短线拼装法施工的宽幅多节段混凝土箱梁的预制控制

采用短线拼装法施工的宽幅多节段混凝土箱梁的预制施工比常规连续箱梁预制节段施工复杂,控制难度和精度要求更高。该文以石首长江公路大桥北边跨的预制施工为工程背景,详细介绍了宽幅混凝土箱梁预制施工中的无应力线形控制和滑移、起吊、存梁施工中的安全控制,通过无应力制造线形控制最终成桥线形,通过横向预应力的分次张拉控制多次体系转换过程中的梁体安全。工程实践表明:采用短线拼装法施工宽幅多节段混凝土箱梁是可行的,既能保证预制线形也能保证拼装前梁体各工序的安全。

极寒条件下东北地区地铁管片预制质量控制

本文结合哈尔滨轨道交通2号线的实践经验,针对哈尔滨地区极寒天气条件下的混凝土管片预制质量控制技术展开探讨.分别从混凝土管片冬季预制施工环境、施工准备、原材料选取、混凝土施工、管片的冬季养护以及成品管片存放等几个方面详细介绍了混凝土管片冬季预制施工过程中应当注意的问题.经实践证明,本文所介绍的管片冬季预制施工技术完全可以满足混凝土管片生产质量的要求,效果良好.

短线法节段预制线形控制技术

短线法节段预制拼装技术在我国桥梁建设中已经被越来越广泛地应用,短线法节段预制拼装关键技术是短线法节段预制线形控制技术。介绍短线法节段预制基本流程及短线法节段预制线形控制的实质、原理和方法。

基于西门子S7-300PLC的光纤预制棒温度控制系统的设计

针对光纤制造行业预制棒加热系统温度控制要求,介绍基于西门子S7-300PLC的光纤预制棒温度控制系统的硬件配置、软件流程、人机画面等。

梁体预制安装控制对公路工程施工的影响分析

预应力梁体施工是一个系统工程,施工工艺是否合理,施工组织与管理水平是否先进,是关系到有效预应力是否实现的关键,也是影响整个公路工程施工整体的协调性的关键。文章以某高速公路项目施工过程为例,以该项目的预应力施工组织为主体,分别从预制场施工组织、箱梁运输吊装组织两个方面进行分析,论述了箱梁预制安装对公路工程施工的影响。

环卫重大设施的工程预制率控制

主要分析了预装拼装技术的基本概念、国内外研究现状和主要工程优势,包括可以有效缩短工期、确保施工质量、提高施工安全性、更加环保和现场作业的系统化程度高。2016年起,建筑单体预制率不应低于40%或单体装配率不低于60%。环卫重大设施建设项目具有其特殊性,功能性建筑的标准化程度低、区域位置特殊对建筑本身的环保功能要求高、构件尺寸种类多且不规则、施工次序也对预制拼装技术的实施有影响。在综合考虑施工质量、成本、建设性能要求等要素后认为,对于环卫重大工程的预制率,需要依据工程项目的具体特点进行控制。

浅谈标准海堤四角预制块预制施工质量控制

围海工程近年来在东南沿海省市发展迅速，作为围海工程的主体，海堤起着至关重要的作用。四角预制块以其独特的“气质”在海堤防护工程过程中运用广泛。如何制作出质量过关、外形优美的四角预制块则十分讲究。

浅谈液压拉深垫电气控制系统

目前我国对液压拉深垫电气化控制的研究与应用还处于初级阶段。还存在诸如基本理论不清,应用前景不明,设计理念不确定等问题。本文针对这一问题对分别从液压拉深垫的组成,原理,编程,应用等多个方面阐述其基本问题。为接下来的研究以及企业在生产线上的应用扫平理论障碍。

装配式建筑在设计阶段的预制率计算研究

随着人们生活水平的不断提高,传统的现浇式建筑建设周期长、劳动效率低、环境污染严重等弊端日益突显,为此,近年来我国积极推行装配式建筑,其缩短工期、节约人力、节能环保的特点更符合新时期现代化建设的要求。相较于传统的现浇式建筑,装配式建筑在设计阶段的成本控制对整个工程项目造价的影响更加显著。本文针对设计阶段影响造价成本的重要指标--预制率,探讨影响预制率的各项因素。从微观角度运用价值工程理论,对比不同种类的预制构件对预制率的影响,得到施工图设计阶段经济的预制构件拆分模式,再从宏观角度分析结构体系类型、房型布置、建筑层数的差异对预制率的影响,在满足预制率要求的前提下,得到方案设计阶段的房型及建筑层数建议。

提高低压储罐抗压环施工质量

根据施工运行压力0.088MPa低压储罐图纸及标准要求要求,施工抗压环时采用焊接对称焊、分段跳焊,预制严格把关,焊前预热充分的措施,提高施工精度,获得令人满意的效果。

Adaptive Modification of the Rolling Force Prediction

In rolling process, the rolling force is an important parameter. The precision of the predicted rolling force will directly affect the precision of the finished product. By using adaptive control theory and fusing the measured and predicted data, the precision of the predicted rolling force is gradually improved. This system has been used in plant for more than one year, and the result of the application shows that the system has steady and reliable performance, and high precision.

Fuzzy disturbance rejection predictive control of ultra-supercritical once-through boiler-turbine unit

In order to overcome the wide-range load tracking and unknown disturbance issues of an ultra-supercritical boiler- turbine unit, a fuzzy disturbance rejection predictive control approach is proposed using the techniques of fuzzy scheduling, model predictive control and extended state observer. Local state-space models are established on the basis of nonlinearity analysis and subspace identification. To eiJiance thedisturbance rejection capability of the controller, a extended state observer is employed to estimate unnown disturbances and model mismatches. The disturbance estimation ennaced local predictive controllers ae subsequently devised based on the local models, the performance of which is further strengthened by incorporating the fuzzy scheduling technique. The simulation results verify the merits of the proposed strategy in achieving satisfactory wide-range load tracking ad disturbance rejection performance.

ADAPTIVE PREDICTIVE CONTROL OF NEAR-SPACE VEHICLE USING FUNCTIONAL LINK NETWORK

A novel nonlinear adaptive control method is presented for a near-space hypersonic vehicle （NHV） in the presence of strong uncertainties and disturbances. The control law consists of the optimal generalized predictive controller （OGPC） and the functional link network （FLN） direct adaptive law. OGPC is a continuous-time nonlinear predictive control law. The FLN adaptive law is used to offset the unknown uncertainties and disturbances in a flight through the online learning. The learning process does not need any offline training phase. The stability analyses of the NHV close-loop system are provided and it is proved that the system error and the weight learning error are uniformly ultimately hounded. Simulation results show the satisfactory performance of the con- troller for the attitude tracking.

Application of the Plate Crown Prediction

The program of the plate crown optimal prediction applied in the plate mill of Wuhan Iron and Steel(Group) Co. Ltd. is described. Optimal prediction is programmed in ALPHA 4000. The original profile, wear, expansion and deformation of work rolls are introduced into the program. The plate crown is controlled by the original profile of work rolls and the draft whose objective is the optimal plate crown. The run schedule is also optimized through the optimal prediction of the plate crown.

Application of Generalized Predictive Adaptive Control Algorithm in the Design of Missile Control System

To study the application of the generalized predictive adaptive control algorithm in missile control system, the algorithm is presented based on the recursive least square estimation, and a controller of the pitch channel of a missile is designed by using this algorithm. The simulations verify that the designed controller can meet the demands of the task well.

The Application and Design of the Economical Nonlinear Controller

This anticle gives a design method of the economical nonlinear controller. The controller is composed of an expert intelligent coordination controller, a fuzzy prediction controller, a fuzzy feedforward controller, a nonlinear controller and so on. The consistence of a distributed control system based on this controller is also shown briefly.

Predictive Control of Optoelectronic Tracking System

Aim To solve the time delay problem in the optoelectronic tracking system, improving the tracking accuracy. Methods The discount least square algorithm was applied to forecast the tracking error caused by the 40?ms delay, and the predicting algorithm was improved by the adaptive discount method.Results The tracking errors of the two methods were compared, and an optimal controller with the improved adaptive discount predicting algorithm was adopted for simulation. Conclusion The predicting algorithms, especially the adaptive discount predicting algorithm, can decrease the tracking error greatly, and the desired tracking prediction can be achieved both in the transient state and in the steady state.

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.

Stable MIMO Constrained Predictive Control with Steadystate Objective Optimization

A two-stage multi-objective optimization model-predictive control algorithms(MPC) strategy is presented. A domain MPC controller with input constraints is used to increase freedom for steady-state objective and enhance stabilization of the controller. A steady-state objective optimization algorithm oriented to transient process is adopted to realize optimization of objectives else than dynamic control. It is proved that the stabilization for both dynamic control and steady-state objective optimization can be guaranteed. The theoretical results are demonstrated and discussed using a distillation tower as the model. Theoretical analysis and simulation results show that this control strategy is efficient and provides a good strategic solution to practical process control.

Robust model predictive control for discrete uncertain nonlinear systems with time-delay via fuzzy model

An extended robust model predictive control approach for input constrained discrete uncertain nonlinear systems with time-delay based on a class of uncertain T-S fuzzy models that satisfy sector bound condition is presented. In this approach, the minimization problem of the “worst-case” objective function is converted into the linear objective minimization problem in- volving linear matrix inequalities (LMIs) constraints. The state feedback control law is obtained by solving convex optimization of a set of LMIs. Sufficient condition for stability and a new upper bound on robust performance index are given for these kinds of uncertain fuzzy systems with state time-delay. Simulation results of CSTR process show that the proposed robust predictive control approach is effective and feasible.