Markov跳变系统的单步约束预测控制

针对离散Markov跳变系统,研究带输出约束的单步预测控制问题。首先设计基于模态的单步预测控制器,驱动系统状态到达相应的终端不变集内,以此保证约束预测控制系统的稳定性,接着进一步讨论了系统存在峰值有界噪声输入情形。其中终端不变集是通过在预测时域外寻求一个虚拟的带约束的状态反馈控制器以保证系统的随机稳定性来获得,为计算方便,控制器的优化问题转化为SDP问题,并得到以LMI描述的优化问题。最后对Markov跳变系统描述的经济学动力系统的仿真结果说明了本控制器设计方法能够在峰值有界噪声输入下保证系统的稳定性,并且使控制变量满足给定的约束条件。     

Robust H∞ control for networked control systems

The robust H∞ control for networked control systems with both stochastic network-induced delay and data packet dropout is studied.When data are transmitted over network,the stochastic data packet dropout process can be described by a two-state Markov chain.The networked control systems with stochastic network-induced delay and data packet dropout are modeled as a discrete time Markov jump linear system with two operation modes.The sufficient condition of robust H∞ control for networked control systems stabilized by state feedback controller is presented in terms of linear matrix inequality.The state feedback controller can be constructed via the solution of a set of linear matrix inequalities.An example is given to verify the effectiveness of the method proposed.     

Robust H∞ control for networked control systems

The robust H∞ control for networked control systems with both stochastic network-induced delay and data packet dropout is studied. When data are transmitted over network, the stochastic data packet dropout process can be described by a two-state Markov chain. The networked control systems with stochastic network-induced delay and data packet dropout are modeled as a discrete time Markov jump linear system with two operation modes. The sufficient condition of robust H∞ control for networked control systems stabilized by state feedback controller is presented in terms of linear matrix inequality. The state feedback controller can be constructed via the solution of a set of linear matrix inequalities. An example is given to verify the effectiveness of the method proposed.     

Robust H_∞ Control for Uncertain Markovian Jump Linear Time-Delay Systems

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Maximum principle for forward-backward stochastic control system with random jumps and applications to finance

<正> Both necessary and sufficient maximum principles for optimal control of stochastic systemwith random jumps consisting of forward and backward state variables are proved.The control variableis allowed to enter both diffusion and jump coefficients.The result is applied to a mean-varianceportfolio selection mixed with a recursive utility functional optimization problem.Explicit expressionof the optimal portfolio selection strategy is obtained in the state feedback form.     

A Guaranteed Cost Approach to Dynamic Output Feedback Control for Neutral-Type Markovian Jumping Stochastic Systems

This paper is devoted to investigating the dynamic output feedback(DOF) control problem of Markovian jump neutral-type stochastic systems with a guaranteed cost function. Both of the state and measurement equations contain time delays. Mode-dependent DOF controllers are first designed such that the closed-loop system is asymptotically stable in mean-square and an adequate performance level of this system is guaranteed. Then, sufficient conditions for the solvability of this problem are derived in the form of linear matrix inequalities(LMIs). A numerical example is presented to reveal the effectiveness of our findings.     

电网电压跌落故障下双馈风力发电机无源性控制

为提高电网电压跌落故障情况下双馈风力发电系统不间断运行的能力,提出了一种基于无源性理论的双馈风力发电机低电压穿越控制策 略. 通过分析双馈风力发电机系统模型的无源性,设计了状态反馈控制器;根据双馈风力发电机在电网电压跌落故障时的运行特点,给出了一种 计及电网电压变化的期望状态值计算方法,状态期望值跟随电网电压变化而迅速改变,通过状态反馈控制器可实现电机电流快速跟踪. 仿真结果 表明在电网电压跌落故障下所提出的控制策略可以有效的抑制双馈风力发电机定、转子过电流,并且降低了电磁转矩波动幅值.     

高阶随机非线性系统状态反馈镇定

针对一类高阶下三角随机非线性系统,提出一种新的镇定方案,采用增加一个幂积分的工具构建了一个全局稳定的光滑状态反馈控制律。通过反馈占有设计方法和Young不等式处理随机系统的非线性项,取消了对随机非线性系统反馈线性化和控制输入呈线性的要求,基于Lyapunov方法,证明了闭环系统依概率全局渐近稳定。最后,仿真实例说明了算法的可行性。     

Constrained predictive control of nonlinear stochastic systems

The receding horizon control (RHC) problem is considered for nonlinear Markov jump systems which can be represented by Takagi-Sugeno fuzzy models subject to constraints both on control inputs and on observe outputs. In the given receding horizon, for each mode sequence of the T-S modeled nonlinear system with Markov jump parameter, the cost function is optimized by constraints on state trajectories, so that the optimization control input sequences are obtained in order to make the state into a terminal invariant set. Out of the receding horizon, the stability is guaranteed by searching a state feedback control law. Based on such stability analysis, a linear matrix inequality approach for designing receding horizon predictive controller for nonlinear systems subject to constraints both on the inputs and on the outputs is developed. The simulation shows the validity of this method.         

一类T-S 模糊广义系统的无源控制

研究了一类T-S模糊广义系统的无源控制问题.通过矩阵分解方法,证明了这类系统容许的充分必要条件.在此基础上,将严格无源的概念引入到T-S模糊广义系统中,得到了使闭环系统容许、严格无源的充分条件,并将此条件用线性矩阵不等式(LMIs)表示.通过解这些矩阵不等式得到状态反馈增益矩阵.这个充分条件,可以一次判定系统的容许、严格无源.最后的数值算例说明所给方法的可行、有效.     

Bayesian estimation for nonlinear stochastic hybrid systems with state dependent transitions

The Bayesian approach is considered as the most general formulation of the state estimation for dynamic systems.However,most of the existing Bayesian estimators of stochastic hybrid systems only focus on the Markov jump system,few literature is related to the estimation problem of nonlinear stochastic hybrid systems with state dependent transitions.According to this problem,a new methodology which relaxes quite a restrictive assumption that the mode transition process must satisfy Markov properties is proposed.In this method,a general approach is presented to model the state dependent transitions,the state and output spaces are discreted into cell space which handles the nonlinearities and computationally intensive problem offline.Then maximum a posterior estimation is obtained by using the Bayesian theory.The efficacy of the estimator is illustrated by a simulated example.     

一种新型的非线性随机大系统自适应镇定方法

研究了一类具有严反馈形式并含有Wiener噪声扰动的非线性随机大系统,其互联项满足线性增长约束。利用微分几何的理论,应用Backstepping算法,基于Lyapunov稳定性理论,选择了适合这类组合非线性系统的状态观测器,设计了自适应输出反馈分散控制律和自适应律,使得闭环,互联的非线性随机大系统实现了概率意义下的全局稳定,仿真结果表明了控制算法的有效性。     

Passivity analysis for uncertain stochastic neural networks with discrete interval and distributed time-varying delays

The problem of passivity analysis is investigated for uncertain stochastic neural networks with discrete interval and distributed time-varying delays. The parameter uncertainties are assumed to be norm bounded and the delay is assumed to be time-varying and belongs to a given interval, which means that the lower and upper bounds of interval time-varying delays are available. By constructing proper Lyapunov-Krasovskii functional and employing a combination of the free-weighting matrix method and stochastic analysis technique, new delay dependent passivity conditions are derived in terms of linear matrix inequalities (LMIs). Finally, numerical examples are given to show the less conservatism of the proposed conditions.     

Study of Modern Securities Pricing Model

On the basis of the theory of system, epistemology, and feedback control, a novel securities pricing model — stochastic volatility pricing model (SVPM) with jump and feedback mechanism is proposed. This model overcomes the defect of traditional SVPM models that neglect the important events happening frequently in financial markets, and also considers the interaction between investors and securities price. Theoretical analysis and numerical simulations indicate that this model can simulate the complex behaviors of real securities price better than traditional SVPMs. Comparisons suggest that the simulated return rates have the same statistical characteristics as the real stocks’. Finally, practical applications of this model show that this is of high precision, efficiency, robustness, and universality.     

Robust reliable guaranteed cost control for nonlinear singular stochastic systems with time delay

To study the design problem of robust reliable guaranteed cost controller for nonlinear singular stochastic systems,the Takagi-Sugeno(T-S)fuzzy model is used to represent a nonlinear singular stochastic system with norm-bounded parameter uncertainties and time delay.Based on the linear matrix inequality(LMI)techniques and stability theory of stochastic differential equations,a stochastic Lyapunov function method is adopted to design a state feedback fuzzy controller.The resulting closed-loop fuzzy system is robustly reliable stochastically stable,and the corresponding quadratic cost function is guarauteed to be no more than a certain upper bound for all admissible uncertainties,as well as different actuator fault cases.A sufficient condition of existence and design method of robust reliable guaranteed cost controller is presented.Finally,a numerical simulation is given to illustrate the effectiveness of the proposed method.     

Sampled-Data H∞ Dynamic Output Feedback Controller Design for Fuzzy Markovian Jump Systems

This paper considers the issue of H_∞ dynamic output feedback controller design for T-S fuzzy Markovian jump systems under time-varying sampling with known upper bound on the sampling intervals. The main aim is to realize sampled-data fuzzy dynamic output feedback control so as to demonstrate the stochastic stability and H_∞ performance index of the closed-loop sampled-data fuzzy Markovian jump systems. Then, by making the most of the information within the sampling interval,...     

随机波动和跳跃下的短期利率动态

在短期利率模型中引入随机波动和跳跃两种因素,利用序贯参数更新思想和粒子滤波方法实现模型的估计,并对中国银行间短期利率进行实证分析. 研究结果显示短期利率存在显著的随机波动和跳跃特征,表明CIR-SV-J模型在描述短期利率动态中拟合效果最优,而且忽视随机波动或跳跃因素会使拟合变差,影响对利率均值回复特征的描述,并证明了随机波动因素在模拟中比跳跃因素起着更为重要的作用.     

随机时延网络控制系统的鲁棒H∞状态反馈控制

研究了含有双随机时延的不确定网络控制系统的鲁棒H_∞状态反馈控制问题。将传感器到控制器和控制器到执行器的网络时延建模为相互独立的连续时间离散状态的马尔可夫随机过程。基于此网络环境,构造时延依赖的控制器,将不确定网络控制系统转化为马尔可夫跳变系统。通过Lyapunov Krasovskii泛函方法和新的矩阵不等式技术,给出了系统随机稳定且满足H_∞性能的充分条件,并以矩阵不等式形式给出了相应的控制器设计方法。最后,给出了仿真算例,验证了该方法的有效性。     

Delay-dependent passive control of linear systems with nonlinear perturbation

The problem of delay-dependent passive control of a class of linear systems with nonlinear perturbation and time-varying delay in states is studied. The main idea aims at designing a state-feedback controller such that for a time-varying delay in states, the linear system with nonlinear perturbation remains robustly stable and passive. In the system, the delay is time-varying. And the derivation of delay has the maximum and minimum value. The time-varying nonlinear perturbation is allowed to be norm-bounded. Using the effective linear matrix inequality methodology, the sufficient condition is primarily obtained for the system to have robust stability and passivity. Subsequently the existent condition of a state feedback controller is given, and the explicit expression of the controller is obtained by means of the solution of linear matrix inequalities （LMIs）. In the end, a numerical example is given to demonstrate the validity and applicability of the proposed approach.     

A Mean-Field Linear-Quadratic Stochastic Stackelberg Differential Game with one Leader and Two Followers

This paper is concerned with a linear-quadratic(LQ) stochastic Stackelberg differential game with one leader and two followers, where the game system is governed by a mean-field stochastic differential equation(MF-SDE). By maximum principle and verification theorem, the open-loop Stackelberg solution is expressed as a feedback form of the state and its mean with the help of three systems of Riccati equations.