A multilevel sampled‐data approach for resilient navigation and control of autonomous systems

Autonomous systems are rapidly becoming an integrated part of the modern life. Safe and secure navigation and control of these systems present significant challenges in the presence of uncertainties, physical failures, and cyber attacks. In this paper, we formulate a navigation and control problem for autonomous systems using a multilevel control structure, in which the high‐level reference commands are limited by a saturation function, whereas the low‐level controller tracks the reference by compensating for disturbances and uncertainties. For this purpose, we consider a class of nested, uncertain, multiple‐input–multiple‐output systems subject to reference command saturation, possibly with nonminimum phase zeros. A multirate output‐feedback adaptive controller is developed as the low‐level controller. The sampled‐data (SD) design of this controller facilitates the direct implementation on digital computers, where the input/output signals are available at discrete time instances with different sampling rates. In addition, stealthy zero‐dynamics attacks become detectable by considering a multirate SD formulation. Robust stability and performance of the overall closed‐loop system with command saturation and multirate adaptive control are analyzed. Simulation scenarios for navigation and control of a fixed‐wing drone under failures/attacks are provided to validate the theoretical findings.     

Event-triggered decentralized adaptive fault-tolerant control of uncertain interconnected nonlinear systems with actuator failures

This paper investigates the event-triggered decentralized adaptive tracking problem of a class of uncertain interconnected nonlinear systems with unexpected actuator failures. It is assumed that local control signals are transmitted to local actuators with time-varying faults whenever predefined conditions for triggering events are satisfied. Compared with the existing control-input-based event-triggering strategy for adaptive control of uncertain nonlinear systems, the aim of this paper is to propose a tracking-error-based event-triggering strategy in the decentralized adaptive fault-tolerant tracking framework. The proposed approach can relax drastic changes in control inputs caused by actuator faults in the existing triggering strategy. The stability of the proposed event-triggering control system is analyzed in the Lyapunov sense. Finally, simulation comparisons of the proposed and existing approaches are provided to show the effectiveness of the proposed theoretical result in the presence of actuator faults.     

矿用电机车脉冲调速的失控及故障处理

可控硅脉冲调速方式具有启动牵引力大,调速均匀,无电能损耗,能实现无级启动等特点,极大地改善了矿用电机车的启动和调速性能。但在可控硅脉冲调速过程中出现的失控现象,常会使电机车损坏或者造成运输事故。因此,分析脉冲调速中的失控故障现象,并且采取相应的处理措施,才能保证矿用电机车的正常运行,以实现煤矿的安全生产。     

龙游大型古洞室群变形破坏方式及加固方法研究

位于中国浙江省西部龙游县的龙游大型古地下洞室群由24个洞室组成,该发现引起了国内外有关专家的关注。对该洞室群进行了多次现场工程地质调查,发现该洞室群已产生了程度不一的破坏,其破坏方式主要表现为洞顶及岩柱的破坏。对完整洞室1#～5#洞而言,也存在着一定的安全隐患。调查发现,在这5个洞室内,洞顶、边墙上的裂缝较为发育,其中1#洞洞顶靠近柱子周围部分、1#,2#洞公共墙上、2#洞洞顶以及3#,4#洞西边墙上的裂缝均较为发育,对洞室群的整体稳定极为不利。为了更好地保护这一人类文化瑰宝,采用FLAC3D数值计算,对洞室变形破坏机理进行了研究。在此基础上,以1#,2#洞为例,本着安全第一,整旧如旧的原则,提出了以支顶为主的加固方法。     

120m混凝土烟囱质量事故处理

某动力厂 12 0m高混凝土烟囱采用滑模施工 ,在 73 3～ 97 7m标高处 ,烟囱中心偏差严重超标 ,造成质量事故。在事故处理过程中 ,利用原有滑模体系将该段混凝土壁顺利拆除 ,并采取措施保证了施工质量     

Benefits of using basic,imprecise or uncertain data for elaborating sewer inspection programmes

One key goal of sewer inspection programmes is to target segments in the worst condition. Despite the development of deterioration models, the influence of available data on models’ predictive power has not been studied in depth yet. In this article, numerical experiments have been conducted to answer three main questions: (1) How can the data most probably available within a utility be used to define an effective inspection programme? (2) Can we use an auxiliary variable in order to compensate effects of missing data on inspection programmes? (3) Is it worth to accept a degree of uncertainty within data instead of not having them? In other words, is it preferable to have uncertainty instead of incompleteness within utility database? In order to respond to these questions, we considered an asset stock and then degraded the information by introducing uncertainty, imprecision and incompleteness within, to form a utility's database. The results show that significant improvement of inspection programmes could be achieved by using the most probably available data within utilities. We also show that using the notion of ‘district’ can provide efficient results when the most informative factor ‘age’ is not available. Finally, it is shown that having uncertain data is preferable to having incompleteness.     

Emergency rush repair task scheduling of distribution networks in large-scale blackouts

This paper focuses on the emergency rush-repair task scheduling of distribution networks in power grid emergencies. As there are many characteristics in distribution network emergency rush-repair such as large number of rush repair points, diverse but with limited repair resources and urgent repair time, this paper takes constraint conditions, such as a variety of execution modes and repair resources into consideration during the model building process of the emergency rush repair scheduling, and we study emergency repair strategies, such as using the emergency generator vehicle, nearby repair strategy and ordinary repair strategy. In order to obtain the optimal solution and satisfy the constraints of the distribution network repair model, this paper improves the traditional serial schedule generation mechanism to a distribution network repair serial schedule generation mechanism by using improved SA algorithm and hierarchical optimization method to search the optimal solution. Finally, we use the model to an example and analyze it. It is validated that the two schedule generation mechanisms that use nearby repair strategy and ordinary repair strategy are both effective. Both the advantages and disadvantages of two mechanisms, and the feasibility and rationality of the model are analyzed in this paper.     

Barriers to energy efficiency in shipping: A triangulated approach to investigate the principal agent problem

Energy efficiency is a key policy strategy to meet some of the challenges being faced today and to plan for a sustainable future. Numerous empirical studies in various sectors suggest that there are cost-effective measures that are available but not always implemented due to existence of barriers to energy efficiency. Several cost-effective energy efficient options (technologies for new and existing ships and operations) have also been identified for improving energy efficiency of ships. This paper is one of the first to empirically investigate barriers to energy efficiency in the shipping industry using a novel framework and multidisciplinary methods to gauge implementation of cost-effective measures, perception on barriers and observations of barriers. It draws on findings of a survey conducted of shipping companies, content analysis of shipping contracts and analysis of energy efficiency data. Initial results from these methods suggest the existence of the principal agent problem and other market failures and barriers that have also been suggested in other sectors and industries. Given this finding, policies to improve implementation of energy efficiency in shipping need to be carefully considered to improve their efficacy and avoid unintended consequences.     

Design structure matrix (DSM) method application to issue of modeling and analyzing the fault tree of a wind energy asset

The perpetual energy production of a wind farm could be accomplished (under proper weather conditions) if no failures occurred. But even the best possible design, manufacturing, and maintenance of a system cannot eliminate the failure possibility. In order to understand and minimize the system failures, the most crucial components of the wind turbines, which are prone to failures, should be identified. Moreover, it is essential to determine and classify the criticality of the system failures according to the impact of these failure events on wind turbine safety. The present study is processing the failure data from a wind farm and uses the Fault Tree Analysis as a baseline for applying the Design Structure Matrix technique to reveal the failure and risk interactions between wind turbine subsystems. Based on the analysis performed and by introducing new importance measures, the “readiness to fail” of a subsystem in conjunction with the “failure riskiness” can determine the “failure criticality.” The value of the failure criticality can define the frame within which interventions could be done. The arising interventions could be applied either to the whole system or could be focused in specified pairs of wind turbine subsystems. In conclusion, the method analyzed in the present research can be effectively applied by the wind turbine manufacturers and the wind farm operators as an operation framework, which can lead to a limited (as possible) design‐out maintenance cost, failures' minimization, and safety maximization for the whole wind turbine system.     

Crankshaft failure analysis of a boxer diesel motor

This paper reports a failure mode analysis of a boxer diesel engine crankshaft. Crankshafts are components which experiment severe and complex dynamic loadings due to rotating bending combined with torsion on main journals and alternating bending on crankpins. High level stresses appear on critical areas like web fillets, as well as the effect of centrifugal forces and vibrations. Since the fatigue fracture near the crankpin-web fillet regions is one of the primary failure mechanisms of automotive crankshafts, designers and researchers have done the best for improving its fatigue strength. The present failure has occurred at approximately 2000 manufactured engines, and after about 95,000 km in service. The aim of this work is to investigate the damage root cause and understand the mechanism which led to the catastrophic failure. Recommendations for improving the engine design are also presented.