Model Reference Fuzzy Adaptive PID Control of Paraffin Oil Level in Capsule Forming Machine

滴丸机定型杯石蜡油液位控制系统是一个存在非线性、参数时变性和耦合性的复杂系统.通过分析建立了该液位系统的数学模型,并且将自适应控制、模糊控制和PID控制结合起来,提出了一种模型参考模糊自适应PID控制方法.该方法无需辨识被控对象参数,实时性好,便于在线控制.仿真结果表明,该方法具有较好的动态品质和调节精度,以及很强的鲁棒性,即使当被控对象参数摄动20%时,依然可以获得理想的控制效果.现场运行实验结果也表明了该方法的有效性.The paraffin oil level control system in capsule forming machine is a nonlineart,ime-variant and coupling system.The mathematical model of the level control system was established.And a new model reference fuzzy adap-tive PID(MRFA-PID)control method was proposed by combining the adaptive control,fuzzy control and PID control techniques.Without need to identify the parameters of the controlled plantt,he proposed method has a good real-time performance,and is easy to be implemented on line.Simulation results show that the proposed method is efficient to design a robust paraffin oil level control system for capsule forming machine with good dynamic character and high regulation precision.Even though the parametersp′erturbation reaches 20%t,he closed-loop system still has satisfied dynamic performance.The effectiveness of the proposed method is also verified by physical experiment.厦门市科技计划资助项目(3502Z2006008

Optimized Kernel-Based Conformal Predictor for Online Fault Detection

为了提高相符预测器的计算效率,在算法中引入基于核的度量学习.将其学习过程分解成2部分:先通过提高75%的训练样本的类可分性获得1个优化核;然后在优化的核空间中采用k近邻方法设计奇异度函数,并使用剩下的25%的样本实现标准的相符预测器算法.将新算法应用于田纳西-伊斯曼过程的多类故障诊断问题,实验结果表明,在保证高的预测效率的同时,新算法可以显著降低计算时间.In order to improve the computational efficiency of conformal predictora,procedure of adaptive kernel-based distance metric learning was incorporated in the algorithm.The learning process was divided into two stages.Firstlya,n op-timized kernel was obtained by increasing the class separability of 75% of the training samples.Secondlyt,he k nearest neighbor classifier was used to design a nonconformity measure function in the optimized kernel space.And then the stan-dard conformal predictor algorithm was conducted on the remaining 25% of the training samples.The new method was ap-plied to the multiple fault diagnosis of Tennessee Eastman process.The results show that the new algorithm provides substan-tial reductions in computational timea,nd ensures high predictive efficiency as well.厦门大学985二期工程信息创新平台资助项目(0000-x07204);厦门市科技计划资助项目(3502Z20083028

Cycle-deadlock Control of Rail Guided Vehicles Systems via Petri Nets

为实现自动小车存取系统的实时控制,基于双重着色赋时PETrI网(COlOrEd TI MEd PETrI nETS,CTPn)构建了rgVS系统(rAIl-guIdEd VEHIClES SySTEM,rgVS)的动态模型。同时为了提高rgVS系统的存储效率,对rgV小车采用基于最短路径的调度策略。并针对rgVS系统的临界状态即将发生环路(环路链)死锁的状况,提出了一种死锁预防的方法。最后基于VC.nET验证其有效性。In order to implement the real time control of the Rail-Guided Vehicles systems,a deadlock control modeling method via Dual Colored Timed Petri Nets was proposed.Moreover,the scheduling strategy for the RGVs system based on shortest path method was addressed to improve the efficiency of storage and retrieval.Then,the critical state in deadlock free was identified and FCFS policy was applied to solve it.Finally,experimental results verified the effectiveness of the policies.厦门大学985二期信息创新平台项目资

Fault diagnosis method based on modified random forests

为解决不可识别故障诊断中无法有效定位的问题,提出一种基于改进随机森林的故障诊断方法。该方法通过改进决策树的bAggIng方式,采用条件概率指数进行决策树的无偏节点分裂,并以权重投票法综合决策树的分类结果。在此基础上,利用变量重要性测量来获取辅助故障定位的故障原型指数,从而较好地弥补了随机森林和传统机器学习在故障诊断中的不足和局限性。最后在一个标准数据集和田纳西-伊斯曼故障诊断的问题上进行验证,结果证明了该方法的有效性与可行性。To solve the problem of inefficient determining fault location in unidentified fault diagnosis of traditional machine-learning technologies, a fault diagnosis method based on modified random forests was proposed.Firstly, random decision trees were created via modified algorithm of bagging and unbiased split selection based on conditional probability index so as to construct random forests.Secondly, weighted voting was applied to combine the prediction of the decision trees.Then, fault prototypes were computed through the measurement of variable-importance in random forests, which assisted in determining the fault location.Finally, the proposed method was illustrated and documented thoroughly in an application of standard dataset and Tennessee Eastman Process (TEP) fault diagnosis.The results verified the presented approach's feasibility and effectiveness.国家自然科学基金资助项目(60704043)---

Multistage Inverse Modeling Method and Its Application in Gelatin Solution Production Process

针对一类串联型工业大系统,提出了多阶段逆模型建模方法:将串联大系统分为若干个阶段,以产品质量指标作为过程设计的起点,用逆向推理的方法,建立各个阶段的逆模型;根据产品质量指标的要求,直接求出各个阶段的控制变量设定值。将该方法应用于胶液生成过程的软测量建模,采用多阶段建模方法和整体建模方法分别建立了基于bP神经网络的胶液生成过程逆模型,并从误差平方和MSE和命中率等方面对两种建模方法的建模精度进行了比较。结果表明,多阶段建模方法可以获得更高的建模精度;同时,具有更大的灵活性;而且逆模型方法可以根据质量指标求出控制变量设定值,更便于实际应用。Aiming at a class of serially connected industrial system,a novel multistage inverse modeling method was presented.The large-scale system is divided into several stages.Using specified product qualities as a starting point for process design.By backward reasoning the required process conditions and the control variable set points of all stages for processing system were found.The inverse models of gelatin solution production process were established based on the BP neural network by using multistage modeling method and whole stage modeling method,and modeling accuracy comparison were made from error and hit rates.The simulation results indicate the model based on the proposed method has smaller error and higher hit rates.Meanwhile,the break down of the sub models increases the flexibility of model development and reduces the effort to change the model when the sub models change.And the required process conditions and the control variable set points of all stages for processing system were found according to specified product qualities.Thus,it is easy to be really applied.This method has been successfully applied on improving the gelatin solution production process and product quality control.厦门市科技计划项目(3502Z20083028);国家自然科学基金项目(50843059);福建省教育厅科技项目(JA08218

Study on Modeling and Optimizing Control of Soft Capsule Dropping Pills Pharmaceutical Process

本论文以软胶囊滴丸制药生产工艺过程为研究对象，以提高软胶囊滴丸产品合格率和质量稳定性为研究目标，基于智能控制、数据驱动建模与智能优化算法对该过程进行建模与优化控制研究。主要工作如下： 首先，对软胶囊滴丸制药生产工艺过程进行了系统分析：软胶囊滴丸过程包含了多个子系统，各子系统本身也各具特点，如明胶溶液生成过程子系统包含多个环节，期间会发生复杂的物理和化学变化，具有明显的非线性，中间控制变量较多，是一个十分复杂的工业过程；明胶温度子系统、石蜡油液位子系统和脉冲压力子系统中则存在不同程度的非线性、参数时变性和纯滞后等问题。在此基础上，针对该过程中存在的问题和各子系统的不同特点，设计相应的控制策略，...This article takes soft capsule dropping pills pharmaceutical production process as the research object. In order to improve the yield of soft capsule dropping pills and its stability of product quality, the modeling and optimizing control are studied based on intelligent control, data-driven modeling and intelligent optimization algorithms. The main work in this dissertation is presented as follo...学位：工学博士院系专业：信息科学与技术学院自动化系_控制理论与控制工程学号：2322006015337

Adaptive control of pulse pressure based on pattern recognition

脉冲滴丸机压力控制系统是具有非线性、参数时变性和耦合性特征的复杂系统,系统响应要求快速、准确、鲁棒性强,但传统的控制方法如常规的固定参数的PID控制器很难使系统同时达到这种最优控制。因此,提出了将自适应控制、模式识别和PID控制相结合的思想,设计了一种基于模式识别的脉冲压力自适应控制策略,通过在线辩识系统的动态输出,根据系统响应所处的状态,采取相应的控制算法,使系统得到了较好的控制。MATLAB仿真和现场实验结果均表明该方法具有较高的动态性能和控制精度,以及较强的鲁棒性。该控制系统已成功投入现场运行。The pulse pressure control system in pulse capsule forming machine is a nonlinear,time-variant and cou- pling system.The system requires good speed,accuracy and robustness performances,but they are hardly obtained simultaneously using traditional methods,such as preset parameter PID controller.To handle this problem,a new a- daptive control policy based on pattern recognition is proposed by combining adaptive control,pattern recognition and PID control technique,which can achieve better results and identify the dynamic output of the system on line using different control strategies.MATLAB simulation and physical experiment results show that the proposed method is ef- ficient in designing a robust pulse pressure control system for pulse capsule forming machine and has good dynamic characteristics,high accuracy and strong robustness.The proposed control system has already used in field applica- tion successfully.国家自然科学基金(60704042);; 厦门市科技计划指导性项目(3502Z2006008)资助项

Improvement of the New Six-head Capsule Forming Machine

针对原设备存在的低位槽溢油现象和明胶温度控制系统超调现象,重点改进和设计了液位和胶温控制系统,将模糊控制引入胶温控制,在MATLAB仿真的基础上,给出了基于PLC(Programmable Logic Controller)的软件和硬件实现;采用SMC压力传感器取代了浮球液位控制,通过PLC模拟量的AD(Analog-Digital)模组采集数据,并经逻辑运算后对液位实施控制;同时完善了人机界面的一些画面的功能及报警功能,提供更强大的帮助功能和一些历史数据如历史趋势图等的信息保存功能.The level control system and the gelatin temperature control system were better designed and Fuzzy PID control was applied in the gelatin temperature control system of the new six-head capsule forming machine to solve the paraffin oil overflow from low position and the overshooting of gelatin temperature.Based on MATLAB simulation,implementation of the PLC-based hardware and software was given.The SMC pressure transmitter was adopted to substitute for the level control float,and the level control was implemented after logic operation based on data gathered by PLC AD module.Functions of picture,warning,assistance and data reservation in the man-machine interface were improved.厦门市科技计划指导性项目(3502Z2006008

Application of Hybrid Fuzzy PID in Gelatin Temperature Control System Based on PLC

从一类工业过程控制对象出发,针对传统PID控制存在的设定值跟随特性不佳的问题,设计出一种基于变设定值权重思想的新型混合模糊PID控制器,该方法通过模糊系统的输出在线修正PID控制器比例作用部分设定值的加权系数,使系统的目标值跟随特性得到改善,并通过MATLAB仿真和PLC编程两种方式加以实现,结果表明本文所设计的控制器不仅响应速度快,而且超调量小,具有很好的设定值跟随特性,在模拟运行中亦取得了优于传统PID控制器的效果.Proceeding from a kind of process plants,aiming at such problems as bad set-point following,the new hybrid fuzzy PID controller based on set-point weight tuning was presented.The set-point weight of the proportional part acted on the PID controller was modified online by fuzzy inference system,so the command tracking was greatly improved.Moreover,realizations of this method based on MATLAB simulation and PLC were also provided,which show that both the overshoot and rise time in set point following can be reduced,so a good set-point following is assured.The superiority of this method is also demonstrated in the application.厦门市科技计划项目(3502Z2006008)资