基于闭环控制策略的负载谐振型臭氧发生器电源

介质阻挡放电型臭氧发生器负载呈容性,随负载外加电压的升高,间隙放电逐渐增强,其总的负载等效电容逐渐变大。针对负载的这一特点,提出了一种基于逆变器输出电流进行闭环频率跟踪控制的高频逆变电源方案,详细分析了该控制策略的特点,并研制了实验样机,进行了实验验证,得出应用该方案的电源具有结构简单、工作频率变化范围小、系统参数容易选择、可靠性高等优点。     

纱线张力检测与控制技术的研究现状与展望

总结纱线张力检测与控制技术的研究现状及发展趋势.阐述了纱线"三辊式"张力检测的原理,对当前国内外有关接触式和非接触式纱线张力检测及控制原理的研究状况进行调研与分析.指出:当前纱线张力检测和控制技术的研究主要方向为采用非接触方式动态测试纱线张力并采取自适应控制技术,以使纱线的张力保持恒定.研究主要集中在提高测试系统的精度、性能、使用方便性及环境适应性上.其发展的总趋势是拓展测量范围,提高检测精度和可靠性;采用闭环控制技术,实现恒张力控制;采用微机电技术,实现在线非接触式检测与控制.     

A dynamic closed-loop location-inventory problem under disruption risk

In this paper, a dynamic closed-loop location-inventory problem is addressed that optimizes strategic decisions (i.e., facility location in terms of contracting/selection of distribution centers and reworking centers) along with tactical ones (i.e., allocation of centers, inventory management) under facility disruption risks. The presented model seeks to minimize total cost as the first objective function, and time as the second one in the considered network. Due to the NP-Hard nature of the model, a hybrid meta-heuristic algorithm based on Multi-Objective Particle Swarm Optimization (MOPSO) and Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is presented to solve the problem in large scales. Finally, applicability of the proposed model is tested via a real case study and the results are analyzed in depth.     

Optimizing a closed-loop supply chain with manufacturing defects and quality dependent return rate

The paper considers a closed-loop serial supply chain consisting of a raw material supplier, a manufacturer, a retailer and a collector who collects the used product from consumers. The retailer's demand is met up by both manufacturing and remanufacturing. The manufacturing process is assumed to be imperfect as it can produce some defectives which are reworked in the same cycle itself. The remanufacturing of used items solely depends on the quality level of collected items. Two mathematical models are developed. The first model considers a single manufacturing–remanufacturing cycle, while the second model considers multiple manufacturing and remanufacturing cycles. Both the models are solved using algorithms developed for sequential and global optimizations. Numerical studies show that (i) the acceptance quality level of returned items and the length of the replenishment cycle for the retailer are lower in case of sequential optimization than those in global optimization, (ii) integration among supply chain members results in less number of shipments from the manufacturer to the retailer, and (iii) the joint total profit is higher when the integrated approach is adopted. The percentage increase in joint total profit with the integrated policy is 1.24% in the first model while it is 0.544% in the second model.     

Nonlinear model predictive control of an industrial polymerization process

Nonlinear model predictive control (NMPC) is used to maintain and control polymer quality at specified production rates because the polymer quality measures have strong interacting nonlinearities with different temperatures and feed rates. Polymer quality measures that are available from the laboratory infrequently are controlled in closed-loop using a NMPC to set the temperature profile of the reactors. NMPC results in better control of polymer quality measures at different production rates as compared to using the nonlinear process model with reaction kinetics to implement offline targets for reactor temperatures.     

Non-kinematic calibration of a six-axis serial robot using planar constraints

This paper describes a non-kinematic calibration method developed to improve the accuracy of a six-axis serial robot, in a specific target workspace, using planar constraints. Simulation confirms that the stiffness of the robot, as well as its kinematic parameters, can be identified. An experimental validation shows that the robot's accuracy inside the target workspace is significantly enhanced by reducing the maximum distance errors from 1.321 mm to 0.274 mm. The experimental data are collected using a precision touch probe, which is mounted on the flange of a FANUC LR Mate 200iC industrial robot, and a high precision 9-in. granite cube. The calibration method makes use of a linear optimization model based on the closed-loop calibration approach using multi-planar constraints. A practical validation approach designed to reliably evaluate the robot's accuracy after calibration is also proposed.     

Competitive closed-loop supply chain network design under uncertainty

This paper studies the competition between two closed-loop supply chains including manufacturers, retailers and recyclers in an uncertain environment. The competition factors are the retail prices of new products and incentives paid to consumers for taking back the used products. Market demands are price sensitive and also the amount of returned products is sensitive to incentives. The primary goal of this paper is to investigate the impact of simultaneous and Stackelberg competitions between two closed-loop supply chains on their profits, demands and returns. A game theoretic approach which is empowered by possibility theory is applied to obtain the optimal solutions under uncertain condition. Finally the theoretical results are analyzed using sample data inspired by a real industrial case.     

Multivariable design of improved linear quadratic regulation control for MIMO industrial processes

In this study, a multivariable linear quadratic control system using a new state space structure was developed for the chamber pressure in the industrial coke furnace. Such processes typically have complex and nonlinear dynamic behavior, which causes the performance of controllers using conventional design and tuning to be poor or to require significant effort in practice. The process model is first treated into a new state space form and the implementation of linear quadratic control is designed using this new model structure. Performance in terms of regulatory/servo, disturbance rejection and measurement noise problems were all compared with the recent model predictive control strategy. Results revealed that the control system showed more robustness and improved the closed-loop process performance under model/process mismatches.     

Designing a closed-loop supply chain network for citrus fruits crates considering environmental and economic issues

Most cities, notably major and agricultural ones, are faced with environmental and waste problems. Distribution and collection of agricultural crops can be challenging duties as world demand and production are substantially increased. Accordingly, resource depletion, environmental concern, and the importance of the circular economy have convinced this research group to focus on a Closed-Loop Supply Chain (CLSC) network design. In this study, a new mixed linear mathematical model for a CLSC was developed which minimizes the CLSC’s total costs and which tackles and controls air pollution. Contrary to previous works about supply chain network design, we firstly consider citrus fruits’ crates in our model. To solve the model, two leading algorithms, Genetic Algorithm and Simulated Annealing, are employed and a third recently successful method, Keshtel Algorithm, is utilized. Further, two hybridization algorithms stemmed from mentioned ones are applied. Finally, the results are assessed by different criteria and compared, and then the two best algorithms are chosen in this case. Consequently, in order to achieve the most effective result, a real case study of crates was conducted. The results obviously presented applicability and efficiency of the proposed model. Thus, the most suitable network for CLSC of citrus fruits’ crates was designed in which the costs and emissions were reduced.     

光伏系统用于漏电流测量的霍尔闭环传感器设计

基于闭环磁通门技术的传感器广泛应用在测量大电流中的小剩余电流以及噪声共模电流。这类传感器的精度以及对大电流的隔离能力使之成为漏电流检测的最优方案,但通常缺点是成本昂贵且体积庞大。本文介绍了一种新型小尺寸且利用霍尔闭环技术对太阳能系统中的漏电流进行测量的传感器:新一代的LDSR产品。