncertaintime-delay singular stochastic systems withMarkovian jump

This paper deals with the problem of H-infinity filter design for uncertain time-delay singular stochastic systems with Markovian jump. Based on the extended It6 stochastic differential formula, sufficient conditions for the solvability of these problems are obtained. Furthermore, It is shown that a desired filter can be constructed by solving a set of linear matrix inequalities. Finally, a simulation example is given to demonstrate the effectiveness of the proposed method.

STOCHASTIC STABILITY OF UNCERTAIN RECURRENT NEURAL NETWORKS WITH MARKOVIAN JUMPING PARAMETERS

In this paper, global robust stability of uncertain stochastic recurrent neural networks with Markovian jumping parameters is considered. A novel Linear matrix inequal- ity（LMI） based stability criterion is obtained to guarantee the asymptotic stability of uncertain stochastic recurrent neural networks with Markovian jumping parameters. The results are derived by using the Lyapunov functional technique, Lipchitz condition and S-procuture. Finally, numerical examples are given to demonstrate the correctness of the theoretical results. Our results are also compared with results discussed in [31] and [34] to show the effectiveness and conservativeness.

Stability of stochastic neural networks with Markovian jumping parameters

The global asymptotical stability for a class of stochastic delayed neural networks （SDNNs） with Maxkovian jumping parameters is considered. By applying Lyapunov functional method and Ito＇s differential rule, new delay-dependent stability conditions are derived. All results are expressed in terms of linear matrix inequality （LMI）, and a numerical example is presented to illustrate the correctness and less conservativeness of the proposed method.

Distributed Model Predictive Control with Actuator Saturation for Markovian Jump Linear System

This paper is concerned with the distributed model predictive control (MPC) problem for a class of discrete-time Markovian jump linear systems (MJLSs) subject to actuator saturation and polytopic uncertainty in system matrices. The global system is decomposed into several subsystems which coordinate with each other. A set of distributed controllers is designed by solving a min-max optimization problem in terms of the solutions of linear matrix inequalities (LMIs). An iterative algorithm is developed to achieve the online computation. Finally, a simulation example is employed to show the effectiveness of the proposed algorithm. © 2014 Chinese Association of Automation.

Robust Stabilization for Uncertain Linear Delay Markow Jump System

Markov jump linear systems are defined as a family of linear systems with randomly Markov jumping parameters and are used to model systems subject to failures or changes in structure. The robust stabilization problem of jump linear delay system with umcerratnty was studied. By using of linear matrix inequalities, the existence conditions of robust stabilizing and the state feedback controller designing methods are also presented and proved. Finally, an illustrated example shows the effectiveness of this approach.

Delay-dependent stabilization of singular Markovian jump systems with state delay

This paper deals with the delay-dependent stabilization problem for singular systems with Markovian jump parameters and time delays. A delay-dependent condition is established for the considered system to be regular, impulse free and stochastically stable. Based on the condition, a design algorithm of the desired state feedback controller which guarantees the resultant closed-loop system to be regular, impulse free and stochastically stable is proposed in terms of a set of strict linear matrix inequalities （LMIs）. Numerical examples show the effectiveness of the proposed methods.

Nonlinear H_∞ filtering for interconnected Markovian jump systems

The problem of nonlinear H∞ filtering for interconnected Markovian jump systems is discussed. The aim of this note is the design of a nonlinear Markovian jump filter such that the resulting error system is exponentially meansquare stable and ensures a prescribed H∞ performance. A sufficient condition for the solvability of this problem is given in terms of linear matrix inequalities（LMIs）. A simulation example is presented to demonstrate the effectiveness of the proposed design approach.

On passivity of state delayed stochastic jump systems

Based on the definition of passivity extended from deterministic system, the sufficient condition on passivity of stochastic jump system is given against unknown state time delay. By means of memoryless state feedback, a class of state delayed stochastic jump systems may be led to passive. The feedback controllers are mode-dependent and can be constructed in terms of the solutions of a set of coupled linear matrix inequalities. A numerical example illustrates the results.

Robust stability and H-infinity control for uncertain discrete-time Markovian jump singular systems

The robust stability and stabilization, and H-infinity control problems for discrete-time Markovian jump singular systems with parameter uncertainties are discussed. Based on the restricted system equivalent （r.s.e.） transformation and by introducing new state vectors, the singular system is transformed into a discrete-time Markovian jump standard linear system, and the linear matrix inequality （LMI） conditions for the discrete-time Markovian jump singular systems to be regular, causal, stochastically stable, and stochastically stable with 7- disturbance attenuation are obtained, respectively. With these conditions, the robust state feedback stochastic stabilization problem and H-infinity control problem are solved, and the LMI conditions are obtained. A numerical example illustrates the effectiveness of the method given in the oaoer.

Exponential stability for uncertain neutral systems with Markov jumps

This paper deals with the global exponential stability problems for stochastic neutral Markov jump systems （MJSs） with uncertain parameters and multiple time-delays. The delays are respectively considered as constant and time varying cases, and the uncertainties are assumed to be norm bounded. By selecting appropriate Lyapunov-Krasovskii functions, it gives the sufficient condition such that the uncertain neutral MJSs are globally exponentially stochastically stable for all admissible uncertainties. The stability criteria are formulated in the form of linear matrix inequalities （LMIs）, which can be easily checked in practice. Finally, two numerical examples are exploited to illustrate the effectiveness of the developed techniques.

Delay-dependent guaranteed cost control for uncertain discrete-time Markovian jump linear systems with mode-dependent time-delays

In this paper,the problem of guaranteed cost control for a class of uncertain discrete-time Markovian jump linear systems with mode-dependent time-delays and a given quadratic cost function are investigated. Attention is focused on designing a memoryless state feedback control law such that the closed-loop system is robust stochastically stable and the closed-loop cost function value is not more than a specified upper bound,for all admissible uncertainties. The key features of the approach include the introduction of a new type of suitable stochastic Lyapunov functional and free weighting matrices techniques. Sufficient conditions for the existence of such controller are obtained in terms of a set of linear matrix inequalities. A numerical example is given to illustrate the less conservatism of the proposed techniques.

Robust guaranteed cost filtering for uncertain timedelay systems with Markovian jumping parameters

The robust guaranteed cost filtering problem for a dass of linear uncertain stochastic systems with time delays is investigated. The system under study involves time delays, jumping parameters and Brownian motions. The transition of the jumping parameters in systems is governed by a finite-state Markov process. The objective is to design linear memoryless filters such that for all uncertainties, the resulting augmented system is robust stochastically stable independent of delays and satisfies the proposed guaranteed cost performance. Based on stability theory in stochastic differential equations, a sufficient condition on the existence of robust guaranteed cost filters is derived. Robust guaranteed cost filters are designed in terms of linear matrix inequalities. A convex optimization problem with LMI constraints is formulated to design the suboptimal guaranteed cost filters.