On the theory of economic MPC: ELOC and approximate infinite horizon EMPC

In recent years, the notion of Economic Model Predictive Control (EMPC) has gained significant interest. Despite a marked improvement in economic performance, it has been shown that this performance will degrade substantially if implemented with a horizon that is not sufficiently large. In the current effort, it is shown that if applied to a particular reaction process, EMPC performance will abruptly collapse at a critical horizon size. To alleviate this issue, we develop an Infinite Horizon EMPC (IH-EMPC) formulation. While this IH-EMPC problem is computationally intractable, it does lead to an approximation of the optimal policy. The resulting Approximate IH-EMPC (AIH-EMPC) is identical to the original finite horizon EMPC, but includes a final cost term that represents the objective function from the finite horizon to infinity. With two example systems, a chemical reactor and a power system with energy storage, it is shown that the AIH-EMPC policy is virtually insensitive to its computational horizon size.     

Eliciting and measuring hesitance in decision-making

Hesitance is an innate human psychological phenomenon pervasive in our daily life. Although it is very complex and still not fully understood, there have been many studies related to this interesting topic. In this study, we proposed two fundamental problems about hesitance: the first is the generating problem, which is related to how to elicit hesitance information from human thinking; the second is the measuring problem, which is related to how to devise effective and reasonable methods to measure hesitance degrees from given hesitance information. With these two fundamental questions, we first discussed and analyzed several examples in real life involving hesitance, showing that it can indeed be recorded and represented. Then we roughly classified the hesitance information into two major classes: static hesitance and dynamic hesitance. Some simple and interesting methods were proposed to elicit hesitance, and more reasonable methods were proposed to measure the hesitance degree from the two classes of hesitance information. All methods that have been discussed in this study try to avoid complexity in every aspect while reserving strictness and reasonability; therefore, the present study provides suitable information for practitioners with different backgrounds.     

基于模糊综合评判和层次分析法的中子管故障风险评估

中子管是一种用途广泛的关键部件，然而目前国产中子管的可靠性水平与国外相比还有一定差距，难以满足各行业的使用需求。本文分析了中子管的主要故障模式，采用模糊综合评判和层次分析法对中子管故障进行了多级模糊综合评判，并对中子管故障风险进行了评估。结果表明，中子管总体故障风险水平中等，故障风险前3位的部件为靶、氘氚储存器和加速极，在设计和使用中应重点关注靶释放氦气，靶膜氧化，氘氚储存器吸气剂局部破损，绝缘瓷管破损，加速极离子加速、聚焦不稳定等故障。     

Structural load alleviation using distributed delay shaper: Application to flexible aircraft

Lightweight flexible aircraft suffers from unwanted oscillatory vibrations during aircraft manoeuvres. A recently developed distributed-delay signal (DZV) shaper is therefore proposed to be applied as a feedforward controller to alleviate the manoeuvre loads, as an alternative to traditional structural filters used routinely in this context. Structural filters are essentially linear low-pass filters with bandwidth below the significant flexible modes, applied to control signals generated either by the pilot’s direct input or by the flight control system. It has been showed that if instead a properly tuned signal shaper is used, better performance can be achieved: first, the target modes are significantly attenuated while the responsiveness of the aircraft is less compromised and secondly, the oscillatory nature of the vibrations are reduced. The high fidelity simulation results on a full scaled dynamic model of a highly flexible blended wing–body (BWB) aircraft show that in comparison to traditional structural filters, signal shapers significantly reduce the wing root loading (forces and moments) which provides potential structural benefits.     

冠状动脉系统的微分积分终端滑模混沌抑制

冠状动脉系统的混沌现象会导致严重的健康问题。以非线性冠状动脉系统为研究对象，建立了不确定性冠状动脉系统动力学模型，提出了不确定性冠状动脉系统的微分积分终端滑模混沌抑制方法，针对该模型的不确定性设计了扰动观测器，根据Lyapunov理论证明了所设计控制系统的稳定性，通过仿真实验验证了所提出的混沌抑制方法的有效性和可行性。     

基于神经网络算法的井下裂缝诊断与堵漏技术

在钻井过程中，常常钻遇不同宽度的井下地层裂缝。钻遇裂缝时容易发生钻井液漏失现象，甚至发生钻井液失返现象，严重影响了安全、高效钻井。目前裂缝封堵的方法常存在封堵成功率不高、堵漏承压能力低的问题，其中一个重要的原因是对井下地层的裂缝宽度等特征认识不清。基于地层裂缝产生的岩石力学机理，确定影响裂缝宽度关键的6个力学和工程因素，并利用神经网络计算的非线性、大数据特点建立了井下地层裂缝宽度的分析模型，模型包含输入层、输出层和3个隐藏层。通过该模型诊断井下裂缝宽度，提高了计算精度，平均误差仅为2.09%，最大误差为5.88%，解决钻井现场仅凭经验判断裂缝误差较大和依靠成像测井成本较高的问题。同时根据神经网络模型诊断得到的裂缝宽度优化堵漏材料的粒径配比，提高了裂缝内的架桥封堵强度和架桥的稳定性，封堵层的承压能力达到12.8 MPa，反向承压能力达到4.5 MPa。现场堵漏试验最高憋压10 MPa，经过封堵作业后大排量循环不漏，达到了裂缝性地层高效堵漏的目的，堵漏一次成功。      

淮河入江水道行洪能力分析

入江水道是淮河下游最大的泄洪河道,承担着淮河上中游70%以上的洪水泄入长江。根据1961—2018年大洪水期间的实测资料,利用水位流量法计算分析入江水道的泄洪能力和防洪能力。结果表明:因历史客观条件限制以及4个梯级控制河段整治的难度与复杂性,在不同时期各控制河段的行洪能力呈现各自不同的特点;经过多年持续有效治理,河道行洪能力整体得到提高;由近年来实测资料推算,各控制河段的行洪能力基本达到设计要求。对入江水道行洪能力的分析为淮河下游区的防汛抗洪和降低特大洪水威胁提供借鉴和参考,对区域经济社会又好又快发展具有现实意义。     

电驱液压式大截面导线压接设备自动化研究

现有的压接设备可控性差、操作复杂,导致压接质量因人而异。针对此问题,提出了基于DDVC技术的导线压接设备自动化控制方案,建立了速度控制系统数学模型,应用Simulink进行仿真,分析系统性能。建立了基于DEFORM的耐张线夹压接实验模型,获得了耐张线夹压接的最佳加载速度曲线,并以此作为压接设备速度控制系统的Simulink仿真模型输入,对压接过程进行了仿真分析。结果表明:开环控制时系统存在一定的超调,加入PID控制后可有效抑制超调;所设计的压接设备可很好地跟随最佳压接曲线,跟随误差仅为0. 904 mm·s-1。研究成果对改进压接设备、提高压接质量提供了新的解决方案。