Robust optimal operation of continuous catalytic reforming process under feedstock uncertainty

The continuous catalytic regenerative (CCR) reforming process is one of the most significant sources of hydrogen production in the petroleum refining process. However, the fluctuations in feedstock composition and flow rate could significantly affect both product distribution and energy consumption. In this study, a robust deviation criterion based multi-objective optimization approach is proposed to perform the optimal operation of CCR reformer under feedstock uncertainty, with simultaneous maximization of product yields and minimization of energy consumption. Minimax approach is adopted to handle these uncertain objectives, and the Latin hypercube sampling method is then used to calculate these robust deviation criteria. Multi-objective surrogate-based optimization methods are next introduced to effectively solve the robust operational problem with high computational cost. The level diagram method is finally utilized to assist in multi-criteria decision-making. Two robust operational optimization problems with different objectives are solved to demonstrate the effectiveness of the proposed method for robust optimal operation of the CCR reforming process under feedstock uncertainty.     

无线电综合测试仪校准装置的研究及其不确定度分析

This calibration device of radio comprehensive tester is studied and established in this paper. It solves the verification and calibration of a large number of general-purpose radio comprehensive testers. The calibration device consists of four calibration sub- systems and calibration software system, including RF generator, audio generator, audio analyzer and RF analyzer. It also researches on the configuration of standard equipment and analyzes the uncertainty of the calibration devices, ensuring accurate and reliable val- ue transfer.     

烟道流量计量标准装置

为了解决我国烟道流量计的量值溯源问题,中国计量科学研究院建立了烟道流量计量标准装置。装置使用可溯源至标准转盘的激光多普勒测速仪作为原级标准器,采用激光多普勒流速剖面扫描和超声流量计波动修正的方式测量标准流量,经校准的8声道超声流量计为工作级标准表,具备了908~104840m3/h的测量能力,扩展不确定度为0.62%(k=2),可对最大口径为1m的流量计进行校准。装置下游测试段包括圆形管段和矩形管段,能够开展烟道流量计测量性能的研究。     

Assessment of the different sources of uncertainty in a SWAT model of the River Senne (Belgium)

Although rainfall input uncertainties are widely identified as being a key factor in hydrological models, the rainfall uncertainty is typically not included in the parameter identification and model output uncertainty analysis of complex distributed models such as SWAT and in maritime climate zones. This paper presents a methodology to assess the uncertainty of semi-distributed hydrological models by including, in addition to a list of model parameters, additional unknown factors in the calibration algorithm to account for the rainfall uncertainty (using multiplication factors for each separately identified rainfall event) and for the heteroscedastic nature of the errors of the stream flow. We used the Differential Evolution Adaptive Metropolis algorithm (DREAM_(zs)) to infer the parameter posterior distributions and the output uncertainties of a SWAT model of the River Senne (Belgium). Explicitly considering heteroscedasticity and rainfall uncertainty leads to more realistic parameter values, better representation of water balance components and prediction uncertainty intervals.     

State-space ARIMA for supply-chain forecasting

ARIMA is seldom used in supply chains in practice. There are several reasons, not the least of which is the small sample size of available data, which restricts the usage of the model. Keeping in mind this restriction, we discuss in this paper a state-space ARIMA model with a single source of error and show how it can be efficiently used in the supply-chain context, especially in cases when only two seasonal cycles of data are available. We propose a new order selection algorithm for the model and compare its performance with the conventional ARIMA on real data. We show that the proposed model performs well in terms of both accuracy and computational time in comparison with other ARIMA implementations, which makes it efficient in the supply-chain context.     

基于滑模的运载器主动段俯仰通道姿控系统设计

与传统比例-积分-微分（PID）控制方法相比，滑模控制（SMC）方法可以比较容易地将不确定性纳入控制器设计中，从而增强系统的鲁棒性。探索了SMC技术在运载器主动段姿态控制中的工程应用，首先通过分析基于趋近律的SMC系统，提出了降低不连续切换项系数的需求，然后研究了基于干扰上界的SMC方法。三通道小偏差仿真结果验证了两种方法的控制效果，表明第2种控制器的鲁棒性更好，稳态误差小，同时发动机喷管摆角需求较小。     

Transport Map sampling with PGD model reduction for fast dynamical Bayesian data assimilation

The motivation of this work is to address real-time sequential inference of parameters with a full Bayesian formulation. First, the proper generalized decomposition (PGD) is used to reduce the computational evaluation of the posterior density in the online phase. Second, Transport Map sampling is used to build a deterministic coupling between a reference measure and the posterior measure. The determination of the transport maps involves the solution of a minimization problem. As the PGD model is quasi-analytical and under a variable separation form, the use of gradient and Hessian information speeds up the minimization algorithm. Eventually, uncertainty quantification on outputs of interest of the model can be easily performed due to the global feature of the PGD solution over all coordinate domains. Numerical examples highlight the performance of the method.     

Distributed learning consensus control based on neural networks for heterogeneous nonlinear multiagent systems

This paper considers a novel distributed iterative learning consensus control algorithm based on neural networks for the control of heterogeneous nonlinear multiagent systems. The system's unknown nonlinear function is approximated by suitable neural networks; the approximation error is countered by a robust term in the control. Two types of control algorithms, both of which utilize distributed learning laws, are provided to achieve consensus. In the provided control algorithms, the desired reference is considered to be an unknown factor and then estimated using the associated learning laws. The consensus convergence is proven by the composite energy function method. A numerical simulation is ultimately presented to demonstrate the efficacy of the proposed control schemes.     

Accuracy of wind energy forecasts in Great Britain and prospects for improvement

The metric representing the wind energy forecast error, when reported as a percent, is calculated quite differently than the error metrics for electricity transmission, electricity load, or in other industries such as manufacturing when they are also reported as a percent. The resulting calculated metric is quite different from what would be reported if the method utilized elsewhere was employed. This paper examines the possible forecast assessment and operational challenges associated with this finding. Concerning the prospects for improvement, the errors reported in MW of energy have a systematic component. With this insight, we developed a model to improve accuracy.