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研究一类结构参数不确定性的切换系统的可靠控制问题.这种可靠系统可以抵御执行器出现故障给系统带来的影响.利用凸组合技术,设计可靠控制器和相应的切换策略,使得不仅当执行器正常时而且当一些执行器出现故障时仍保证闭环系统是全局渐近稳定的,最后通过仿真算例验证所设计方法的可行性、有效性. 相似文献
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针对包含时滞的一类非线性不确定系统,在执行器可能发生故障的情况下,研究了此类系统可靠控制器的设计和成本上界的确定问题。从Lyapunov定理出发,经演绎后得到可靠控制器和成本有界需要满足的矩阵不等式,通过利用Schur补定理,将矩阵不等式化为标准的LMI,同时给出了系统控制器和成本上界。闭环控制器能够使得系统在执行器失效时系统对允许的不确定性具有容错能力,且保成本上界的存在。最后通过给出一个系统实例,检验了所提出方法的可应用性。 相似文献
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传感器失效不确定时滞系统指数稳定可靠控制 总被引:1,自引:0,他引:1
针对一类含有时变时滞的不确定参数线性系统,研究了在传感器发生故障情况下系统指数稳定鲁棒可靠控制器设计问题。系统中的参数不确定性满足广义匹配条件,时变时滞及其变化率有界,并假设故障传感器元件的输出为零。经过适当的状态变换,将原系统的指数稳定鲁棒可靠控制问题转化为另一个等价系统的鲁棒可靠控制问题。根据Lyapunov稳定性理论,得到了系统存在指数稳定鲁棒可靠控制器应满足的一个矩阵不等式。为了便于数值求解,将该矩阵不等式转化为线性矩阵不等式(LMI),并给出了可靠控制器的设计方法和步骤。利用该文方法设计的指数稳定鲁棒可靠控制器能够使得时滞系统对于任意允许的不确定性以及传感器失效都具有指定衰减度的渐近稳定性。数值算例说明了所提出设计方法的有效性。 相似文献
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研究了含有故障执行器的线性不确定时滞系统的可靠保性能鲁棒控制问题.执行器故障模型概括了执行器正常、执行器部分退化和执行器完全失效三种情况,系统的性能函数是带有故障输入项的积分二次函数.利用Lyapunov稳定理论及矩阵不等式方法,得到了系统存在可靠保性能鲁棒控制器的代数矩阵不等式(AMI)形式的充分条件和控制器的设计方法,给出了系统的一个可保性能的表达式.基于LMI方法,给出了AMI的一个求解算法.一个数值例子说明结论的可行性. 相似文献
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不确定时滞系统的指定衰减度保代价可靠控制 总被引:1,自引:1,他引:0
针对一类含有时变时滞的不确定参数线性系统;研究了在执行器发生故障情况下系统具有指定衰减度的保代价可靠控制器设计问题。系统中的参数不确定性满足广义匹配条件;时变时滞及其变化率有界;执行器失效采用增益故障模型。系统的性能函数是含有指数项和故障输入项的积分二次型函数。经过适当的状态变换;将原系统的指定衰减度保代价可靠控制问题转化为另一个等价系统的保代价可靠控制问题。根据Lyapunov稳定性理论;得到了系统存在指定衰减度保代价可靠控制器应满足的一个矩阵不等式;进一步将这个矩阵不等式转化为线性矩阵不等式(LMI);并给出了系统的保代价表达式。利用论文方法设计的指定衰减度保代价可靠控制器能够使得时滞系统对于任意允许的不确定量以及执行器故障都保持鲁棒可靠指数稳定;并且使系统具有保代价的性能指标。 相似文献
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研究一类不确定组合时滞系统的状态反馈鲁棒分散可靠控制问题。系统包含状态时滞,控制输入时滞和参数不确定性。目的是设计分散线性无记忆状态反馈控制器,使得对于任意容许的不确定性以及在每一个子系统中预先指定的执行器子集合内执行器的失效,相应的闭环系统渐近稳定。最后给出一个数值例子验证了本文所给结果的有效性。 相似文献
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研究具有不可靠通信信道和有限带宽约束的Markov跳变系统的混合事件/时间驱动H∞控制问题.为处理有限带宽约束,首先,基于驱动误差、辅助变量和切换时刻设计分布式混合事件/时间驱动机制以确定每个传感器节点的驱动时刻;其次,提出一种新的TOD(try-once-discard)调度协议以保证在驱动时刻仅有唯一的传感器节点接入网络.此外,将不可靠通信信道导致的数据丢包现象建模为伯努利分布,基于驱动时刻的数据传输情况构建随机序列和调度矩阵序列,对数据接收情况进行建模.以此为基础,利用线性矩阵不等式(linear matrix inequality,LMI)得到保证闭环Markov跳变系统在无扰动时随机稳定和有扰动时有限增益L2随机稳定的充分性条件,并给出反馈增益阵的设计方法.最后,通过实例仿真验证所提出方法的有效性. 相似文献
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Rita de Cassia M. Rodrigues & Solon V. de Carvalho 《International Transactions in Operational Research》2001,8(2):235-248
We study a queueing system where both inter-arrival and service times are distributed according to phase-type distributions. This system is modeled as a Markov decision process with full and partial information. The objective is to minimize the long-run average cost of the system. Numerical results are presented. 相似文献
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As an effective strategy to facilitate delivering customized products within short lead time, hybrid manufacturing via a two-stage process has received attention from academia and industry. In this paper, we study a two-stage hybrid manufacturing system in which semifinished products are manufactured in a make-to-stock fashion in the first stage and end-products are produced from semifinished goods in a make-to-order (MTO) mode in the second stage. The rate of MTO production can be controlled within given limits, depending on the status of the system. The primary goal of this paper is to study a policy for coordinating order admission, MTO production rate, and inventory replenishment controls. Formulating the problem as a Markov decision process model, we characterize the structure of optimal control policies to maximize the long-run average profit. Using a numerical experiment, we study how the flexibility in MTO production rate affects the optimal policy and the optimal profit. We also examine the effect of the number of alternative MTO production rates on the optimal profit. We propose three heuristic policies implementable for general cases. The first heuristic describes two linear switching functions for admission and production controls and a selection rule for MTO production rate control. The second heuristic specifies fixed thresholds for the control decisions using the local information. The third heuristic presents linear switching functions that approximate the optimal threshold curves. Unlike second and third heuristics, the first heuristic does not require a grid search to determine the control parameters. We implement numerical studies to examine the marginal impact of system parameters and the effect of the number of alternative MTO production rates on the performance of the heuristics. Compared to the optimal policy, the average percentage performance of the first and third heuristics is less than 1% for both numerical studies. On the other hand, the average percentage performance of the second heuristic is larger than 3%, and it exceeds 10% for a set of particular problem examples. 相似文献
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A primary challenge of agent-based policy learning in complex and uncertain environments is escalating computational complexity with the size of the task space(action choices and world states) and the number of agents.Nonetheless,there is ample evidence in the natural world that high-functioning social mammals learn to solve complex problems with ease,both individually and cooperatively.This ability to solve computationally intractable problems stems from both brain circuits for hierarchical representation of state and action spaces and learned policies as well as constraints imposed by social cognition.Using biologically derived mechanisms for state representation and mammalian social intelligence,we constrain state-action choices in reinforcement learning in order to improve learning efficiency.Analysis results bound the reduction in computational complexity due to stateion,hierarchical representation,and socially constrained action selection in agent-based learning problems that can be described as variants of Markov decision processes.Investigation of two task domains,single-robot herding and multirobot foraging,shows that theoretical bounds hold and that acceptable policies emerge,which reduce task completion time,computational cost,and/or memory resources compared to learning without hierarchical representations and with no social knowledge. 相似文献
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P. Kess 《Control Engineering Practice》1993,1(5)
The objective of this paper is to give a holistic picture of the economic control as part of the management function in the process production organizations. The systematics described is a three dimensional life cycle model of the systems development. The first dimension defines the levels of decision making in the organization. The second dimension describes the various functions of the production organization and the third dimension formulates different abstraction models of the system in question. 相似文献
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Antonio Pietrabissa 《International journal of control》2013,86(12):2290-2301
ALOHA random access protocols are distributed protocols based on transmission probabilities, that is, each node decides upon packet transmissions according to a transmission probability value. In the literature, ALOHA protocols are analysed by giving necessary and sufficient conditions for the stability of the queues of the node buffers under a control vector (whose elements are the transmission probabilities assigned to the nodes), given an arrival rate vector (whose elements represent the rates of the packets arriving in the node buffers). The innovation of this work is that, given an arrival rate vector, it computes the optimal control vector by defining and solving a stochastic control problem aimed at maximising the overall transmission efficiency, while keeping a grade of fairness among the nodes. Furthermore, a more general case in which the arrival rate vector changes in time is considered. The increased efficiency of the proposed solution with respect to the standard ALOHA approach is evaluated by means of numerical simulations. 相似文献
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A theoretical as well as conceptual framework for the use of learning algorithms in telephone traffic routing is given. The approach is distinctly different from the mathematical programming methods generally used in such cases. Learning algorithms at the network nodes update their strategies for routing traffic on the basis of success or failure in completing calls. The entire system is described as a Markov process and different learning schemes are shown to lead to different flow patterns in the steady state. 相似文献
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The paper is devoted to the first order delayed linear system with relay output controlled by the proportional-integral (PI) regulator. The deterministic system exhibits stable oscillations, and, since the system itself is stable, it can be suitable to switch off the controller if there are no disturbances during a long time interval. In the present work, the random disturbances are modelled by a Poisson stream of impulses, and the goal is to determine the instants of switching on (off) of the PI controller. After several assumptions and quantization of the time axis, we construct the new optimal control problem which is successfully solved with the help of the dynamic programming approach. 相似文献
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研究多维组件, 单一产品的双需求型面向订单装配(Assemble-to-order, ATO)系统. 产品需求为延期交货型, 当其不被满足时将产生缺货等待成本; 而独立组件需求为销售损失型, 其不被满足时将产生缺货损失成本. 该问题可以抽象成一个动态马尔科夫决策过程(Markov decision process, MDP), 通过对双需求模型求解得到状态依赖型最优策略, 即任一组件的最优生产--库存策略由系统内其他组件的库存水平决定. 研究解决了多需求复杂ATO系统的生产和库存优化控制问题. 提出在一定条件下, 组件的基础库存值可以等价于最终产品需求的库存配给值. 组件的基础库存值与库存配给值随系统内其他组件库存的增加而增加, 而产品需求的库存配给值随系统组件库存和产品缺货量的增加而减少. 最后通过数值实验分析缺货量及组件库存对最优策略结构的影响, 并得到了相应的企业生产实践的管理启示. 相似文献
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Many media processing applications create a load that varies significantly over time. Hence, if such an application is assigned a lower processing-time budget than needed in its worst-case load situation, deadline misses are likely to occur. This problem can be dealt with by designing media processing applications in a scalable fashion. A scalable media processing application can run in multiple qualities, leading to correspondingly different resource demands. The problem we consider is to find an accompanying quality control strategy, which minimizes both the number of deadline misses and the number of quality changes, while maximizing the quality of processing. We present an initial approach to the above problem by modeling it as a Markov decision process (MDP). Our model is based on measuring relative progress at milestones. Solving the MDP results in a quality control strategy that can be applied during runtime with only little overhead. We evaluate our approach by means of a practical example, which concerns a scalable MPEG-2 decoder. 相似文献