基于数字化生产模型的在线故障诊断技术研究

提出了一种基于数字化的生产模型,使用控制图、故障树分析和专家知识,能够进行制造过程实时监控的诊断,该模型提高了故障诊断系统的可靠性,并提供了可实际操作的可视化建模工具.所开发的在线统计过程控制系统能够根据生产事件的监测,动态响应制造过程变化.该系统运用可视化建模工具,根据专家经验进行故障树建模,通过故障树自动生成专家系统诊断规则库,实现诊断知识的自动获取.将该系统应用于汽车变速箱装配过程的检测与故障诊断,验证了方法的有效性.     

基于强酸当量的pH值的多模型自适应控制

pH控制由于其严重的非线性一直是过程控制中的难题。基于强酸当量的控制方案在过程流流速远大于中和流流速的前提下将过程机理模型转化为近似线性模型,该方案具有对模型误差鲁棒的优点,已得到广泛的认可,但在中和曲线发生变化时其控制性能显著下降。为了克服这一问题,该文采用了基于混合型参数估计的多模型自适应控制方案。模型集的选取采用了固定模型与自适应模型相结合的方案。仿真结果表明,该设计方案能够有效的克服中和曲线变动带来的影响,具有良好的控制效果。     

先进控制是技术发展的必然趋势

为了克服控制理论和实际工业应用之间的脱节现象，尽快地将现代控制理论移植到过程控制领域．充分发挥计算机的功能．世界各国在加强建模理论、辨识技术、优化控制、最优控制、高级过程控制等方面进行研究，推出了从实际工业过程特点出发，寻求对模型要求不高，在线计算方便，对过程和环境的不确定性有一定适应能力的控制策略和方法。例如．自适应控制系统、     

基于以太网的过程控制系统研究

基于Internet网络的过程控制系统能很好的解决现有硬件资源短缺,充分发挥网络的优势.文章主要针对实验室的过程控制装置进行二次开发,采用TCP/IP技术,实现了对控制现场的网络化监控,通过试验证明,该系统实时性好,可靠性高.     

计算机集成综合自动化预测控制建模

预测控制是一种基于模型的先进控制技术,所采用的预测控制算法对模型的精度要求不高,比传统的最优控制和自适应控制更适应复杂的工业工程过程中不确定环境的需要.提出了一种基于预测模型预测系统未来输出、滚动实施优化并结合了闭环反馈校正的计算机优化控制算法,采用滚动的有限时段优化取代了一次性的全局优化实现滚动优化控制,更符合实际工业过程控制的特点,对克服系统的不确定性影响具有更强的鲁棒性.利用提供的优化控制算法,在实际应用中取得了较好的效果.     

基于模型预测控制的乳化物干燥控制系统

分析了干燥的过程从而确立了模型预测控制的各个环节,有预测模型、参考轨迹、滚动优化、反馈算法.并且辅助介绍了模型预测控制的基本原理和优势.实现了乳化物干燥过程中的品质在线检测和识别的有效控制,解决了目前乳化物干燥设备中存在的非稳态过程控制精度低、物料损耗大、费用高等问题.     

风洞模型支撑系统振动主动控制试验研究

风洞试验中,在非定常气动载荷激励下,模型支撑系统会出现振动,较大量级的振动会制约试验安全和测量精度。为解决风洞试验中模型支撑系统的振动问题,在模型支撑系统支杆尾部安装压电智能结构,配合PID和神经网络算法,实现对模型支撑系统振动的主动控制。为验证上述结构的振动主动控制效果,在某风洞中,使用LMS Test.Lab动态信号采集分析系统对安装压电智能结构的模型支撑系统开展模态试验和风洞试验研究。试验结果表明:(1)风洞试验中,模型支撑系统振动以一阶和二阶振动为主,随着风速增大,二阶加速度与一阶加速度振幅比增加;(2)PID算法可以实现试验各工况的振动控制,但控制效果不稳定;具有自适应性的神经网络算法在控制中不收敛,振动出现发散。(3)以振动加速度有效值为考察依据,对于一阶振型,PID算法减振幅度约为92.94%,神经网络算法减振幅度约为83.89%;对于二阶振型,PID算法减振幅度约为68.65%,神经网络算法不收敛,振动出现发散。     

湿式双离合自动变速器起步过程的试验研究

针对湿式双离合器自动变速器的特点,建立起步过程动力学模型,根据车辆起步过程评价指标,得出起步过程控制策略.并结合以大众DQ250为目标变速器的起步台架试验,分析小油门平稳起步工况,验证控制方法.试验结果表明,控制策略适应拟定工况,符合车辆起步要求.     

过程控制中测量系统误差的性能影响分析

从控制图的建立和监控两个不同阶段的角度分别讨论了测量系统误差对过程质量控制监控性能的影响.以平均运行长度作为过程控制性能评价的指标,分析了两种不同类型的测量误差对监控性能的干扰模式.最后通过一个算例分析测量系统误差的危害性,表明一个好的测量系统在过程监控中的重要性.     

智能工序质量控制技术研究

人工智能在工序质量控制中的研究与应用有两个重要的方面 :基于统计过程控制的过程诊断分析 ;质量预测控制。文中对其应用过程中存在问题以及将来的发展趋势作了分析和介绍 ,并提出了解决方案和系统模型。     

音圈致动快速反射镜的降阶自抗扰控制

为改善航空光电载荷用音圈致动快速反射镜的控制性能,提出一种降阶自抗扰控制方法。首先,对快速反射镜(Fast Steering Mirror,FSM)模型进行了分析并获取了模型参数。根据自抗扰控制理论,设计了FSM的三阶通用自抗扰控制器。将电涡流传感器的测量结果视为已知,提出降阶扩张状态观测器及其对应的自抗扰控制器设计方法。根据控制器带宽设计思想,推导了对于FSM这类二阶欠阻尼对象的控制律,并给出了加入扰动补偿量的控制律的具体实现形式。实验结果表明,降阶自抗扰控制能明显改善FSM的位置阶跃响应动态性能,能实现无超调与振荡的阶跃响应,稳态时间由11.7 ms提升至9.2 ms,同时能够降低FSM对位置斜坡输入跟踪的稳态误差,并改善其速度响应动态过程,像移补偿稳速时间由10.2 ms提升至7.8 ms,提升约24%。降阶自抗扰控制具有实现简单、运算量小的特点,能够明显提升FSM的动态性能。     

Disturbance-observer-based fuzzy model predictive control for nonlinear processes with disturbances and input constraints

This paper proposes a disturbance-observer-based fuzzy model predictive control (DOBFMPC) scheme for the nonlinear process subject to disturbances and input constraints. The proposed control scheme is composed of the baseline fuzzy model predictive control (FMPC) law designed on the Takagi–Sugeno fuzzy model and the disturbance compensation law. To build a fuzzy model of appropriate complexity and accuracy for the nonlinear process model, a systematic approach is developed via the gap metric to determine the linearization points. With FMPC, the asymptotic stability is theoretically proved, and the input constraints are satisfied by both the free control variables and the future control inputs in the form of the state feedback law. The disturbance compensation gain is designed such that the influence of the disturbance is removed from the output channels by the composite DOBFMPC law at the steady state. The application to a subcritical boiler–turbine system demonstrate the effectiveness of the proposed control scheme.     

Predictive IP controller for robust position control of linear servo system

Position control is a typical application of linear servo system. In this paper, to reduce the system overshoot, an integral plus proportional (IP) controller is used in the position control implementation. To further improve the control performance, a gain-tuning IP controller based on a generalized predictive control (GPC) law is proposed. Firstly, to represent the dynamics of the position loop, a second-order linear model is used and its model parameters are estimated on-line by using a recursive least squares method. Secondly, based on the GPC law, an optimal control sequence is obtained by using receding horizon, then directly supplies the IP controller with the corresponding control parameters in the real operations. Finally, simulation and experimental results are presented to show the efficiency of proposed scheme.     

基于公理化设计的可编程序控制器控制系统设计方法

为提升可编程序控制器控制系统设计的系统性和科学性,提出了基于公理化设计原理的可编程序控制器控制系统的设计方法,并建立了设计过程模型.该过程模型把可编程序控制器控制系统设计分为系统层设计和软件层设计两个设计层次,每个层次都基于公理化设计理论进行设计.两个设计层之问通过层级映射关系进行连接,实现了公理化设计理论与可编程序控制器控制系统传统设计知识的有效结合.最后通过实例验证了该方法的可行性.     

Performance optimization of linear active disturbance rejection control approach by modified bat inspired algorithm for single area load frequency control concerning high wind power penetration

The linear active disturbance approach is employed to deal with the load frequency control issue of a single area wind power system based on doubly fed induction generator, and the performance of the control law is optimized by using the bat-inspired algorithm. The load frequency control issue has become more challenging in a complex power system based on wind energy conversion system due to the varying feature of the wind penetration, and sustaining the balance between the power generation and demand by rejecting the internal uncertainties in the process model and the external disturbances simultaneously. In the framework of the presented linear active disturbance rejection control approach, by constructing an extended state observer, the total disturbance, including all the unmodelled dynamics in the process model and the external disturbances, can be estimated in real time and then compensated by a simple linear PD control law. The controller parameters tuning is then simplified into the optimization of the two bandwidths: observer bandwidth, and the controller bandwidth. Then, this issue can be achieved by employing the heuristic modified bat inspired algorithm based on the optimization of the proposed performance index. The effectiveness of the proposed approach is validated by the extensive simulation examples of the load frequency control issue involved in the single area power system, taking into account different wind penetration, as well as the external disturbances. The performance robustness of the proposed approach against the parameters perturbation in the process model is also demonstrated via the Monte-Carlo method. The performance superiority of the proposed approach over the conventional Proportional Integral and Fuzzy-Proportional Integral based controller even in the presence of external disturbances and uncertainty in power system parameters under different cases of high wind penetration is also validated from the simulation results.     

基于灰色预测的永磁同步电动机速度控制

本文针对永磁同步电动机非线性动态数学模型，采用直接反馈线性化控制，建立了闭环系统的输入-输出模型，通过线性化模型来设计控制器，该方法简单适用；同时，为了克服此反馈线性化控制对模型要求精确化这一不足，提出了基于灰色理论的不确定预测器，它能在线预测永磁同步电机的不确定因素并相应的调整反馈线性化控制法则，从而提高了系统的动态性能。仿真与实验结果表明，该方法对永磁同步电机速度控制具有很好的跟踪性能和鲁棒性能。     

Neuro-estimator based GMC control of a batch reactive distillation

In this paper, an artificial neural network (ANN)-based nonlinear control algorithm is proposed for a simulated batch reactive distillation (RD) column. In the homogeneously catalyzed reactive process, an esterification reaction takes place for the production of ethyl acetate. The fundamental model has been derived incorporating the reaction term in the model structure of the nonreactive distillation process. The process operation is simulated at the startup phase under total reflux conditions. The open-loop process dynamics is also addressed running the batch process at the production phase under partial reflux conditions. In this study, a neuro-estimator based generic model controller (GMC), which consists of an ANN-based state predictor and the GMC law, has been synthesized. Finally, this proposed control law has been tested on the representative batch reactive distillation comparing with a gain-scheduled proportional integral (GSPI) controller and with its ideal performance (ideal GMC).     

Improved fuzzy PID controller design using predictive functional control structure

In conventional PID scheme, the ensemble control performance may be unsatisfactory due to limited degrees of freedom under various kinds of uncertainty. To overcome this disadvantage, a novel PID control method that inherits the advantages of fuzzy PID control and the predictive functional control (PFC) is presented and further verified on the temperature model of a coke furnace. Based on the framework of PFC, the prediction of the future process behavior is first obtained using the current process input signal. Then, the fuzzy PID control based on the multi-step prediction is introduced to acquire the optimal control law. Finally, the case study on a temperature model of a coke furnace shows the effectiveness of the fuzzy PID control scheme when compared with conventional PID control and fuzzy self-adaptive PID control.     

High precision tracking control of a servo gantry with dynamic friction compensation

This paper is concerned with the tracking control problem of a voice coil motor (VCM) actuated servo gantry system. By utilizing an adaptive control technique combined with a sliding mode approach, an adaptive sliding mode control (ASMC) law with friction compensation scheme is proposed in presence of both frictions and external disturbances. Based on the LuGre dynamic friction model, a dual-observer structure is used to estimate the unmeasurable friction state, and an adaptive control law is synthesized to effectively handle the unknown friction model parameters as well as the bound of the disturbances. Moreover, the proposed control law is also implemented on a VCM servo gantry system for motion tracking. Simulations and experimental results demonstrate good tracking performance, which outperform traditional control approaches.     

基于Internet的网络化控制系统设计及控制研究

对于基于Internet的网络化控制系统,由于其网络延时具有随机、长时滞特性,使得控制系统稳定性和动态性能很差。本文基于离散的状态反馈网络化控制系统,提出了一种基于对象模型的多步预测补偿方法,通过在执行器端设置消息缓冲的办法实现时滞补偿的策略。基于Socket技术,应用LabWindows/CVI,采用以上时滞补偿方法设计了基于Internet的液位过程控制系统。实时跟踪控制实验和抗外部扰动实验结果结果表明,本文所提时滞补偿策略有效可行,能够很好地提高网络控制系统的动态性能。