A simple method of tuning parallel cascade controllers for unstable FOPTD systems

A simple method is proposed to design parallel cascade controllers for open loop unstable processes. A proportional (P)controller is considered for the secondary loop and a proportional integral (PI) controller is considered for the primary loop (P/PI control configuration). Coefficients of the corresponding powers of s (Laplace variable), in the numerator is matched with the coefficients of the corresponding powers of s in the denominator of a closed loop transfer function for a servo problem. Three simulation case studies are considered in this paper. The first case involves a stable secondary loop process and an unstable primary process, the second case involves both unstable primary and secondary processes and the third one, a simulation application to a nonlinear bioreactor model equations. For comparison purposes, P/PI controller design is also carried out by improved simultaneous relay autotuning method, synthesis method and minimizing ISE criterion method. It is found that the proposed method gives a better performance. Robust stability analysis using the complimentary sensitivity function is carried out. The present method is found to be more robust.     

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.     

The generalized forced oscillation method for tuning PID controllers

In this paper a generalized tuning methodology for proportional–integral–derivative (PID) controllers is proposed. The methodology is akin to the Ziegler–Nichols forced oscillation method, inheriting fully its practical appeal, but can be applied to much more general classes of plants. This generalization is achieved by employing a relay with adjustable phase (RAP) in a relay feedback experiment, and the tuning consists of formulas based on measurements obtained from this experiment. Experimental results in a liquid processing plant with of-the-shelf industrial equipments illustrate the performance of the methodology and the practical procedures involved in its application, which can be fully automated.     

Simple method of designing centralized PI controllers for multivariable systems based on SSGM

A method is given to design multivariable PI/PID controllers for stable and unstable multivariable systems. The method needs only the steady state gain matrix (SSGM). The method is based on the static decoupler design followed by SISO PI/PID controllers design and combining the resulted decoupler and the diagonal PI(D) controllers as the centralized controllers. The result of the present method is shown to be equivalent to the empirical method proposed by Davison EJ. Multivariable tuning regulators: the feed-forward and robust control of general servo-mechanism problem. IEEE Trans Autom Control 1976;21:35–41. Three simulation examples are given. The performance of the controllers is compared with that of the reported centralized controller based on the multivariable transfer function matrix.     

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.     

Fuzzy model-based observers for fault detection in CSTR

Under the vast variety of fuzzy model-based observers reported in the literature, what would be the properone to be used for fault detection in a class of chemical reactor? In this study four fuzzy model-based observers for sensor fault detection of a Continuous Stirred Tank Reactor were designed and compared. The designs include (i) a Luenberger fuzzy observer, (ii) a Luenberger fuzzy observer with sliding modes, (iii) a Walcott–Zak fuzzy observer, and (iv) an Utkin fuzzy observer. A negative, an oscillating fault signal, and a bounded random noise signal with a maximum value of ±0.4 were used to evaluate and compare the performance of the fuzzy observers. The Utkin fuzzy observer showed the best performance under the tested conditions.     

Performance assessment of static lead-lag feedforward controllers for disturbance rejection in PID control loops

This paper assesses the performance of feedforward controllers for disturbance rejection in univariate feedback plus feedforward control loops. The structures of feedback and feedforward controllers are confined to proportional-integral-derivative and static-lead-lag forms, respectively, and the effects of feedback controllers are not considered. The integral squared error (ISE) and total squared variation (TSV) are used as performance metrics. A performance index is formulated by comparing the current ISE and TSV metrics to their own lower bounds as performance benchmarks. A controller performance assessment (CPA) method is proposed to calculate the performance index from measurements. The proposed CPA method resolves two critical limitations in the existing CPA methods, in order to be consistent with industrial scenarios. Numerical and experimental examples illustrate the effectiveness of the obtained results.     

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.     

A novel auto-tuning method for fractional order PI/PD controllers

Fractional order PID controllers benefit from an increasing amount of interest from the research community due to their proven advantages. The classical tuning approach for these controllers is based on specifying a certain gain crossover frequency, a phase margin and a robustness to gain variations. To tune the fractional order controllers, the modulus, phase and phase slope of the process at the imposed gain crossover frequency are required. Usually these values are obtained from a mathematical model of the process, e.g. a transfer function. In the absence of such model, an auto-tuning method that is able to estimate these values is a valuable alternative. Auto-tuning methods are among the least discussed design methods for fractional order PID controllers. This paper proposes a novel approach for the auto-tuning of fractional order controllers. The method is based on a simple experiment that is able to determine the modulus, phase and phase slope of the process required in the computation of the controller parameters. The proposed design technique is simple and efficient in ensuring the robustness of the closed loop system. Several simulation examples are presented, including the control of processes exhibiting integer and fractional order dynamics.     

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.     

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。     

显微图像的直线描述和检测算法

实现一种对不同直线进行检测的算法。运用于图像中轴变换、凸包逼近、矩边逼近等算法。该方法的主要优点有:(1)交互性:可由人工设置检测直线的甑别条件;(2)普适性和灵活性:可检测不同类型的直线。实验结果表明该方法对于检测数码显微镜捕获的图像的直线具有非常大的实用意义。     

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.