数学教学中“目标控制法”的理论与实践

数学教学中“目标控制法”的理论与实践张莉杨姗姗从一般的意义上说，人类的一切活动都是在一定的目标驱使下进行的，而目标的实现程度，又取决于实现目标的方法。教学的目标，就是以学生为主体，通过教师的主导作用，引导学生对科学的认识从不知到有知，从少知到多知，最...

国际工程项目管理中目标控制法的应用

随着我国工程项目逐渐走向国际化之后面临的挑战越来越多,在面对各种机遇的同时,企业也在不断思考如何降低资金成本、同时保证工程质量提升竞争力。目标控制法是一种可以有效帮助企业在国际项目中保持优势的方法。本文简要阐述了在国际工程项目管理中目标控制法的应用。

浅谈工程项目施工进度目标控制法

大中型工业设计项目的总体进度计划,以及单位项工程施工进度计划,一般都采用目标控制网络计划,影响施工进度计划正常进行的因素很多,如未能考虑各种影响因素,在实施中就会出现某个或某些控制目标被突破的情况,使施工进度计划在实际执行中要进行经常性的修改和调整。本文试图提出一种事先合理地考虑各种对施工进度的影响因素,在保证工程项目总目标得以控制的前提下,科学地编制目标控制施工进度计划的方法。以减少施工进度计划修改和调整的频度,保证工程总体目标的实现。

基于改进遗传算法的污水处理多目标优化控制方法

通过分析遗传算法的实际意义,提出利用算法定位污水处理目标源的方式,定义一个与行为结果最为符合的处理目标,使处理过程中多目标具备一个相对平衡的处理值。同时,结合多目标优化,从4个阶段规划控制污水处理过程,以此完成对污水处理的多目标优化控制。此外,设计对比实验,证明提出的方法在应用中可有效地降低污染物浓度。

房屋建筑工程造价的控制措施研究

针对房屋建筑工程造价问题,采取实践经验总结法,做了简单的论述。通过研究提出:(1)工程造价的控制,要采取全过程把控的措施,做好事前预测、事中控制、事后监督,促使控制目标的实现。(2)为强化造价控制,需要不断创新控制方式方法,引入新技术和新手段,全面提高造价控制水平,实现造价控制的要求。

国外高等医学教育学科式课程结构改革趋势分析

国外的医学教育课程结构基本可分为3种类型,即'传统学科式'、'以问题为中心式'及'器官系统式'。其中,传统学科式以其体现医学科学系统性、基础性、完整性及循序渐进的教学,方便教学实施与管理,节省财力等等优点一直被各医学院校广泛采用。如英国38所医学院校中36所采用传统医学课程模式。

Optimization and Control of Extractive Distillation with Heat Integration for Separating Benzene/Cyclohexane Mixtures

In this work, the extractive distillation with heat integration process is extended to separate the pressure-insensitive benzene-cyclohexane azeotrope by using furfural as the entrainer. The optimal design of extractive distillation process is established to achieve minimum energy requirement using the multi-objective genetic algorithm, and the results show that energy saving for this heat integration process is 15.7%. Finally, the control design is performed to investigate the system's dynamic performance, and three control structures are studied. The pressure-compensated temperature control scheme is proposed based on the first two control structures, and the dynamic responses reveal that the feed disturbances in both flow rate and benzene composition can be mitigated well.

Multi-objective optimization based on Genetic Algorithm for PID controller tuning

To get the satisfying performance of a PID controller, this paper presents a novel Pareto-based multi-objective genetic algorithm (MOGA), which can be used to find the appropriate setting of the PID controller by analyzing the pareto optimal surfaces. Rated settings of the controller by two criteria, the error between output and reference signals and control moves, are listed on the pareto surface. Appropriate setting can be chosen under a balance between two criteria for different control purposes. A controller tuning problem for a plant with high order and time delay is chosen as an example. Simulation results show that the method of MOGA is more efficient compared with traditional tuning methods.

Multi-objective optimization of active steering system with force and displacement coupled control

A novel active steering system with force and displacement coupled control(the novel AFS system) was introduced,which has functions of both the active steering and electric power steering.Based on the model of the novel AFS system and the vehicle three-degree of freedom system,the concept and quantitative formulas of the novel AFS system steering performance were proposed.The steering road feel and steering portability were set as the optimizing targets with the steering stability and steering portability as the constraint conditions.According to the features of constrained optimization of multi-variable function,a multi-variable genetic algorithm for the system parameter optimization was designed.The simulation results show that based on parametric optimization of the multi-objective genetic algorithm,the novel AFS system can improve the steering road feel,steering portability and steering stability,thus the optimization method can provide a theoretical basis for the design and optimization of the novel AFS system.

Multi-objective optimization based optimal setting control for industrial double-stream alumina digestion process

The operation variables,including feed rate of ore slurry,caustic solution and live steams in the double-stream alumina digestion process,determine the product quality,process costs and the environment pollution.Previously,they were set by the technical workers according to the offline analysis results and an empirical formula,which leads to unstable process indices and high consumption frequently.So,a multi-objective optimization model is built to maintain the balance between resource consumptions and process indices by taking technical indices and energy efficiency as objectives,where the key technical indices are predicted based on the digestion kinetics of diaspore.A multi-objective state transition algorithm(MOSTA)is improved to solve the problem,in which a self-adaptive strategy is applied to dynamically adjust the operator factors of the MOSTA and dynamic infeasible threshold is used to handle constraints to enhance searching efficiency and ability of the algorithm.Then a rule based strategy is designed to make the final decision from the Pareto frontiers.The method is integrated into an optimal control system for the industrial digestion process and tested in the actual production.Results show that the proposed method can achieve the technical target while reducing the energy consumption.

Multi-rate tracking controller analysis and design for target tracking systems

As the sampling rates of the inner loop and the outer loop of the target tracking control system are different,a typical digital multi-rate control system was formed.If the traditional single-rate design method was applied,the low sampling rate loop will seriously impact the dynamical characteristic of the system.After analyzing and calculating the impact law of the low sampling rate loop to the bandwidth and the stability of the tracking system,a kind of multi-rate control system design method was introduced.Corresponding to the different sampling rates of the inner loop and the outer loop,the multi-rate control strategy was constituted by a high sampling rate sub-controller and a low sampling rate sub-controller.The two sub-controllers were designed separately and connected by means of the sampling rate converter.The low sampling rate controller determined the response rapidity of the system,while the high sampling rate controller applied additionally effective control outputs to the system during a sampling interval of the low sampling rate controller.With the introduced high and low sampling rates sub-controllers,the tracking control system can achieve the same performance as a single-rate controller with high sampling rate,yet it works under a much lower sampling rate.The simulation and experimental results show the effectiveness of the introduced multi-rate control design method.It reduces the settling time by 5 times and the over shoot by 4 times compared with the PID control.

Model predictive control for adaptive cruise control with multi-objectives: comfort,fuel-economy,safety and car-following

For automated vehicles,comfortable driving will improve passengers’ satisfaction.Reducing fuel consumption brings economic profits for car owners,decreases the impact on the environment and increases energy sustainability.In addition to comfort and fuel-economy,automated vehicles also have the basic requirements of safety and car-following.For this purpose,an adaptive cruise control (ACC) algorithm with multi-objectives is proposed based on a model predictive control (MPC) framework.In the proposed ACC algorithm,safety is guaranteed by constraining the inter-distance within a safe range; the requirements of comfort and car-following are considered to be the performance criteria and some optimal reference trajectories are introduced to increase fuel-economy.The performances of the proposed ACC algorithm are simulated and analyzed in five representative traffic scenarios and multiple experiments.The results show that not only are safety and car-following objectives satisfied,but also driving comfort and fuel-economy are improved significantly.

An attitude algorithm based on the band seamless splicing imaging for agile satellite

In order to realize fast maneuvering imaging of the target area with high resolution agile satellite, a new attitude matching algorithm is developed. A strict mosaic imaging model of ray trace and the velocity vector mapping are built according to the strip mosaic imaging principle and the relationship between imaging target and the camera focal plane. The three-axis attitude is deduced based on the principle of optimal tracking of the maneuvering path. Finally, the geometric scaling simulation is carried out through the time delayed and integration(TDI) charge coupled device(CCD) prototype system, satellite attitude control physical simulation platform and the LED earth target simulator. The experimental results show that the algorithm could realize the matching band seamless splicing imaging of the target very well, confirming the correctness of the algorithm.

Sliding-Mode-Control Based Robust Guidance Algorithm Using Only Line-of-Sight Rate Measurement

Robust guidance algorithm using only line-of-sight rate measurement is proposed for the interceptor with passive seeker.The initial relative distance,initial closing velocity and their error boundaries are employed to obtain their estimations according to the interceptor-target relative kinematics.A robust guidance law based on sliding mode control is formulated,in which the boundary of target maneuver is needed and the chattering phenomenon inevitably exists.In order to address the defects above,an estimation to the boundary of the target acceleration is proposed to improve the robust guidance law and the Lyapunov stability analysis is included.The main feature of the robust guidance algorithm is that it reduces the influence of the relative distance,the closing velocity and the target maneuver on the interception and enhances the effect of line-of-sight rate.With two worst conditions of initial measured distance and initial measured closing velocity,performances of the proposed guidance laws are verified via numerical simulations against different target maneuvers.