Stochastic maximum principle for mixed regular-singular control problems of forward-backward systems

This paper considers a stochastic optimal control problem of a forward-backward system with regular-singular controls where the set of regular controls is not necessarily convex and the regular control enters the diffusion coefficient. This control problem is difficult to solve with the classical method of spike variation. The authors use the approach of relaxed controls to establish maximum principle for this stochastic optimal control problem. Sufficient optimality conditions are also investigated.     

Maximum principle for partially-observed optimal control problems of stochastic delay systems

This paper is concerned with partially-observed optimal control problems for stochastic delay systems. Combining Girsanov’s theorem with a standard variational technique, the authors obtain a maximum principle on the assumption that the system equation contains time delay and the control domain is convex. The related adjoint processes are characterized as solutions to anticipated backward stochastic differential equations in finite-dimensional spaces. Then, the proposed theoretical result is applied to study partially-observed linear-quadratic optimal control problem for stochastic delay system and an explicit observable control variable is given.     

Stochastic Optimal Control Problem in Advertising Model with Delay

This paper investigates the optimal control problem arising in advertising model with delay. The authors reformulate the problem in Hilbert space by stochastic evolution equation and consider the optimal control problem of controlled stochastic evolution system. The necessary and sufficient optimality conditions of the control are established. The proposed approach is different from most existing studies of optimal advertising policy problem with delay. These results are applied to the optimal advertising policy problem under two different structures and the optimal advertising strategies are obtained.     

Stabilization of Continuous-Time Systems Against Stochastic Network Uncertainties: Fundamental Variance Bounds

This paper studies the stabilizability and stabilization of continuous-time systems in the presence of stochastic multiplicative uncertainties. The authors consider multi-input, multi-output(MIMO) linear time-invariant systems subject to multiple static, structured stochastic uncertainties,and seek to derive fundamental conditions to ensure that a system can be stabilized under a mean-square criterion. In the stochastic control framework, this problem can be considered as one of optimal control under state-or input-dependent random noises, while in the networked control setting, a problem of networked feedback stabilization over lossy communication channels. The authors adopt a mean-square small gain analysis approach, and obtain necessary and sufficient conditions for a system to be meansquare stabilizable via output feedback. For single-input, single-output(SISO) systems, the condition provides an analytical bound, demonstrating explicitly how plant unstable poles, nonminimum phase zeros, and time delay may impose a limit on the uncertainty variance required for mean-square stabilization. For MIMO minimum phase systems with possible delays, the condition amounts to solving a generalized eigenvalue problem, readily solvable using linear matrix inequality optimization techniques.     

有包丢失的动态输出反馈奇异网络化系统稳定性分析

基于正则、无脉冲的奇异被控对象,研究了同时具有时延和数据包丢失的动态输出反馈网络控制系统的建模和稳定性问题。 当时延不大于一个采样周期、数据包丢失率一定时,将动态输出反馈网络控制系统建模为数据包丢失率约束的异步动态切换系统,利用切换系统和线性矩阵不等式方法,推导出数据包丢失率约束的系统指数稳定的充分条件,并且给出了系统指数稳定的指数衰减率以及最大容许数据包丢失率。仿真实验说明分析方法和研究结果是有效可行的。     

Numerical Solutions for Optimal Control of Stochastic Kolmogorov Systems

This work is concerned with controlled stochastic Kolmogorov systems. Such systems have received much attention recently owing to the wide range of applications in biology and ecology.Starting with the basic premise that the underlying system has an optimal control, this paper is devoted to designing numerical methods for approximation. Different from the existing literature on numerical methods for stochastic controls, the Kolmogorov systems take values in the first quadrant. That is, each component of the state is nonnegative. The work is designing an appropriate discrete-time controlled Markov chain to be in line with(locally consistent) the controlled diffusion. The authors demonstrate that the Kushner and Dupuis Markov chain approximation method still works. Convergence of the numerical scheme is proved under suitable conditions.     

Optimal control of multisolution ordinary differential equations in the absence of convexity

<正> In this paper,the authors study an optimal control problem governed by a class of multistateordinary differential equations in the absence of convexity.To overcome the difficulty that thecorresponding approximate optimal control problem may have no solution,relaxed controls are introduced.With the help of relaxation theory,Pontryagin's maximum principle for the optimal pairs ofthe original control problem is obtained.In the end of this paper,the authors discuss the applicationof the maximum principle by an example.     

具有时变时延和丢包的网络控制系统H∞优化控制

研究了一类存在时变时延和丢包的网络控制系统(networked control systems, NCS )的H∞优化控制问题。当网络时延和连续丢包有界时,NCS被建模为等效的具有时变时滞的系统,利用Lvapunov Krasovskii泛函和线性矩阵不等式方法,在NCS渐近稳定的基础上给出NCS状态反馈次优和最优H∞控制律的设计方法,求解时不需要使用重复迭代,设计控制器时也无须知道调节参数。仿真表明了此方法的可行性和有效性。     

Optimal Switching Integrity Attacks on Sensors in Industrial Control Systems

In this article, an optimal switching integrity attack problem is investigated to study the response of feedback control systems under attack. The authors model the malicious attacks on sensors as additive norm bounded signals. The authors consider an attacker who is only capable of launching attacks to limited number of sensors once a time and changing the combinations of attacked sensors all over the time. The objective of this paper is to find the optimal switching sequence of these combinations and the optimal attack input. The authors solve this problem by transforming it into a traditional optimal control problem with new control variables vary continuously in the range [0, 1]. The optimal solutions of the new control variables are of bang-bang-type. Therefore, an algebraic switching condition and an optimal attack input can be obtained. Finally, numerical results are provided to illustrate the effectiveness of the methods.     

Optimal Output Feedback Control and Stabilization for NCSs with Packet Dropout and Delay: TCP Case

This paper considers the output feedback control and stabilization problems for network control systems (NCSs) with packet dropout and input delay, and the TCP (transmission control protocol) case is mainly investigated. Specifically, whether the control signal is lost can be acknowledged by the receiver in the NCSs. The main contributions are: 1) For the finite horizon case, the “optimal” output feedback control is derived by using the dynamic programming approach, and it is noted that the separation principle holds for the considered situation; 2) For the infinite horizon case, for the first time, the necessary and sufficient stabilization conditions are derived for NCSs with packet dropout and delay.     

具有模型和实际差异的非线性离散时滞系统最优控制

研究了非线性分布时滞系统的最优控制,提出了一种基于线性分布时滞模型和二次型性能指标问题的迭代算法。在模型和实际存在差异的情况下,该算法通过迭代求解分布时滞线性最优控制问题和参数估计问题,获得原问题的最优解。仿真实例表明该算法的有效性和实用性。     

Decentralized Control of Discrete-Time System with Delay in Mean Field LQR Problem

This paper studies the decentralized optimal control of discrete-time system with input delay,where a large number of agents with the identical decoupling dynamical equations and the coupling cost function through the mean field are considered.The decentralized and centralized optimal controllers are proposed by the optimal tracking control of LQR problem with delay.They are proved that the optimal controllers and the optimal cost function of the centralized and decentralized solutions are equivalent for the optimal control problem.An illustrative example is given to show the efficiency of the decentralized optimal controllers.     

OPTIMAL CONTROL OF A CLASS OF DISTRIBUTED PARAMETER DELAY SYSTEMS

1.IntroductionManyphysicalsystems,suchajsthemodynamics,electrodynamics,populationbiology,aregovernedbydifferentialequations,integrodifferentialequationsormoregenerallyfunctionaldifferentialevolutionequationsonBanachspace.Associatedoptimalcontrolprobl...     

On optimal mean-field control problem of mean-field forward-backward stochastic system with jumps under partial information

This paper considers the problem of partially observed optimal control for forward-backward stochastic systems driven by Brownian motions and an independent Poisson random measure with a feature that the cost functional is of mean-field type. When the coefficients of the system and the objective performance functionals are allowed to be random, possibly non-Markovian, Malliavin calculus is employed to derive a maximum principle for the optimal control of such a system where the adjoint process is explicitly expressed. The authors also investigate the mean-field type optimal control problem for the system driven by mean-field type forward-backward stochastic differential equations (FBSDEs in short) with jumps, where the coefficients contain not only the state process but also its expectation under partially observed information. The maximum principle is established using convex variational technique. An example is given to illustrate the obtained results.     

一类具输入时滞的分布参数系统移动控制

基于移动传感器/执行器网络,研究了一类具有输入时滞的分布参数系统稳定性控制问题。利用抽象发展方程理论、算子半群理论和Lyapunov稳定性定理,设计系统的反馈控制器;再结合移动传感器/执行器的动力学行为,设计其控制力。证明了在反馈控制器和控制力的作用下,分布参数系统在具输入时滞情况下是渐近稳定的。通过数值仿真实验表明,不同的输入时滞,对系统的稳定效果有一定的影响,但在控制力的作用下,系统都能趋于稳态,说明本文中对于具有输入时滞的分布参数系统的控制策略是有效的。     

一类具输入时滞的分布参数系统移动控制

基于移动传感器/执行器网络,研究了一类具有输入时滞的分布参数系统稳定性控制问题。利用抽象发展方程理论、算子半群理论和Lyapunov稳定性定理,设计系统的反馈控制器;再结合移动传感器/执行器的动力学行为,设计其控制力。证明了在反馈控制器和控制力的作用下,分布参数系统在具输入时滞情况下是渐近稳定的。通过数值仿真实验表明,不同的输入时滞,对系统的稳定效果有一定的影响,但在控制力的作用下,系统都能趋于稳态,说明本文中对于具有输入时滞的分布参数系统的控制策略是有效的。     

区间时滞相关不确定奇异系统的鲁棒稳定性和镇定性

研究区间时滞相关的不确定时变时滞奇异系统的鲁棒稳定性和镇定性问题,不确定参数假设是范数有界的。充分利用时滞的下界信息构造Lyapunov函数,用严格的矩阵不等式给出系统对所有的容许不确定满足正则、无脉冲、稳定的新判据。基于这个判据,设计状态反馈控制器使得系统鲁棒稳定。数值例子说明所得结果具有更小的保守性。     

Uniformed model of networked control systems with long time delay

Feedback control systems wherein the control loops are closed through a real-time network are called networked control systems （NCS）. The defining feature of an NCS is that information is exchanged using a network among control system components. Two new concepts including long time delay and short time delay are proposed. The sensor is almost always clock driven. The controller or the actuator is either clock driven or event driven. Four possible driving modes of networked control systems are presented. The open loop mathematic models of networked control systems with long time delay are developed when the system is driven by anyone of the four different modes. The uniformed modeling method of networked control systems with long time delay is proposed. The simulation results are given in the end.