工业遥控用频率合成二次变频FSK窄带收发模块

目前市场上流行的无线收发模快,一般有如下几种形式:①LC谐振式超再生收发头,此种模块价格低、结构简单,但抗干扰能力差,特别是由于LC谐振回路引起的频率偏移,使性能极不稳定,只能用在玩具及低档产品中.②带声表谐振器的发射头和超再生接收头,此种方式的发射机中采用了一只频率稳定度较高的声表谐振器(大部分为315MHz或433.92MHz).

工业园区微网调度研究与仿真

为提高新能源消纳能力和供电经济性、可靠性,研究了含风光柴储、生活负荷、具有有限可控能力工业负荷的工业园区微电网,提出了一种基于日前和日内相结合的优化调度方案。为保证日前优化调度的经济性,提出了一种分段变异优化的改进粒子群算法求解调度模型。改进算法相较于传统粒子群算法收敛性速度更快,同时提高了经济性,减少了园区的运行成本。日内运行时,为了校正日前预测偏差,采用源网荷储共同参与调整,保证尽可能跟随日前经济结果,提高微网系统的可靠性。日内调整建立详细化的仿真模型,采用实时仿真技术。利用实时仿真软件RT-LAB和实时仿真机OP4510构建的实时仿真平台,解决模型仿真用时较长、求解困难的问题,验证了工业园区微网调度策略的可行性。

采取有效措施,抑制2017年工业煤耗上升

2016年下半年以来,经济向好发展的形势推动了主要工业部门产量上升及煤耗增加,2017年上半年全国煤耗转为正增长,煤耗增长主要来自工业和发电部门。工业煤耗上涨的趋势将影响国家若干重要目标的实现,应引起国家和企业的重视和警觉,采取快速有效的措施扭转钢铁、水泥、电力、煤化工等主要耗煤部门煤炭消费上升的趋势,确保实现2017年煤炭消费总量继续保持在下降通道,同时结合长期措施,实现2020煤控目标,加速推进能源转型。

An adaptive switching control approach for trajectory tracking of robotic manipulators

In order to design a suitable controller which can achieve accurate trajectory tracking and a good control performance, and guarantee the stability and robustness of a robot system due to external disturbances error and internal parameter variations, an adaptive switching control strategy is proposed. The proposed scheme is designed under the condition of bounded distances and consists of an adaptive switching law and a PD controller. Based on the Lyapunov stability theory, it is proved that the proposed scheme can guarantee the tracking performance of the robotic manipulator and is adapted to varying unknown loads. Simulations are carded out on a two-link robotic manipulator, which illustrate the feasibility and validity of the proposed control scheme and the robustness for variational payloads.

神经网络可拓融合技术在生物废气检测中的应用

将生物滴滤塔有机废气处理过程视为一个可控工业生态环境,以净化废气的流量、循环液流量、pH值、塔内温度等过程参数作为可拓物元,采用神经网络模型的可拓融合的方法对工业生态环境中微生物的反应过程的状态检测进行了研究。通过仿真和实验发现净化处理过程适合用人工神经网络(ANN)模型建模,而通过对遗传算法的改进能够提高其收敛速度。采用改进遗传算法(MGA)与LMBP算法相结合(MGA-LMBP),建立了神经网络模拟生物滴滤塔处理有机废气的过程可拓融合模型,利用已有的实验数据样本训练神经网络模型,取得了较好的效果。

Time-stamped predictive functional control for networked control systems with random delays

The random delays in a networked control system (NCS) degrade control performance and can even destabilize the control system.To deal with this problem,the time-stamped predictive functional control (PFC) algorithm is proposed,which generalizes the standard PFC algorithm to networked control systems with random delays.The algorithm uses the time-stamp method to estimate the control delay,predicts the future outputs based on a discrete time delay state space model,and drives the control law that applies to an NCS from the idea of a PFC algorithm.A networked control system was constructed based on TrueTime simulator,with which the time-stamped PFC algorithm was compared with the standard PFC algorithm.The response curves show that the proposed algorithm has better control performance.

A Trusted Attestation Mechanism for the Sensing Nodes of Internet of Things Based on Dynamic Trusted Measurement

Internet of things has been widely applied to industrial control, smart city and environmental protection, in these applica- tion scenarios, sensing node needs to make real-time response to the feedback control of the application layer. Therefore, it is nec- essary to monitor whether or not awareness nodes are trusted in real time, but the existing mechanisms for trusted certification lack the real-time measurement and tracking of the sensing node. To solve the above problems, this paper proposes a dynamic metric based authentication mechanism for sensing nodes of Internet of things. Firstly, the dynamic trustworthiness measure of the sensing nodes is carried out by introducing the computational function such as the trust function, the trust- worthiness risk assessment function, the feed- back control function and the active function of the sensing node. The dynamic trustworthi- ness measure of sensing nodes from multiple dimensions can effectively describe the change of trusted value of sensing nodes. Then, on the basis of this, a trusted attestation based on node trusted measure is realized by using the revocable group signature mechanism of local verifier. The mechanism has anonymity, un- forgeability and traceability, which is proved the security in the standard model. Simulationexperiments show that the proposed trusted attestation mechanism is flexible, practical and ef｜Scient and has better attack resistance. It can effectively guarantee the reliable data transmission of nodes and realize the dynamic tracking of node reliability, which has a lower impact on system performance.

Mixed-Weights Least-Squares Stable Predictive Control Algorithm with Soft and Hard Constraints

Mixed-weight least-squares (MWLS) predictive control algorithm, compared with quadratic programming (QP) method, has the advantages of reducing the computer burden, quick calculation speed and dealing with the case in which the optimization is infeasible. But it can only deal with soft constraints. In order to deal with hard constraints and guarantee feasibility, an improved algorithm is proposed by recalculating the setpoint according to the hard constraints before calculating the manipulated variable and MWLS algorithm is used to satisfy the requirement of soft constraints for the system with the input constraints and output constraints. The algorithm can not only guarantee stability of the system and zero steady state error, but also satisfy the hard constraints of input and output variables. The simulation results show the improved algorithm is feasible and effective.

CONTROL WORK IN CLOSE RANGE PHOTOGRAMMETRY

The purpose, classification, required accuracy and surveying methods of control work for close range photogrammetry have been briefly stated. The different methods for definition of space, object coordinate system are also reviewed. It is suggested that the habitu-ally-practised rotation angle system for aerophotogrammetry in China should be used for the future teaching and resaarching work in the close range photogrammetry, and that the rotation angle system for terrestrial deformation photogrammetry should be left out in order to avoid the confuse and reduce the amount of expanse for making softwares. It has been emphasized that there are three improtant aspects in the close range control work with high accurary using the conventional method of engineering surveying: the use of standard scale for measurement of distance between two general stations, the accurate determination of start direction line between two general stations and the handling method of influence of 2C change. A method for setting up industrial surveying control net with extra-high accuracy ±(0.05–0.20) mm is presented by the author. This kind of industrial control net is necessary for batch process of large industrial components with purposes of measurement, inspect and lofting. There are some special methods of control work in the close range photogrammetry, including two methods presented by the author.

Genetic algorithm tuned PI controller on PMSM simplified vector control

A simple control structure in servo system is occasionally needed for simple industrial application which precise and high control performance is not exessively important so that the cost production can be reduced efficiently. Simplified vector control, which has simple control structure, is utilized as the permanent magnet synchronous motor control algorithm and genetic algorithm is used to tune three PI controllers used in simplified vector control. The control performance is obtained from simulation and investigated to verify the feasibility of the algorithm to be applied in the real application. Simulation results show that the speed and torque responses of the system in both continuous time and discrete time can achieve good performances. Furthermore, simplified vector control combined with genetic algorithm has a similar perfofmance with conventional field oriented control algorithm and possible to be realized into the real simple application in the future.

Industrial wastes applications for alkalinity regulation in bauxite residue: A comprehensive review

Bauxite residue is a highly alkaline material generated from the production of alumina in which bauxite is dissolved in caustic soda.Approximately 4.4 billion tons of bauxite residues are either stockpiled or landfilled,creating environmental risks either from the generation of dust or migration of filtrates.High alkalinity is the critical factor restricting complete utilization of bauxite residues,whilst the application of alkaline regulation agents is costly and difficult to apply widely.For now,current industrial wastes,such as waste acid,ammonia nitrogen wastewater,waste gypsum and biomass,have become major problems restricting the development of the social economy.Regulation of bauxite residues alkalinity by industrial waste was proposed to achieve‘waste control by waste’with good economic and ecological benefits.This review will focus on the origin and transformation of alkalinity in bauxite residues using typical industrial waste.It will propose key research directions with an emphasis on alkaline regulation by industrial waste,whilst also providing a scientific reference point for their potential use as amendments to enhance soil formation and establish vegetation on bauxite residue disposal areas(BRDAs)following large-scale disposal.

A new real-time ethernet MAC protocol for time-critical applications

The authors propose a new persistent transmission based real time Ethernet MAC protocol that provides a predictable upper bound for the delivery delay of real time frames. Moreover, it is compatible with the protocol used by the existing Ethernet controllers for conventional datagram traffic and thus standard Ethernet stations can be used in the system without any modification. The paper describes the protocol in detail and analyses the maximum delivery delay for real time traffic and the efficiency of the channel.

Multivariate Statistical Process Monitoring and Control: Recent Developments and Applications to Chemical Industry

Multivariate statistical process monitoring and control (MSPM&C) methods for chemical process monitoring with statistical projection techniques such as principal component analysis (PCA) and partial least squares (PLS) are surveyed in this paper. The four-step procedure of performing MSPM&C for chemical process, modeling of processes, detecting abnormal events or faults, identifying the variable(s) responsible for the faults and diagnosing the source cause for the abnormal behavior, is analyzed. Several main research directions of MSPM&C reported in the literature are discussed, such as multi-way principal component analysis (MPCA) for batch process, statistical monitoring and control for nonlinear process, dynamic PCA and dynamic PLS, and on-line quality control by inferential models. Industrial applications of MSPM&C to several typical chemical processes, such as chemical reactor, distillation column, polymerization process, petroleum refinery units, are summarized. Finally, some concluding remarks and future considerations are made.

Hellinger distance based probability distribution approach to performance monitoring of nonlinear control systems

Control performance monitoring has attracted great attention in both academia and industry over the past two decades. However, most research efforts have been devoted to the performance monitoring of linear control systems, without considering the pervasive nonlinearities(e.g. valve stiction) present in most industrial control systems. In this work, a novel probability distribution distance based index is proposed to monitor the performance of non-linear control systems. The proposed method uses Hellinger distance to evaluate change of control system performance. Several simulation examples are given to illustrate the effectiveness of the proposed method.

A Pragmatic Approach for Assessing the Economic Performance of Model Predictive Control Systems and Its Industrial Application

In this article,an approach for economic performance assessment of model predictive control(MPC) system is presented.The method builds on steady-state economic optimization techniques and uses the linear quadratic Gaussian(LQG) benchmark other than conventional minimum variance control(MVC) to estimate the potential of reduction in variance.The LQG control is a more practical performance benchmark compared to MVC for performance assessment since it considers input variance and output variance,and it thus provides a desired basis for determining the theoretical maximum economic benefit potential arising from variability reduction.Combining the LQG benchmark directly with benefit potential of MPC control system,both the economic benefit and the optimal operation condition can be obtained by solving the economic optimization problem.The proposed algorithm is illustrated by simulated example as well as application to economic performance assessment of an industrial model predictive control system.

Soft sensor modeling based on Gaussian processes

In order to meet the demand of online optimal running, a novel soft sensor modeling approach based on Gaussian processes was proposed. The approach is moderately simple to implement and use without loss of performance. It is trained by optimizing the hyperparameters using the scaled conjugate gradient algorithm with the squared exponential covariance function employed. Experimental simulations show that the soft sensor modeling approach has the advantage via a real-world example in a refinery. Meanwhile, the method opens new possibilities for application of kernel methods to potential fields.

Infrastructure for China＇s Ecologically Balanced Civilization

China＇s green investment needs up to 2020 are ￥1.7 trillion-2.9 trillion CNY （$274 billion-468 billion USD） per year. Estimates of financing requirements are provided for multiple sectors, including susainable energy, infrastructure （including for environmental protection）, environmental remediation, industrial pollution control, energy and water efficiency, and green products. The context to China＇s green financing is discussed, covering urbanization, climate change, interactions between infrastructure sectors, and the transformation of industry. Much of the infrastructure financing will occur in cities, with a focus on equity, environmental protection, and quality of life under the National New-Type Urbanization Plan （2014-2020）. China has implemented many successful policies in the building sector, but there is still considerable scope for improvement in the energy efficiency of Chinese buildings. China is currently pursuing low-carbon growth strategies that are consistent with its overall environmental and quality-of-life objectives. Beyond 2020, China＇s future as an ecologically balanced civilization will rest on the implementation of a central infrastructure policy： China 2050 High Renewable Energy Penetration Scenario and Roadmap Study. As exemplified by the Circular Economy Development Strategy and Near-Term Action Plan, an essential part of China＇s green industrial transformation involves engineering systems that conserve materials, thereby reducing or even eliminating wastes. To better understand changes to China＇s economy under its green transformation and to unlock large potential sources of finance, it is necessary to undertake a fuller examination of all of China＇s infrastructure sectors, particularly freight rail infrastructure and ports. Large investments are required to clean up a legacy of environmental contamination of soil and groundwater and to reduce industrial pollution. Transformation of the power sector away from coal will avoid some industrial treatment costs. The contribution of engineers in planning, designing, and constructing China＇s new green infrastructure will be furthered by understanding the broad policy context and the interactions between land use, infrastructure, and environmental performance.

Effects site conditions on industrial fiber plantations of Lar/x olgensis

Plot sampling was conducted in the second cultivation areas ofLarix olgensis in Heilongjiang Province, China. By analyzing plot investigation data, wood properties, and kraft pulps of 840 plots and 248 sample trees in industrial plantations of L. olgensis on different sites, we examined the growth process of L. olgensis industrial plantation with suitable structure, the wood fiber feature, chemical composition, physical performance and pulp characteristics. It is suggested that site conditions have major effects on plantation growth, fiber contains, fiber length, rate between fiber length and fiber width, pulping rate and pulp physics intensity. The best site for L. olgensis industrial plantation growth is site class Ⅰ and site class Ⅱ, which are on lower locations. Site condition has an obvious influence on the wood characteristics. Within the range of site conditions and stand densities studied, the worse the site condition, the less the fiber contains, the shorter the fiber length, and the more the 1% NaOH extraction. This kind of relationship becomes more obvious as stand age increases. However, the influence of site condition on pulping rate and pulp physics intensity is not obvious. The result provides theoretical base for cultivation of industrial fiber plantation of L. olgensis.

A Genetic Algorithm-based Approach to Scheduling of Batch Production with Maximum Profit

The optimal scheduling of multi-product batch process is studied and a new mathematics model targeting the maximum profit is proposed, which can be solved by the modified genetic algorithm (MGA) with mixed coding (sequence coding and decimal coding) developed by us. In which, the partially matched cross over (PMX) and reverse mutation are used for the sequence coding, whereas the arithmetic crossover and heteropic mutation are used for the decimal coding. In addition, the relationship between production scale and production cost is analyzed and the maximum profit is always a trade-off of the production scale and production cost. Two examples are solved to demonstrate the effectiveness of the method.