流程工业最优生产控制的递阶流率模型

基于流程工业生产系统特性,构造新的递阶流率控制模型,对目标泛函的积分上限重 新定义,引入新的状态变量,在最优生产时间标准下给出了递阶滚动优化算法框架.仿真结果 表明该生产策略更易于工程实现.     

事件触发间歇通讯下多智能体系统的固定时间分布式优化

针对多智能体系统的分布式优化问题,提出一种新的事件触发非周期间歇通讯控制方法,并研究该控制方法下系统的固定时间收敛性.首先,考虑一类更一般的分布式优化问题,其优化目标是局部目标函数的凸组合.其次,为了减少控制过程中智能体之间的通讯花费,设计一种新的事件触发间歇控制协议.通过引入两个辅助动力系统,并运用固定时间稳定性理论、代数图论和不等式放缩技巧,证明智能体的状态在固定时间内达到一致并渐近收敛到优化问题的最优解.结合事件触发条件以及间歇控制机制,排除控制过程中的Zeno行为.最后,通过数值仿真验证所得结论的有效性.     

基于滚动优化的对偶控制策略

考虑具有未知参数的随机系统的最优控制问题.提出了一种新的基于滚动优化的对偶控制算法.在动态规划泛函方程中,用Kalman滤波对系统的状态进行估计;用线性化方法对阶段损失函数中的后验概率进行近似,然后,用滚动优化策略对控制与学习之间的耦合关系进行解耦.从而获得了原不可解泛函方程的解析递推表达式和一个易于实施的控制律的解析解.用一个例子说明了控制律的性能,仿真结果表明:该控制律具有良好的对偶性质,在学习和控制之间实现了较好的平衡.     

基于二维混合模型的最优重复控制方法

针对一类线性系统,提出一种基于连续／离散二维混合模型的最优重复控制设计新方法．通过独立地 考虑重复控制系统连续的控制行为与离散的学习行为,建立了重复控制系统的连续／离散二维混合模型,并将重复 控制器设计问题转化为一类连续／离散二维系统的镇定问题．在此基础上,应用最优控制原理,对给定的性能指标 泛函,获得了最优重复控制律．通过调节性能指标泛函中的相关参数,可以对控制和学习行为进行独立的调节．最 后,通过数值仿真验证了所提方法的有效性．     

变分法与现代控制理论

变分法是求泛函极值的一种方法。泛函是函数的函数。譬如，控制系统的输出为控制系统输入的函数，而输入函数又是时间的函数，又如控制系统的目标函数，通常是状态变量与控制变量加权的函数。而状态变量与控制变量又是时间的函数。当我们控制的目标是最短时间或者最低能耗的时候，可以把控制问题归结为求一个泛函的极值曲线问题。由此可见，变分法对现代控制理论是相当重要的。现代控制理论的核心内容是最优控制。最优，一般是指某一性能指标为最优，而不可能要求项项指标为最优，而某一性能指标的最优，往往是要求在满足某种限制条件下，达…     

变采样网络控制系统的最优保性能控制

研究了一类不确定时延网络控制系统的最优保性能控制问题.针对线性时不变控制对象,控制器和控制对象采用时间-事件驱动,系统成为变采样网络控制系统,考虑在不确定时延小于或者等于一个变采样周期时,基于动态输出反馈对变采样网络控制系统进行建模,利用线性矩阵不等式研究了系统的保性能控制,并设计了保性能控制率和最优保性能控制率,最后给出实例表明在最优保性能控制率的控制下系统稳定.     

CGF系统中的飞机智能决策模型的研究与实现

计算机生成兵力系统(CGF)中导弹模型作为舰载武器模型的最重要组成部分,其实体建模精度和弹道模拟一直是我们关心的问题.精确制导武器制导律研究中,当略去导弹和制导系统的惯性,将导弹当作可控制的质点时,确定出的导弹飞向目标的弹为理想弹道.在计算机生成兵力系统实际需求下,随着制导精度要求的提高,理想的弹道和理想的比例导引已不能满足要求.该文据比例导引的差分方程,在对比例导引进行三维弹道仿真的基础上,分别对基于二次型的最优制导律、考虑弹体动态特性的二次型最优制导律进行了三维弹道仿真,绘制出了可直观显示的弹道特性,计算了导弹与目标遭遇时间,并对结果进行了比较分析.得出考虑弹体动态特性的二次型最优制导律性能最优的结论.     

约束非线性系统稳定经济模型预测控制

考虑约束非线性系统,提出一种新的具有稳定性保证的经济模型预测控制（Economic model predictive control,EMPC）策略.由于经济性能指标的非凸性和非正定性,引入关于经济最优平衡点的正定辅助函数.利用辅助函数的最优值函数定义原始EMPC优化问题的稳定性约束.应用终端约束集、终端代价函数和局部控制器三要素,建立闭环系统关于经济最优平衡点的渐近稳定性和渐近平均性能.进一步,结合多目标理想点概念,将提出的控制策略用于多个经济性能指标的优化控制,得到稳定多目标EMPC策略.最后,以连续搅拌反应器为例,比较仿真结果验证本文策略的有效性.     

基于支持向量机的一类非线性系统预测控制

针对一类具有输出反馈耦合的离散非线性系统,将过程的非线性部分通过支持向量机转化为全局线性状态空间模型,并在目标函数中引入系统状态的变化,给出一种类似于离散PI最优调节器的新型预测控制器.该方法不需要在线辨识系统参数,因为系统的内模已转换成全局离线模型.由于引入了新的优化目标函数,该控制器的控制效果和鲁棒性优于仅考虑预测输出误差的传统预测控制器.仿真结果表明,它也优于经典离散PI最优调节器.     

含状态和输入时滞的离散时间系统的近似最优跟踪控制

针对状 态和控制输入均含有时滞的离散时间系统, 提出最优跟踪控制的设计方法. 通 过引入一种新的状态向量, 将含有状态和控制输入时滞的离散时间系统转化为 含有虚拟扰动项的无时滞离散时间系统. 根据最优控制理论, 构造离散Riccati矩阵方 程和离散Stein矩阵方程的序列, 并证明该解序列一致收敛于变换后的离散时间系统的最优跟 踪控制策略. 利用最优控制的逐次逼近设计方法, 得到最优跟踪控制的近似 解, 并给出求解最优跟踪控制律的算法. 仿真算例表明了所提出最优跟踪控制 方法的有效性.     

Optimal tracker for unreliable manufacturing systems

This paper deals with the inventory-production control problem where the produced items are assumed to deteriorate at a rate that depends on the demand rate of the production system. The state of this production system is assumed to be described by a continuous-time Markov process taking values in a finite discrete space. The inventory production control problem is formulated as a stochastic optimal control problem. The optimal policy that solves the optimal control problem is obtained in terms of a set of coupled Riccati equations. The guaranteed cost problem is also treated. A numerical example is provided to show the usefulness of the proposed model.     

A comprehensive model for software rejuvenation

Recently, the phenomenon of software aging, one in which the state of the software system degrades with time, has been reported. This phenomenon, which may eventually lead to system performance degradation and/or crash/hang failure, is the result of exhaustion of operating system resources, data corruption, and numerical error accumulation. To counteract software aging, a technique called software rejuvenation has been proposed, which essentially involves occasionally terminating an application or a system, cleaning its internal state and/or its environment, and restarting it. Since rejuvenation incurs an overhead, an important research issue is to determine optimal times to initiate this action. In this paper, we first describe how to include faults attributed to software aging in the framework of Gray's software fault classification (deterministic and transient), and study the treatment and recovery strategies for each of the fault classes. We then construct a semi-Markov reward model based on workload and resource usage data collected from the UNIX operating system. We identify different workload states using statistical cluster analysis, estimate transition probabilities, and sojourn time distributions from the data. Corresponding to each resource, a reward function is then defined for the model based on the rate of resource depletion in each state. The model is then solved to obtain estimated times to exhaustion for each resource. The result from the semi-Markov reward model are then fed into a higher-level availability model that accounts for failure followed by reactive recovery, as well as proactive recovery. This comprehensive model is then used to derive optimal rejuvenation schedules that maximize availability or minimize downtime cost.     

Digital twin-based opti-state control method for a synchronized production operation system

The intelligent manufacturing strategy and customer demand have mutually promoted each other. Also, the production mode is shifting towards customized production, and more rental resources or services are introduced to the production system, therefore, the systems are becoming more complex. Compared with traditional production systems, such systems have some new features, this work calls this type of system as a synchronized production operation system (SPOS). Under such circumstances, production systems are influenced by more frequent uncertainties, and the planning-based production decision and control approach is no longer applicable. The opti-state control (OsC) method is proposed to help SPOS keep in an optimal state when uncertainties affect the system. Besides, a digital twin-based control framework (DTCF) is designed for getting the full element information needed for decision making. Based on the comprehensive information of the production system obtained by the DTCF, the OsC method is introduced to the virtual control layer to formulate the optimal target guiding the path of the system in real time through the dynamic matching mechanism (qualitative perspective). Then multi-stage synchronized control with analysis target cascading (ATC) method is used to get the local optimal state decisions (quantitative perspective). From both qualitative and quantitative aspects to ensure the system is under an optimal target path for optimal operation procedure. At last, a case study in a large-size paint making company in China is used to validate the effectiveness of the approach.     

A problem in jointly optimal production and advertising decisions

In this paper, a production control model proposed by Holt, Modigliani, Muth and Simon and a marketing model suggested by Nerlove and Arrow, are combined to produce an optimal control problem with two state variables, two control variables and inequality constraints on these variables. The optimal production rate and advertising expenditures over time are determined using the maximum principle. Due to the complex nature of the necessary conditions, the numerical technique known as the initial-value shooting method, is used to generate optimal trajectories. A numerical example is presented to illustrate the solution.     

多时滞离散系统鲁棒稳定性优化模型

给出一类时变不确定状态多时滞离散系统,通过构造Lyapunov函数,仅需求解一个关于线性矩阵不等式组(LMIs)的优化模型,就可设计出保证闭环系统稳定的无记忆状态反馈鲁棒控制器,最后通过数值例子说明该方法的正确性和有效性。     

Design of optimal PID controller using hybrid differential evolution and particle swarm optimization with an aging leader and challengers

This paper presents a new algorithm designed to find the optimal parameters of PID controller. The proposed algorithm is based on hybridizing between differential evolution (DE) and Particle Swarm Optimization with an aging leader and challengers (ALC-PSO) algorithms. The proposed algorithm (ALC-PSODE) is tested on twelve benchmark functions to confirm its performance. It is found that it can get better solution quality, higher success rate in finding the solution and yields in avoiding unstable convergence. Also, ALC-PSODE is used to tune PID controller in three tanks liquid level system which is a typical nonlinear control system. Compared to different PSO variants, genetic algorithm (GA), differential evolution (DE) and Ziegler–Nichols method; the proposed algorithm achieve the best results with least standard deviation for different swarm size. These results show that ALC-PSODE is more robust and efficient while keeping fast convergence.     

Manufacturing flow control and preventing maintenance: a stochasticcontrol approach

A stochastic control model for simultaneously planning production and maintenance in a flexible manufacturing system (FMS) is proposed, and an efficient technique for computing the optimal control policy is developed. The model extends previous formulations by including an age-dependent machine failure rate and by allowing the control to influence some jump rates (namely the preventive maintenance activities). By using an adaptation to the case of piecewise-deterministic systems of the approximation technique initially proposed by H.J. Kushner (1977) in the realm of the optimal control of diffusions, one shows how it is possible to computer the optimal control for a two-machine system     

需求随机波动下多设备批量生产系统的视情维护策略研究

针对需求随机波动情况下多设备批量生产系统的设备维护问题,提出了一种基于滚动生产计划和设备退化状况的视情维护策略。首先,通过滚动时域规划方法预测不同产品的随机需求并在此基础上以总生产成本最小确定滚动生产计划。其次,在每一滚动生产周期开始前检测系统中各设备的退化水平,利用Gamma过程描述退化增量,以最小维护成本率确定当前退化状态下各设备的最佳维护时间,同时为避免生产过程中断利用提前延后维护策略对预防维护进行动态调整。在系统层,利用生产转换时机对需要维护的组件进行组合维护。再次,引入时间约束和服务水平约束,建立批量生产与视情维护的联合优化模型,以总成本最小为目标,确定实际生产计划和维护计划。最后,通过算例以整个生产计划期内的总成本和故障次数为度量验证了所提出的多设备批量生产系统视情维护策略的有效性。     

基于小邻域系和特征基团的人脸皮沟老化检测

人脸老化过程极为复杂,皮沟特征极其细微,并且伴随大量噪声。传统的皮沟匹配方法不能很好地刻画出细微老化的特征变化,人脸老化的检测准确度不强。提出一种基于小邻域系和特征基团的人脸老化检测算法,建立了人脸图像小邻域系和特征基团的对应关系,构造了运动参数联合概率分布的能量函数来反映人脸皮沟参数之间的约束关系。最后采用模拟退火算法对老化特征在约束关系下的相关关联求出最优解,得到不同老化程度下各皮沟特征点的关联性。实验表明:该方法能很好地对人脸不同状态下的皮沟老化特征进行识别,检测结果更加准确,且准确度更高。     

The stochastic sliding mode variable structure guidance laws based on optimal control theory

A stochastic sliding-mode variable structure guidance law involving optimal control theory is presented for the missile target intercept model, in which state noise, uncertain system parameters, target movement and measured noise are considered. This guidance law synthesizes the merits of optimal guidance law with line-of-sight rate convergence and sliding-mode guidance law with strong robustness. Through theoretic analysis, it is proved that the sliding mode hyperplane is sub-achievable in the closed loop system. The numerical results show the effectiveness of the proposed control algorithm.