结构不确定线性时滞系统的无记忆鲁棒镇定

针对状态和控制均存在时滞的一类结构不确定线性时滞系统 ,讨论了鲁棒镇定问题 ,当不确定性参数满足有界性条件时 ,提出了一种无记忆线性状态反馈控制律 ,可保证闭环系统具有二次稳定性     

一类不确定时滞混沌系统的全局鲁棒自适应神经网络同步控制器设计

研究一类不确定时滞混沌系统的全局鲁棒自适应神经网络同步控制器设计,其系统中的不确定时滞项不是简单的线性有界条件,而是允许其存在高阶项,因此具有全局特性．在控制器的设计上;首先通过选取合适的径向基函数（RBF）神经网络的权向量去逼近时滞系统中的未知连续有界部分;然后在RBF神经网络输出的基础上,选用一个鲁棒自适应控制器来趋近时滞系统的不确定部分;同时,利用Lyapunov稳定性理论对混沌同步的条件给出了论证;最后,数据仿真的结果表明该方法的有效性．     

时滞对主动悬架幅频特性的影响

为探究时滞对主动悬架控制性能的影响,在分析时滞对闭环控制系统传递特性影响的基础上,建立了考虑控制输入时滞的悬架系统模型,并以该模型为研究对象,理论分析了时滞对天棚主动控制和加速度阻尼主动控制下悬架幅频特性的影响,最后通过数值仿真进行了分析与验证。结果表明:时滞导致车体加速度的传递率增大,同时还造成一、二阶主振型频率的变化,并在中、高频区域产生多个共振峰;较大的时滞会造成主动悬架振动控制效果的明显恶化甚至系统的失稳。     

非线性系统的鲁棒H∞输出反馈控制

研究了带有时变参数不确定的非线性系统的鲁棒 H∞ 输出反馈控制问题 ,此不确定性包含在所有系统矩阵中并受到某种积分函数限制。建立了非线性鲁棒 H∞ 控制问题与相应一般非线性系统的 H∞ 控制问题之间的等价关系 ,从而通过求解不包含参数不确定的辅助非线性系统的标度 H∞ 控制问题来获得非线性鲁棒 H∞ 控制问题的解。     

鲁棒D-稳定输出反馈H∞控制方法及其仿真

考虑了一类不确定系统的具有闭环极点约束的输出反馈H∞控制,运用基于线性矩阵不等式的方法(LMI),由二次D-稳定导出了鲁棒D-稳定的输出反馈控制器存在的充分条件和设计方法.该方法虽然具有一定的保守性,但求解方便有效,且易于扩展到多目标鲁棒控制.最后,仿真说明了该设计方法的正确性.     

主被动混合隔振的虚拟样机技术

为了能够更准确方便得到主被动混合隔振系统的特性与设计参数,利用虚拟样机技术对主被动混合隔振系统进行了主动控制仿真研究。首先,对主被动混合隔振平台进行了理论计算与模态分析;然后,通过ADAMS软件创建了混合隔振平台的虚拟样机,并将其导入至MATLAB/SMULINK中搭建了主被动混合隔振系统,通过变步长法对主被动混合隔振系统进行了次级通道辨识,并在此基础上基于多通道Fx-LMS算法进行了主被动混合隔振的效果分析。仿真结果表明:利用虚拟样机技术对主被动混合隔振系统进行主动控制取得了较好的控制效果,为主被动混合隔振物理样机的设计与制造提供了新的思路与方法。     

某岸舰导弹最优伺服系统的补偿控制

本文提供了一种在多环最优反馈控制系统基础上的补偿控制,以更好地改善系统的性能,降低系统对参数变化的灵敏度,提高抗扰性。分析表明,这种结构的系统具有鲁棒(Robust)性,结构简单、易行。仿真结果也证实了这一点。     

一类不确定非线性时滞系统的鲁棒容错控制

针对一类非线性时滞系统,基于Lyapunov稳定性理论,讨论了不确定参数系统的鲁棒容错控制问题。当故障在失效的传感器以及失效的执行器发生时,且非线性不确定性满足一定的增益条件,通过基于线性矩阵不等式(LMI)方法各自给出了故障在传感器和执行器失效发生时,闭环系统渐近稳定的存在条件及相应控制器的设计方法。一个设计算例的仿真结果表明了该方法是有效的。     

一类非光滑非线性系统的鲁棒输出跟踪控制

研究一类具有不可控不稳定线性化的非光滑和本质非线性系统的鲁棒输出跟踪问题.应用Lyapunov稳定性和"加幂积分器"方法构造出一个鲁棒非线性状态控制器,解决了系统的全局鲁棒输出跟踪问题,且所求控制律能确保跟踪误差充分小,闭环系统所有信号全局有界.仿真结果证明了所提出方法的有效性.     

带有状态滞后的连续广义系统的鲁棒正实控制﹡

对带有状态滞后的连续广义系统的严格正实性进行了分析,得出了这类系统渐近稳定且严格正实的充分条件,该充分条件与滞后无关。进一步地,对这类系统带有不确定性和控制量的情况进行了研究。提出了一种基于线性状态反馈控制的鲁棒正实控制器设计方法,使得控制器设计可以通过求解线性矩阵不等式方便地加以解决,且保证了闭环系统的严格正实性。最后,通过实例分析说明所提出的鲁棒正实控制器设计方法是可行的、有效的。     

Optimal burn‐in procedure for periodically inspected systems

Burn‐in is a widely used method to improve the quality of products or systems after they have been produced. In this paper, we study burn‐in procedure for a system that is maintained under periodic inspection and perfect repair policy. Assuming that the underlying lifetime distribution of a system has an initially decreasing and/or eventually increasing failure rate function, we derive upper and lower bounds for the optimal burn‐in time, which maximizes the system availability. Furthermore, adopting an age replacement policy, we derive upper and lower bounds for the optimal age parameter of the replacement policy for each fixed burn‐in time and a uniform upper bound for the optimal burn‐in time given the age replacement policy. These results can be used to reduce the numerical work for determining both optimal burn‐in time and optimal replacement policy. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

Fluctuations of the optimal advertising and inventory policy: A qualitative analysis

This paper discusses the properties of the inventory and advertising policy minimizing the expected discounted cost over a finite horizon in a dynamic nonstationary inventory model with random demand which is influenced by the level of promotion or goodwill. Attention is focused on the relation between the fluctuations over time of the optimal policies and the variations over time of the factors involved, i.e., demand distributions and various costs. The optimal policies are proved to be monotone in the various factors. Also, three types of fluctuations over time of the optimal policies are discussed according to which factor varies over time. For example, if over a finite interval, the random demand increases (stochastically) from one period to the next, reaches a maximum and then decreases, then the optimal inventory level will do the same. Also the period of maximum of demand never precedes that of maximum inventory. The optimal advertising behaves in the opposite way and its minimum will occur at the same time as the maximum of the inventory. The model has a linear inventory ordering cost and instantaneous delivery of stocks; many results, however, are extended to models with a convex ordering cost or a delivery time lag.     

Indirect robust control of agile missile via Theta-D technique

An agile missile with tail fins and pulse thrusters has continuous and discontinuous control inputs. This brings certain difficulty to the autopilot design and stability analysis. Indirect robust control via Theta-D technique is employed to handle this problem. An acceleration tracking system is formulated based on the nonlinear dynamics of agile missile. Considering the dynamics of actuators, there is an error between actual input and computed input. A robust control problem is formed by treating the error as input uncertainty. The robust control is equivalent to a nonlinear quadratic optimal control of the nominal system with a modified performance index including uncertainty bound. Theta-D technique is applied to solve the nonlinear optimal control problem to obtain the final control law. Numerical results show the effectiveness and robustness of the proposed strategy.     

Upper and lower bounds for a pattern bombing problem

This paper includes two simple analytic formulas for kill probability that are applicable in circumstances where shots should be fired in a pattern. The two formulas bracket the maximum kill probability achievable with an optimal pattern. The upper bound corresponds to an optimal nonfeasible pattern, and the lower bound to a nonoptimal feasible pattern.     

Replacement models under additive damage

A production system which generates income is subject to random failure. Upon failure, the system is replaced by a new identical one and the replacement cycles are repeated indefinitely. In our breakdown model, shocks occur to the system in a Poisson stream. Each shock causes a random amount of damage, and these damages accumulate additively. The failure time depends on the accumulated damage in the system. The income from the system and the cost associated with a planned replacement depend on the accumulated damage in the system. An additional cost is incurred at each failure in service. We allow a controller to replace the system at any stopping time T before failure time. We will consider the problem of specifying a replacement rule that is optimal under the following criteria: maximum total long-run average net income per unit time, and maximum total long-run expected discounted net income. Our primary goal is to introduce conditions under which an optimal policy is a control limit policy and to investigate how the optimal policy can be obtained. Examples will be presented to illustrate computational procedures.     

Minimizing the false alarm rate in systems with transient abnormality

We consider a stochastic partially observable system that can switch between a normal state and a transient abnormal state before entering a persistent abnormal state. Only the persistent abnormal state requires alarms. The transient and persistent abnormal states may be similar in appearance, which can result in excess false alarms. We propose a partially observable Markov decision process model to minimize the false alarm rate, subject to a given upper bound on the expected alarm delay time. The cost parameter is treated as the Lagrange multiplier, which can be estimated from the bound of the alarm delay. We show that the optimal policy has a control‐limit structure on the probability of persistent abnormality, and derive closed‐form bounds for the control limit and present an algorithm to specify the Lagrange multiplier. We also study a specialized model where the transient and persistent abnormal states have the same observation distribution, in which case an intuitive “watchful‐waiting” policy is optimal. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 320–334, 2016     

A refined deterministic linear program for the network revenue management problem with customer choice behavior

We present a new deterministic linear program for the network revenue management problem with customer choice behavior. The novel aspect of our linear program is that it naturally generates bid prices that depend on how much time is left until the time of departure. Similar to the earlier linear program used by van Ryzin and Liu (2004), the optimal objective value of our linear program provides an upper bound on the optimal total expected revenue over the planning horizon. In addition, the percent gap between the optimal objective value of our linear program and the optimal total expected revenue diminishes in an asymptotic regime where the leg capacities and the number of time periods in the planning horizon increase linearly with the same rate. Computational experiments indicate that when compared with the linear program that appears in the existing literature, our linear program can provide tighter upper bounds, and the control policies that are based on our linear program can obtain higher total expected revenues. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

A note on the single-machine scheduling problem with minimum weighted completion time and maximum allowable tardiness

This paper analyzes the Smith-heuristic for the single-machine scheduling problem where the objective is to minimize the total weighted completion time subject to the constraint that the tradiness for any job does not exceed a prespecified maximum allowable tardiness. We identify several cases of this problem for which the Smith-heuristic is guaranteed to lead to optimal solutions. We also provide a worst-case analysis of the Smith-heuristic; the analysis shows that the fractional increase in the objective function value for the Smith-heuristic from the optimal solution is unbounded in the worst case.     

Iterative coloring extension of a maximum clique

In this paper we present an improved branch and bound algorithm for the vertex coloring problem. The idea is to try to extend the coloring of a maximum clique to its adjacent vertices. If this succeeds, its successive neighbors are considered; in case of failure (i.e., in the case the initial colors are not sufficient), working on the subgraph induced by the maximum clique and its neighborhood, the lower bound is improved by seeking for an optimal coloring of this subgraph by branch and bound. The process is repeated iteratively until the whole graph is examined. The iterative scheme exploits a further lower bound obtained by integrating a simple algorithm into the maximum clique search, and a new method to compute upper bounds on subgraphs. Furthermore, a new branching rule and a method for the selection of the initial maximum clique are presented. Extensive computational results and comparisons with existing exact coloring algorithms on random graphs and benchmarks are given. © 2001 John Wiley & Sons, Inc. Naval Research Logistic 48: 518–550, 2001