An effective frequency domain approach to tuning non-PID controllers for high performance

In this paper, a new tuning method is proposed for the design of non-PID controllers for complex processes to achieve high performance. Compared with the existing PID tuning methods, the proposed non-PID controller design method can yield better performance for a wide range of complex processes. A suitable objective transfer function for the closed-loop system is chosen according to process characteristics. The corresponding ideal controller is derived. Model reduction is applied to fit the ideal controller into a much simpler and realizable form. Stability analysis is given and simulation examples are provided to demonstrate the effectiveness of the proposed method.     

一种并行系统时基误差自适应估计方法

在并行采集系统中,通道间时基延迟的不一致性严重降低了系统性能.针对时间延迟估计算法多基于时域实现,需进行复杂的插值运算以获取采样间隔非整数倍时基延迟的问题,本文基于时基误差的频域模型,将通道间的误差信号建模为自适应滤波器,提出了一种无需插值的估计算法.计算机仿真及实际应用验证结果表明,该方法能动态跟踪时基延迟变化,有效地估计通道时延,具有迭代次数少、运算量小、实时性高的特点.     

A PSO-based optimal tuning strategy for constrained multivariable predictive controllers with model uncertainty

This paper describes the development of a method to optimally tune constrained MPC algorithms with model uncertainty. The proposed method is formulated by using the worst-case control scenario, which is characterized by the Morari resiliency index and the condition number, and a given nonlinear multi-objective performance criterion. The resulting constrained mixed-integer nonlinear optimization problem is solved on the basis of a modified version of the particle swarm optimization technique, because of its effectiveness in dealing with this kind of problem. The performance of this PSO-based tuning method is evaluated through its application to the well-known Shell heavy oil fractionator process.     

A tuning algorithm for model predictive controllers based on genetic algorithms and fuzzy decision making

Model Predictive Control is a valuable tool for the process control engineer in a wide variety of applications. Because of this the structure of an MPC can vary dramatically from application to application. There have been a number of works dedicated to MPC tuning for specific cases. Since MPCs can differ significantly, this means that these tuning methods become inapplicable and a trial and error tuning approach must be used. This can be quite time consuming and can result in non-optimum tuning. In an attempt to resolve this, a generalized automated tuning algorithm for MPCs was developed. This approach is numerically based and combines a genetic algorithm with multi-objective fuzzy decision-making. The key advantages to this approach are that genetic algorithms are not problem specific and only need to be adapted to account for the number and ranges of tuning parameters for a given MPC. As well, multi-objective fuzzy decision-making can handle qualitative statements of what optimum control is, in addition to being able to use multiple inputs to determine tuning parameters that best match the desired results. This is particularly useful for multi-input, multi-output (MIMO) cases where the definition of "optimum" control is subject to the opinion of the control engineer tuning the system. A case study will be presented in order to illustrate the use of the tuning algorithm. This will include how different definitions of "optimum" control can arise, and how they are accounted for in the multi-objective decision making algorithm. The resulting tuning parameters from each of the definition sets will be compared, and in doing so show that the tuning parameters vary in order to meet each definition of optimum control, thus showing the generalized automated tuning algorithm approach for tuning MPCs is feasible.     

New iterative method for model updating based on model reduction

Model reduction technique is usually employed in model updating process. Here, a new iterative method associating the model updating method with the model reduction technique is investigated. Using the traditional iterative method, the errors resulted from replacing the reduction matrix of the experimental model with that of the finite element (FE) model are not fully considered, which needs more iterations and computing time. In order to reduce the errors produced in the replacement, a new iterative method is proposed based on the traditional method, in which the correction term related to the errors is added. The comparisons between the traditional iterative method and the proposed iterative method are shown by model updating examples of solar panels and both of these two iterative methods combine the cross-model cross-mode (CMCM) method and the succession-level approximate reduction (SAR) technique. The results indicate that the convergence rate and the computing time of the new method are significantly superior to those of the traditional iterative method with or without noise.     

A fast method for online closed-loop system identification

In the modern control schemes broadly applied presently in the servo drive system of machine tools, the sampling frequency has been growing larger and larger becomes higher and higher, so it is important to keep up-to-date with the variance of the actual system parameters. As a solution to the problem, a novel method developed from the recursive extended least squares (RELS) algorithm in terms of the computation of functions, operates in such a way that the parameters of the system model are revised only when several proper new groups of data are obtained. The simulation and experimentation of online direct closed-loop system identification indicate that, by selecting the updating step, this method is able to effectively cut down the identifying cost time while obtaining satisfactory accuracy of estimation.     

The sensitivity method in finite element model updating: A tutorial

The sensitivity method is probably the most successful of the many approaches to the problem of updating finite element models of engineering structures based on vibration test data. It has been applied successfully to large-scale industrial problems and proprietary codes are available based on the techniques explained in simple terms in this article. A basic introduction to the most important procedures of computational model updating is provided, including tutorial examples to reinforce the reader’s understanding and a large scale model updating example of a helicopter airframe.     

MIMO model of an interacting series process for Robust MPC via System Identification

This paper discusses the empirical modeling using system identification technique with a focus on an interacting series process. The study is carried out experimentally using a gaseous pilot plant as the process, in which the dynamic of such a plant exhibits the typical dynamic of an interacting series process. Three practical approaches are investigated and their performances are evaluated. The models developed are also examined in real-time implementation of a linear model predictive control. The selected model is able to reproduce the main dynamic characteristics of the plant in open-loop and produces zero steady-state errors in closed-loop control system. Several issues concerning the identification process and the construction of a MIMO state space model for a series interacting process are deliberated.     

相序检测的极速算法

醉提出了一种相序检测的新算法，该算法运算极快，使相序检测的速度提高了1000至10000倍，可广泛运用于数字化检测之中。     

Taguchi method for analyzing the tactical planning model in a closed-loop supply chain considering remanufacturing option

Recent years, there has been a growing interest in reverse logistics, recycling, remanufacturing, and reusing due to the environmental concerns, economical issues, and legal obligations. Companies should take into account the recovery options such as recycling, remanufacturing, etc. while preparing their tactical plans. In this paper, a mixed integer linear programming model is proposed for tactical planning in a conceptual closed-loop supply chain with remanufacturing option. In the model, both forward and reverse flows are involved and two production alternatives are considered: either production of new products directly in manufacturing plants or bringing the returned products back to “as new condition” in the remanufacturing facilities. The proposed model attempts to optimize all of the consecutive stages in the closed-loop supply chain. Hence, the purpose of this research is to formulate a mathematical programming model to focus primarily on integrating remanufacturing as a recovery option into tactical planning process. The proposed model is applied to an illustrative case and solved by LINGO 9.0 optimization solver. In order to obtain the best objective function value that is targeted, the effects of the major factors regarding reverse flows and remanufacturing system are examined with the help of Taguchi experimental design technique at the end of the study. Analysis of variance, Taguchi's signal/noise ratios, analysis of means graphs and interaction graphs are provided by MINITAB 14 software and interpreted for the evaluation of experimental results and effects of related factors.     

A model-based ultrasonic quantitative evaluation method for bonding quality of multi-layered material

Reflection coefficients play an important role in the quantitative evaluation of the bonding quality of the interfaces of the multi-layered composite material. This paper proposes a reflection coefficient-based echo signal model and a new Gaussian model based blind deconvolution method for extracting reflection coefficients of bonding interface. The traditional deconvolution problem can be converted into a parameters estimation process in this model. Moreover, in order to avoid the potential computational burden caused by multiple parameters estimation and the much dependence on the initial parameter values during the estimation process, empirical mode decomposition (EMD) method and an improved Genetic Algorithm are used for parameters estimation. Simulation experiment verified the reliability of this method at different signal-to-noise ratio and with different initial parameter values, and then, reflection coefficients reconstruction of a metal multi-layered composite material specimen is performed through measurement experiment and the result is satisfying. Both the simulation and measurement experiments proved the feasibility and validity of this method.     

A new method for tuning PI controllers with symmetric send-on-delta sampling strategy

In this paper we present a new method for tuning PI controllers with symmetric send-on-delta (SSOD) sampling strategy. First we analyze the conditions that produce oscillations in event based systems considering SSOD sampling strategy. The Describing Function is the tool used to address the problem. Once the conditions for oscillations are established, a new robustness to oscillation performance measure is introduced which entails with the concept of phase margin, one of the most traditional measures of relative stability in closed-loop control systems. Therefore, the application of the proposed robustness measure is easy and intuitive. The method is tested by both simulations and experiments. Additionally, a Java application has been developed to aid in the design according to the results presented in the paper.     

A model-based identification method of transverse cracks in rotating shafts suitable for industrial machines

This paper presents a model-based transverse crack identification method suitable for industrial machines. The method is validated by experimental results obtained on a large test rig, which was expressly designed for investigating the dynamical behaviour of cracked horizontal rotors. The identification method and the relative theory is briefly presented, while three different types of cracks are considered: the first is a slot, therefore not actually a crack since it has not the typical breathing behaviour, the second a small crack (14% of the diameter) and the third a deep crack (47% of the diameter). The excellent accuracy obtained in identifying position and depth of different cracks proves the effectiveness and reliability of the proposed method.     

机械产品内部构件状态的视觉检测方法

文中研究了机械产品内部构件状态的视觉检测方法。运用机器视觉技术对产品的图像进行预处理、特征提取和匹配操作,基于模式识别的方法建立了故障诊断模型,最终实现了产品内部构件状态的自动检测。利用所述方法,对具体的机械产品进行了检测试验,结果表明该方法实用、迅速、可靠,对于自动检测复杂机械产品内部构件的状态具有普遍意义。     

A systematic approach for the sequence controller design in manufacturing systems

This paper presents a systematic approach for the design and implementation of the sequence controller in manufacturing systems. By employing the IDEF0, we construct the simplified Petri net controller (SPNC) through the material flow diagram and the information flow diagram. Then, the ladder logic diagram (LLD) can be transformed from the SPNC through the token passing logic (TPL). The proposed approach, including the IDEF0, SPNC, and TPL tools, leads to the standard IEC1131-3 LLD for PLC implementation. Finally, an application of a stamping process is provided to illustrate the design procedure of the developed approach .     

一类基于统计理论的神经网络模式识别方法

本文针对用人工神经网络进行模式识别时样本特征指标过多的问题,提出用统计理论的主成分分析方法对数据进行预处理,再选出几个主成分作为神经网络的输入节点,从而极大地简化人工神经网络,提高了模式识别的效果。     

Coherent fluctuation nephelometry: A high-sensitivity method for detecting particles in liquids

A new method for detecting micron and submicron particles in liquids by measuring the intensity fluctuations of coherent radiation scattered from these particles is described and compared to available techniques. It is shown that this method allows the record-breaking detection sensitivities of 10³–10⁴ particles/ml to be attained at a simple design of the analyzer.     

A near-wall reynolds stress model for backward-facing step flows

A near-wall Reynolds stress model has been used in numerical computations for two-dimensional, incompressible turbulent flows over backward-facing steps. Numerical results are compared with Direct Numerical Simulation data as well as experimental data for flow quantities such as the skin friction, wall pressure,U-velocity and the Reynolds stress. Budgets of the transport equations for theU-velocity, turbulence kinetic energy,k and the Reynolds shear stress,— are also calculated and compared with the Direct Numerical Simulation data. The comparison reveals that the near-wall Reynolds stress model predicts the reattachment length fairly accurately. The near-wall Reynolds stress model also predicts the development of the boundary layer downstream of the reattachment point correctly when the Reynolds number is low. However, the model generally predicts a weak separation bubble and a slowly developing boundary layer when the Reynolds number is high.     

A robust and reliable method for detecting signals of interest in multiexponential decays

The concept of rejecting the null hypothesis for definitively detecting a signal was extended to relaxation spectrum space for multiexponential reconstruction. The novel test was applied to the problem of detecting the myelin signal, which is believed to have a time constant below 40 ms, in T2 decays from magnetic resonance imagining of the human brain. It was demonstrated that the test allowed the detection of a signal in a relaxation spectrum by using only the information in the data, thus avoiding any potentially unreliable prior information. The test was implemented both explicitly and implicitly for simulated T2 measurements. For the explicit implementation, the null hypothesis was that a relaxation spectrum existed that had no signal below 40 ms and that was consistent with the T2 decay. The confidence level by which the null hypothesis could be rejected gave the confidence level that there was signal below the 40 ms time constant. The explicit implementation assessed the test's performance with and without prior information where the prior information was the non-negative relaxation spectrum assumption. The test was also implemented implicitly with a data conserving multiexponential reconstruction algorithm that used left invertible matrices and that has been published previously. The implicit and explicit implementations demonstrated similar characteristics in detecting the myelin signal in both the simulated and experimental T2 decays, providing additional evidence to support the close link between the two tests. When the relaxation spectrum was assumed to be non-negative, the novel test required signal to noise ratios (SNRs) approaching 1000 in the T2 decays for detection of the myelin signal with high confidence. When the relaxation spectrum was not assumed to be non-negative, the SNR requirements for a detection with high confidence increased by a factor of 25. The application of the test to a T2 decay from human white matter, measured in vivo with a SNR of 650, demonstrated a solid detection of the signal below 40 ms believed to be due to the myelin water. This study demonstrated the robustness and reliability of extending the concept of rejecting the null hypothesis to relaxation spectrum space. The study also raised serious questions about the susceptibility to false positive detection of the myelin signal of the multiexponential reconstruction algorithms currently in use.     

A radio-wave method for detecting and identifying permeable inclusions in stratified inhomogeneous media

The problems associated with the efficiency of practical application of a numerical algorithm for detecting, locating, and identifying inhomogeneous dielectric inclusions in plane-layered media are considered. The results of computational experiments on the determination of both physical and geometric parameters of inhomogeneities and the effect of the measurement error on the quality of the inspection procedure are presented. This method can be used in the nondestructive testing of the quality of industrial dielectric articles.