多重不确定的密码体制研究

针对现有密码体制中只有密钥不确定的特点,文章提出了多重不确定密码体制的概念,指出了可能实现的一些途径。文章分析了其优势,指出这类密码体制在大大增强安全性的同时,其可能带来的运算量的增加是可以忽略的。     

Robust stability and stabilization of discrete singular systems with interval time-varying delay and linear fractional uncertainty

The robust stability and robust stabilization problems for discrete singular systems with interval time-varying delay and linear fractional uncertainty are discussed. A new delay-dependent criterion is established for the nominal discrete singular delay systems to be regular, causal and stable by employing the linear matrix inequality (LMI) approach. It is shown that the newly proposed criterion can provide less conservative results than some existing ones. Then, with this criterion, the problems of robust stability and robust stabilization for uncertain discrete singular delay systems are solved, and the delay-dependent LMI conditions are obtained. Finally, numerical examples are given to illustrate the e?ectiveness of the proposed approach.     

Uncertainty modeling and robust minimax LQR control of multivariable nonlinear systems with application to hypersonic flight

For a class of multi‐input and multi‐output nonlinear uncertainty systems, a novel approach to design a nonlinear controller using minimax linear quadratic regulator (LQR) control is proposed. The proposed method combines a feedback linearization method with the robust minimax LQR approach in the presence of time‐varying uncertain parameters. The uncertainties, which are assumed to satisfy a certain integral quadratic constraint condition, do not necessarily satisfy a generalized matching condition. The procedure consists of feedback linearization of the nominal model and linearization of the remaining nonlinear uncertain terms with respect to each individual uncertainty at a local operating point. This two‐stage linearization process, followed by a robust minimax LQR control design, provides a robustly stable closed loop system. To demonstrate the effectiveness of the proposed approach, an application study is provided for a flight control problem of an air‐breathing hypersonic flight vehicle (AHFV), where the outputs to be controlled are the longitudinal velocity and altitude, and the control variables are the throttle setting and elevator deflection. The proposed method is used to derive a linearized uncertainty model for the longitudinal motion dynamics of the AHFV first, and then a robust minimax LQR controller is designed, which is based on this uncertainty model. The controller is synthesized considering seven uncertain aerodynamic and inertial parameters. The stability and performance of the synthesized controller is evaluated numerically via single scenario simulations for particular cruise conditions as well as a Monte‐Carlo type simulation based on numerous cases. It is observed that the control scheme proposed in this paper performs better, especially from the aspect of robustness to large ranges of uncertainties, than some controller design schemes previously published in the literature. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Path-planning strategies for a point mobile automaton moving amidst unknown obstacles of arbitrary shape

The problem of path planning for an automaton moving in a two-dimensional scene filled with unknown obstacles is considered. The automaton is presented as a point; obstacles can be of an arbitrary shape, with continuous boundaries and of finite size; no restriction on the size of the scene is imposed. The information available to the automaton is limited to its own current coordinates and those of the target position. Also, when the automaton hits an obstacle, this fact is detected by the automaton's tactile sensor. This information is shown to be sufficient for reaching the target or concluding in finite time that the target cannot be reached. A worst-case lower bound on the length of paths generated by any algorithm operating within the framework of the accepted model is developed; the bound is expressed in terms of the perimeters of the obstacles met by the automaton in the scene. Algorithms that guarantee reaching the target (if the target is reachable), and tests for target reachability are presented. The efficiency of the algorithms is studied, and worst-case upper bounds on the length of generated paths are produced.Supported in part by the National Science Foundation Grant DMC-8519542.     

粗糙集理论及其在图像处理中的应用*

首先描述了粗糙集理论的基本概念,包括粗糙集知识表示方法和粗糙集约简理论;叙述了粗糙集理论及其与其他非线性理论相结合在图像处理中的应用情况;最后指出了粗糙集理论应用于图像处理的基本思路,并指出将粗糙集理论与其他非线性理论相结合应用于图像处理,将会产生更加有效的结果.     

西江流域压咸风险调度及其时空传递规律研究

枯水期珠江河口咸潮情势日益加重,径流不确定加剧了压咸风险,严重威胁沿线的供水安全。本文基于概率密度分布描述径流不确定性,构建了单源风险调度基本框架。以西江流域五座水库为研究对象,量化了预报误差与压咸风险的响应关系;揭示了压咸风险的时空传递规律;将压咸风险划分为3个等级;确定出各级风险越级传递的临界阈值。研究表明：随预报误差的增大,压咸风险提前且持续天数增加、风险率增大;压咸风险呈逐时段累积和从上游向下游、从支流向干流的时空传递规律;当预报误差超过±16%、±21%时,压咸风险从轻险越级至中险、中险越级至重险。研究成果对于西江流域压咸风险的调控和粤港澳大湾区的供水安全具有重要的应用价值。     

多类型源储协调互动的配电网分布鲁棒优化调度

分布式光伏、风电等可再生能源出力具有较强的随机性和不确定性,其大量并网给配电网的运行带来了极大的挑战。本文提出了一种多类型源储协调互动的配电网分布鲁棒优化调度方法,基于分布鲁棒优化理论,对配电网中传统离散设备、可再生能源以及储能决策进行协调优化,提高配电网运行的经济性和安全性,实现了配电网运行决策保守性与鲁棒性的有效平衡。首先,考虑多类型源储资源的协调互动,建立配电网优化调度模型,并将其转化为混合整数二阶锥规划的形式;其次,利用可再生能源出力场景集进行不确定性刻画,建立分布鲁棒优化模型,并通过列和约束生成算法进行求解;最后,在PG&E69节点系统上进行算例分析,验证了所提方法的可行性与准确性。     

考虑新能源消纳及需求响应不确定性的配电网主从博弈经济调度

针对当前配电网侧风电消纳率较低的问题,运用Stackelberg动态博弈理论,提出一种以配电网侧为主体、负荷侧为从体的主从博弈模型.通过分析用户负荷特性,建立用户负荷特性模型;运用三角模糊数描述需求响应的不确定性,建立价格型需求响应不确定性模型;以配电网侧配电网运行成本最小及风电消纳最大、负荷侧用户电费最低为目标建立配电网主从博弈经济模型,二者通过优化配电网侧的准实时电价策略集及负荷侧需求响应策略集达到博弈均衡;以修改后的IEEE 30节点系统为算例,采用改进型教与学优化算法求得该主从博弈模型的均衡解.算例仿真分析表明,所建模型能够有效提高配电网风电消纳能力,减少配电网运行成本和用户电费,实现主、从体双方社会效益与经济效益最优化.     

基于深度强化学习的光储充电站储能系统优化运行

优化储能充放电策略有利于提升光储充电站运行经济性,但是现有模型驱动的随机优化方法无法全面考虑储能系统的复杂运行特性以及光伏发电功率、电动汽车充电负荷的不确定性.因此,提出一种基于深度强化学习的光储充电站储能系统全寿命周期优化运行方法.首先对储能运行效率模型和容量衰减模型进行精细化建模.然后考虑电动汽车充电需求、光伏出力和电价的不确定性,在满足电动汽车充电需求和光伏消纳的条件下,以光储充电站收益最大化为目标,建立了基于强化学习的储能优化运行问题.考虑到储能充放电决策动作的连续性,采用双延迟深度确定性策略梯度算法进行求解.采用实际历史数据对模型进行训练,根据当前时段状态对储能充放电策略进行实时优化.最后,对所提方法及模型进行测试,并将所提出的方法与传统模型驱动方法进行对比,结果验证了所提方法及模型的有效性.     

Regional mass flux balancing for controlling gentle soil remediation operations

Extraction of heavy metals by accumulating plants is a method which is currently in development for the "gentle" remediation of contaminated agricultural soils (phytoremediation, see [2]). Areal contaminant mass flux balances are basic criteria for the design of such remediations and their control. A framework for the integration of contaminant balances relating the field scale of remediation with the regional scale of soil monitoring networks is provided by the recently developed method PROTERRA [3]. The objective of the study presented in this paper was to test the suitability of PROTERRA for planning and monitoring gentle soil remediations. For this purpose we applied the PROTERRA method to the contaminated agricultural land in and around Dornach, Switzerland, to assess copper flux balances.The calculations showed that atmospheric deposition and the application of pesticides and manure are important pathways for the inputs of copper. The copper export with a special maize cultivar accumulating heavy metals would be about three times higher than the average metal export with crops. A moderate increase of sewage sludge application would lead to a substantial increase of the copper input. Decisions to remediate the soil should take the uncertainty of mass flux balances both on field scale as well as on regional scale into account. Therefore, an important need of further development of the PROTERRA method is the integration of uncertainty analysis on both scales.