Asynchronous adaptive output feedback sliding mode control for Takagi-Sugeno fuzzy Markovian jump systems with actuator faults

In this article, the problem of asynchronous adaptive dynamic output feedback sliding mode control (SMC) for a class of Takagi-Sugeno (T-S) fuzzy Markovian jump systems (MJSs) with actuator faults is investigated. The asynchronous dynamic output feedback control strategy is employed, as the nonsynchronization phenomenon of jump modes exists between the plant and the controller. A novel asynchronous adaptive SMC approach is proposed to solve the synthesis problem for T-S fuzzy MJSs with actuator faults. Sufficient conditions for stochastic asymptotic stability of T-S fuzzy MJSs are given. Under the designed asynchronous adaptive SMC scheme, the effects of actuator faults and external disturbance can be completely compensated and the reachability of sliding surface is ensured. Finally, an example is provided to demonstrate the effectiveness of the proposed design techniques.     

Damage propagation and strength prediction of a single-lap interference-fit laminate structure

Frontiers of Mechanical Engineering - Experimental and finite element research was conducted on the bolted interference fit of a single-lap laminated structure to reveal the damage propagation...     

Stacking behavior of the close-packed Ta-atom planes and its effects on formation of “hybrid grains” in TaC0.66-0.7 ceramics

In previous works, it was found hard to synthesize “phase pure” ζ-Ta₄C_3-z at relatively low temperatures even by prolonged heating, though ζ-Ta₄C_3-z was believed stable till decomposition at ~2130°C. When the samples were subjected to TEM, vast richness of locally disordered structures in close relation with stacking of the close-pacted Ta-atom planes was observed. Although kinetic factors including diffusion of C atoms/vacancies and re-stacking of the Ta-atom planes explain the densely disordered structures, the richness of local disorders is a scenario that shows cohabitant of the cubic, rhombohedral, and hexagonal structures in a single grain, i.e. formation of a “hybrid grain” consisted of the three symmetries, indicating a transitional or intermediate stage before complete formation of the final phase of rhombohedral ζ-Ta₄C_3-z. This time tantalum carbide ceramics TaC_x with C:Ta atomic ratios x = 0.66 and 0.7 were prepared by reaction hot pressing of TaC and Ta powder mixtures. 5–30 mol% Cu/Ag additives and heat treatments were used to reproduce “hybrid grains” to facilitate further TEM and HRTEM observations on the disordered hybrid grains to argue for the transitional/intermediate stage. The cohabitant cubic, rhombohedral, and hexagonal structures in single grains may also help explain the difficulty in identification of the various phases by XRD in the transitional/intermediate stage of ζ-Ta₄C_3-z reaction. Microstructural evolution and fracture toughness of the composites were also investigated.     

A new interval diagnosis method: Application to the spacecraft rendezvous phase of the Mars sample return mission

This paper presents a new optimized interval principal component analysis applied to detect and isolate actuators faults of an autonomous spacecraft involved in the rendezvous phase of the Mars sample return mission. Based on the exploitation of various arithmetic and interval analysis properties, the new interval model is built by solving the interval eigenpairs problem via a resolution of a parametric linear programming problem. The detection and isolation phases are performed by extending the classic methods to interval-valued data. The proposed method is applied to detect and isolate actuators faults that can occur on the spacecraft's thrusters. Based on data provided by a “high fidelity” industrial simulator developed by Thales Alenia Space, the obtained results proved the effectiveness of the proposed interval fault diagnosis method on detecting and isolating thrusters' faults.     

浅谈煤矿数据的分析与应用

当今社会科技发展快、信息流通量大,人们之间的交流越来越密切,大数据这个高科技时代的产物也应运而生。煤炭作为工业发展的重要组成部分,其发展关系着整个工业的发展。如今,许多现代大型煤矿已能将井下设备信息上传到地面,在地面就可直观的看到设备当前运行的情况,从而更可靠的进行安全生产。通过结合实例将上传的设备信息数据进行整理和分析,从而预测设备的运行状况,提出建设性建议。同时对加强煤矿安全生产、促进煤炭行业现代化建设、提高煤矿的经济效益和社会效益具有重要的意义。     

Topological preservation techniques for nonlinear process monitoring

This work proposes a novel approach for the offline development and online implementation of data-driven process monitoring (PM) using topological preservation techniques, specifically self-organizing maps (SOM). Previous topological preservation PM applications have been restricted due to the lack of monitoring and diagnosis tools. In the proposed approach, the capabilities of SOM are further extended so that all aspects of PM can be performed in a single environment. First for fault detection, using SOM's vector quantization abilities, an SOM-based Gaussian mixture model (GMM) is proposed to define the normal region. For identification, an SOM-based contribution plot is proposed to identify the variables most responsible for the fault. This is done by analyzing the residual of the faulty point and an SOM model of the normal region used in fault detection. The data points are projected on the model by locating the best matching unit (BMU) of the point. Finally, for fault diagnosis a procedure is formulated involving the concept of multiple self-organizing maps (MSOM), creating a map for each fault. This allows the ability to include new faults without directly affecting previously characterized faults. A Tennessee Eastman Process (TEP) application is performed on dynamic faults such as random variations, sticky valves and a slow drift in kinetics. Previous studies of the TEP have considered particular feed-step-change faults. Results indicate an excellent performance when compared to linear and nonlinear distance preservation techniques and standard nonlinear SOM approaches in fault diagnosis and identification.     

An overview on fault diagnosis and nature-inspired optimal control of industrial process applications

Fault detection, isolation and optimal control have long been applied to industry. These techniques have proven various successful theoretical results and industrial applications. Fault diagnosis is considered as the merge of fault detection (that indicates if there is a fault) and fault isolation (that determines where the fault is), and it has important effects on the operation of complex dynamical systems specific to modern industry applications such as industrial electronics, business management systems, energy, and public sectors. Since the resources are always limited in real-world industrial applications, the solutions to optimally use them under various constraints are of high actuality. In this context, the optimal tuning of linear and nonlinear controllers is a systematic way to meet the performance specifications expressed as optimization problems that target the minimization of integral- or sum-type objective functions, where the tuning parameters of the controllers are the vector variables of the objective functions. The nature-inspired optimization algorithms give efficient solutions to such optimization problems. This paper presents an overview on recent developments in machine learning, data mining and evolving soft computing techniques for fault diagnosis and on nature-inspired optimal control. The generic theory is discussed along with illustrative industrial process applications that include a real liquid level control application, wind turbines and a nonlinear servo system. New research challenges with strong industrial impact are highlighted.     

Acute kidney injury in China

China has a large population and bears a heavy burden of kidney diseases. Acute kidney injury (AKI) is increasingly prevalent in China and is associated with severe morbidity and mortality. The inadequacies of early diagnosis and management remain the major challenges to Chinese nephrologists. There is an urgent need for a nationwide, or even a global effort to increase an awareness of the devastating effects of AKI, to develop professional preventive strategies, as well as to achieve early diagnosis and early intervention. In this article, we review the increasing incidence of AKI and complexity behind prevention and management, focusing on differences in various clinical settings in China.     

蚌埠市淮河南岸某高层建筑CFG桩复合地基应用探讨

以淮河南岸一级阶地某高层建筑采用CFG桩复合地基工程实例,通过利用工程地质参数复核计算、静载荷试验、沉降观测等验证资料,来探讨说明CFG桩复合地基在该区高层建筑使用的安全适用性。     

Fault estimation and accommodation for networked control systems with nonuniform sampling periods

This paper deals with the problem of fault estimation and accommodation for a class of networked control systems with nonuniform uncertain sampling periods. Firstly, the reason why the adaptive fault diagnosis observer cannot be applied to networked control systems is analyzed. Based on this analysis, a novel robust fault estimation observer is constructed to estimate both continuous‐time fault and system states by using nonuniformly discrete‐time sampled outputs. Furthermore, using the obtained states and fault information, a nonuniformly sampled‐data fault tolerant control law is designed to preserve the stability of the closed‐loop system. The proposed scheme can not only guarantee the impact of continuous‐time uncertainties and discrete‐time sampled estimation errors on the faulty system to satisfy a H _∞ performance index but also repress the negative effect of the unknown intersample behavior of continuous‐time fault by use of an inequality technique. Finally, simulation results are included to demonstrate the feasibility of the proposed method. Copyright © 2014 John Wiley & Sons, Ltd.