Efficient parameterisation of nonlinear system models: a comment on Nöel and Schoukens (2018)

Abstract

Nöel, J. P., & Schoukens, J. [2018. Grey-box state-space identification of nonlinear mechanical vibrations. International Journal of Control, 91, 1–22] discuss a methodology for the discrete-time state-space identification of nonlinear systems and apply this to experimental data from the well known Silverbox nonlinear circuit, producing a model characterised by 13 parameters. This model explains the data very well but the parameter estimates are not well defined in the optimisation results, with the very large confidence bounds suggesting that the model is over-parameterised. This comment shows that this is indeed the case and that the data can be explained equally well by an alternative continuous-time, State-Dependent Parameter (SDP) transfer function model with only 6 parameters, the estimates of which are well defined with very tight confidence bounds. The comment also raises questions about how the model form for nonlinear systems such as the Silverbox should be identified and suggests that the Data-Based Mechanistic (DBM) approach to modelling has some advantages in this regard.     

Variation in the effect of system usage and individual impact: A meta-regression of empirical findings

The relationship between system usage and individual impact has received considerable attention in prior studies. However, the results for the relationship have been mixed. This study hypothesizes that the variation in the effect of system usage on individual impact may be attributed to characteristics of the research contexts. This research examines the effects of voluntariness of use, number of organizations, number of respondents, type of respondents, and information system type, while controlling for geographic region and industry sector using meta-regression methods to examine the findings from 74 studies published between 1992 and 2018. Implications for research and practice are discussed.     

城市轨道交通供电系统新技术研究

供电系统是轨道交通重要的子系统,城市轨道交通对供电系统要求较高。为提高城市轨道交通供电系统的技术水平和运行质量,对智能传感器、大数据、故障预测与健康管理等城市轨道交通供电系统新技术进行了研究。     

悬挂系统参数对轨交车辆运行平稳性的影响分析

介绍了轨交车辆悬挂系统的组成与作用,分析了轨交车辆运行平稳性及其指标。以某型轨交客车为研究对象,应用SIMPACK软件建立车辆动力学模型,分析悬挂系统参数对轨交车辆运行平稳性的影响。通过分析,得到空气弹簧刚度、阻尼系数及其它悬挂关键参数对轨交车辆运行平稳性的影响规律。     

自动扶梯智能安防系统的设计

为了预防自动扶梯发生安全事故,设计了一种基于人工智能的自动扶梯智能安防系统。这一系统利用视频数据采集平台采集乘客数据,应用机器视觉及人工智能技术对乘客的姿态与行为进行主动识别,针对乘客的危险行为给出异常报警,在出现危险状态时触发声光报警器,控制自动扶梯减速或停止运行。这一系统通过有线或无线网络将数据传输至云平台,监管部门可基于手机客户端进行实时监控。特种设备监督管理部门、检验机构、维护保养单位、产权单位等可通过这一系统掌握自动扶梯运行状况。应用所设计的自动扶梯智能安防系统,可以显著提高自动扶梯安全事故预防水平和应急处理能力。     

A digital-twin visualized architecture for Flexible Manufacturing System

The new generation of industrial 4.0 intelligent manufacturing system consists of Human-Cyber-Physical System (HCPS), integrating human with cyber and physical systems. In manufacturing, a digital-twin visualization architecture is to solve the human-machine interaction problem that concerns digital-twin modeling on the Cyber-Physical (C-P) side and on the Human-Cyber side. Although there are many related research and applications, there lacks attention in terms of full life cycle functional services and lightweight architecture. This paper presents a general architecture of digital-twin visualization for flexible manufacturing systems (FMS). How the digital-twin C-P modeling of multi-source heterogeneous information can be described is investigated and how the 3D visualized human-machine interaction with digital-twin scenario information is explored in the proposed architecture. Besides, the visualization method of high-value information, relating to the life cycle planning, design, debugging and service stages, is studied and discussed thoroughly. Also, a digital-twin modeling concept of "Geometric information (G)-Historical samples (H)-Object attribute (O)-Snapshot collection (S)-Topology constraint (T)" (GHOST) is proposed, and methods for developing virtual digital-twin scenes architecture are presented. Based on the proposed modeling concept of GHOST for digital-twin, prototypes have been developed for the general platform of digital-twin RESTful services and the cross-platform general visual mock-up software. Experimental results show that this method is effective in the FMS lifecycle in various aspects.     

Comparison of OWAS,RULA and REBA for assessing potential work-related musculoskeletal disorders

This study compared three representative observational methods for assessing musculoskeletal loadings: Ovako Working Posture Analysis System (OWAS), Rapid Upper Limb Assessment (RULA), and Rapid Entire Body Assessment (REBA). The comparison was based on 209 cases of upper-body musculoskeletal disorders (MSDs) diagnosed by medical doctors. The most awkward/stressful posture in each participant's tasks was assessed using these techniques. Postural loadings were rated more highly by the RULA than by the OWAS and REBA (p < 0.01). The chi-square test and logistic regression analysis showed that only RULA grand score and action level, and REBA action level were associated with MSD work-relatedness (p < 0.01, p < 0.05, and p < 0.05, respectively). The percentage concordant values of the logistic model for the RULA grand score and action level were 52.4% and 44.8%, respectively, while the percentage concordant value for the REBA action level was 22.1%. Therefore, the RULA may be the best system for estimating the postural loads and work-relatedness of MSDs.Relevance to industryWork-related musculoskeletal disorders are the leading cause of workplace disability in the developed countries. For preventing the disorders, quantification of musculoskeletal loads is required.     

Optimization of PEMFC system operating conditions based on neural network and PSO to achieve the best system performance

PEMFC system is a complex new clean power system. Based on MATLAB/Simulink, this paper develops a system-level dynamic model of PEMFC, including the gas supply system, hydrogen supply system, hydrothermal management system, and electric stack. The neural network fits the electric stack model to the simulation data. The effects of different operating conditions on the PEMFC stack power and system efficiency are analyzed. Combining the power of the reactor and the system efficiency to define the integrated performance index, the particle swarm optimization (PSO) algorithm is introduced to optimize the power density and system efficiency of the PEMFC with multiple objectives. The final optimal operating point increases the power density and system efficiency by 1.33% and 12.8%, respectively, which maximizes the output performance and reduces the parasitic power.     

Calculating the shading reduction coefficient of photovoltaic system efficiency using the anisotropic sky scattering model

The front-row shading reduction coefficient is a key parameter used to calculate the system efficiency of a photovoltaic (PV) power station. Based on the Hay anisotropic sky scattering model, the variation rule of solar radiation intensity on the surface of the PV array during the shaded period is simulated, combined with the voltage–current characteristics of the PV modules, and the shadow occlusion operating mode of the PV array is modeled. A method for calculating the loss coefficient of front shadow occlusion based on the division of the PV cell string unit and Hay anisotropic sky scattering model is proposed. This algorithm can accurately evaluate the degree of influence of the PV array layout, wiring mode, array spacing, PV module specifications, and solar radiation on PV power station system efficiency. It provides a basis for optimizing the PV array layout, reducing system loss, and improving PV system efficiency.     

Optimal operating conditions to maximize the net power of polymer electrolyte membrane fuel cells: The stack-system interface of a commercial 18 kW module

A new, experimental method based on air flow rate rather than current is presented to optimize operating parameters for the stacks and systems of proton exchange membrane fuel cells (PEMFCs) for maximizing their net power. This approach is illustrated for a commercial 18 kW PEMFC module. The impact of contamination pressure drop across the cathode air filter is also investigated on the compressor behavior. It is further shown that a 4V reduction in the compressor voltage reduces its power consumption by 9.1%. Using the 3D graphs of the power-pressure-flow data, it is found that the stack pressure of 180 kPaa is superior to the higher tested pressures as it enhances the net power by 7.0 and 13.7% at different conditions. Application of the present study will lead to the development of PEMFCs with higher power output by optimizing stack pressure, stoichiometry and air flow to properly deliver the system design specifications.