一种新的整定方法用于参数不确定条件下二自由度内部模型控制(英文)

Internal model control （IMC） yields very good performance for set point tracking, but gives sluggish response for disturbance rejection problem. A two-degree-of-freedom IMC （2DOF-IMC） has been developed to overcome the weakness. However, the setting of parameter becomes a complicated matter if there is an uncertainty model. The present study proposes a new tuning method for the controller. The proposed tuning method consists of three steps. Firstly, the worst case of the model uncertainty is determined. Secondly, the parameter of set point con- troller using maximum peak （Mp） criteria is specified, and finally, the parameter of the disturbance rejection con- troller using gain margin （GM） criteria is obtained. The proposed method is denoted as Mp-GM tuning method. The effectiveness of Mp-GM tuning method has evaluated and compared with IMC-controller tuning program （IMCTUNE） as bench mark. The evaluation and comparison have been done through the simulation on a number of first order plus dead time （FOPDT） and higher order processes. The FOPDT process tested includes processes with controllability ratio in the range 0.7 to 2.5. The higher processes include second order with underdarnped and third order with nonminimum phase processes. Although the two of higher order processes are considered as difficult processes, the proposed Mp-GM tuning method are able to obtain the good controller parameter even under process uncertainties.     

A SIMPLE TITO PI TUNING METHOD SUITABLE FOR INDUSTRIAL APPLICATIONS

A simple tuning method for TITO (Two-Input, Two-Output) PI controllers will be presented in this article. The method is an extension of the SISO PID tuning method based on Internal Model Control (IMC). An approximate model for tuning purpose will be developed using the information from the interaction measure of the TITO system. The procedure of the tuning method is very simple and straightforward utilizing only two bias-relay feedback tests. The tuning method can easily be applied to various industrial situations with almost no need for a priori process knowledge. Various TITO examples will be used to demonstrate the performance of this tuning method. Both setpoint and load disturbance responses will be examined     

A one-step tuning method for PID controllers with robustness specification using plant step-response data

This paper presents a novel method for proportional-integral-derivative (PID) controller tuning directly using the step response data of the process without resorting to a process model. The required process data are collected from a one-shot step test that can be conducted under either closed-loop or open-loop conditions. The proposed method derives the PID parameters so that the resulting control system behaves as closely as possible to the prescribed reference model. Two structures of the reference model are considered for general design and improved disturbance rejection, respectively. A simple one-dimensional optimization problem is formulated to determine an appropriate reference model for the controlled process. Moreover, the proposed PID tuning method includes a robustness specification based on the maximum peak of sensitivity function that enables the user to explicitly address the trade-off between performance and robustness. Simulation examples are provided to illustrate the superiority of the proposed method over existing (model-based) tuning methods.     

GRAPHICAL TECHNIQUE FOR MODELING INTEGRATING (Non-SELF-REGULATING) PROCESSES WITHOUT STEADY-STATE PROCESS DATA

Model-fitting techniques for controller tuning that require the process to be initially at steady state cannot generally be used with integrating (non-self-regulating) processes. To address this issue, a graphical model-fitting technique is detailed and demonstrated for determination of first order plus dead time integrating model parameters from integrating process response plots. The resulting model parameters can be used directly in a range of tuning correlations designed specifically for integrating processes. The advantage of this technique is that it requires only two periods of constant manipulated and disturbance variables sustained just long enough for the process variable to respond and establish a clear slope. This is an important benefit because integrating processes generally cannot be maintained at an initial steady state as required when using techniques published for self-regulating processes. The result is an industry-friendly method. The method is demonstrated for level control in a pumped tank, a classical challenge in industrial practice. Both a simulation and a bench-scale experimental system are used in the demonstration studies.     

A new direct-synthesis tuning method for pi-controllers

A new efficient tuning method for proportional-integral (PI) controllers is proposed using overdamped closed-loop dynamics of the system. In line with other direct-synthesis and IMC methods, this new approach uses the desired closed-loop response to satisfy usual control and tuning objectives, but unlike the most other tuning methods hitherto-reported for PID controllers, it does not require that a process model be identified. Yet this new direct-synthesis (NDS) method is capable of making the controller perform the dual control functions of both good set-point tracking and disturbance rejection. Furthermore, it turns out that the new tuning method works equally well for difficult cases like large time delay and nonminimum phase processes. Finally, it can be said that this NDS method can be easily implemented and understood by the plant operating personnel because it has been developed emphasizing its on-site utility.     

GRAPHICAL TECHNIQUE FOR MODELING INTEGRATING (Non–SELF-REGULATING) PROCESSES WITHOUT STEADY-STATE PROCESS DATA

Model-fitting techniques for controller tuning that require the process to be initially at steady state cannot generally be used with integrating (non–self-regulating) processes. To address this issue, a graphical model-fitting technique is detailed and demonstrated for determination of first order plus dead time integrating model parameters from integrating process response plots. The resulting model parameters can be used directly in a range of tuning correlations designed specifically for integrating processes. The advantage of this technique is that it requires only two periods of constant manipulated and disturbance variables sustained just long enough for the process variable to respond and establish a clear slope. This is an important benefit because integrating processes generally cannot be maintained at an initial steady state as required when using techniques published for self-regulating processes. The result is an industry-friendly method. The method is demonstrated for level control in a pumped tank, a classical challenge in industrial practice. Both a simulation and a bench-scale experimental system are used in the demonstration studies.     

A SIMPLE METHOD FOR TUNING CASCADE CONTROL SYSTEMS

A simple method for tuning controllers in a cascade system is presented, In this method, all the relations that facilitate the tuning procedures are well prepared in terms of figures or simple equations. Using these figures and equations, the controller tuning for different configurations of cascade systems becomes easy and straightforward when process models are available. On the other hand, when process models are not available, a simple method that uses one single run of step input experiment to develop such models is proposed. Based on these developments in the controller tuning and process models, an autotuning system that uses relay feedback is presented. Unlike the existing autotuning systems, this proposed system conducts identification and controller tuning in a decoupled manner. As a result, no excessive trial- and-error efforts for modeling and tuning are required. Simulation results show the potential usage of such a method, It is interested to see that the resulting systems have almost compatible responses to those systems which have been designed optimally in one way or another as reported in the literature. It is not, however, the purpose of this article to emphasize on obtaining superior performance to all other existing methods, but to emphasize on its effectiveness and simplicity for application.     

ROBUST CLOSED LOOP LOG MODULUS DESIGN OF SISO SMITH PREDICTORS FOR A SPECIAL CLASS OF PROCESSES

Linear open loop stable or prestabilized SISO processes with uncertain or changing time delays are controlled via a Smith Predictor. The processes under consideration have no other nonminimum phase characteristics than the time delay. Further, the process models have an inherent integration constant of zero or one. A controller design procedure is presented which guarantees a robust closed loop system, where the major tuning parameter of the controller is a nonlinear function of the maximum closed loop Log Modulus and the model-plant mismatch.     

Frequency domain tuning approach for adaptive feedforward control using lead–lag compensators

The tuning of lead–lag compensators to be used as feedforward controllers for measured disturbances is performed in the frequency domain. The identification of process G_u and disturbance dynamics G_d uses extended recursive least squares, and the frequency responses are calculated from the least squares coefficients. A lead–lag compensator G_ll is designed which minimises the function $G_{{\rm ll}} (j\omega ) + (G_{{\rm d}} (j\omega ))/(G_{{\rm u}} (j\omega ))$ over a finite number of frequencies, using the Nelder–Mead simplex method. The effectiveness of the frequency domain tuning strategy is compared by simulation to established tuning rules for first‐order plus delay processes. The tuning method is experimentally verified on a pilot scale methanol–water distillation column. © 2011 Canadian Society for Chemical Engineering     

Half order plus time delay (HOPTD) models to tune PI controllers

Methods based on the first‐order plus time delay (FOPTD) model are very popular for tuning proportional‐integral (PI) controllers. The FOPTD model‐based methods are simple and their utility has been proved with many successful applications to a wide range of processes in practice. However, even for some overdamped processes where the FOPTD model seems to be applied successfully, these empirical FOPTD model‐based methods can fail to provide stable tuning results. To remove these drawbacks, a PI controller tuning method based on half‐order plus time delay (HOPTD) model is proposed. Because FOPTD model‐based methods can be applied to higher order processes, the proposed HOPTD model‐based method can be applied to higher order processes as well. It does not require any additional process information compared to the FOPTD model‐based method and hence can be used for overdamped processes in practice, complementing the traditional FOPTD model‐based methods. © 2016 American Institute of Chemical Engineers AIChE J, 63: 601–609, 2017     

TUNING PID CONTROLLER FOR OPEN-LOOP UNSTABLE PROCESSES WITH TIME DELAY

A calculation method of PID controller tuning for the first- and the second-order open-loop unstable process models with time delay is presented in this study. Optimum PID controller tuning data based on the models and minimum IAE criterion were obtained via Powell searching technique, and these data were then empirically correlated into several multiple-regression equations by a least-squares method. Thus PID controller tuning based on the models can easily be obtained by the calculation of these correlated equations. Simulation with a reset-feedback PID control algorithm has demonstrated that the proposed tuning method based on the first-order model can provide better results than the latest studies. In addition, simulation has also unveiled that tuning results based on the second-order models are superior to the first-order model for a higher-order process.     

基于VRFT的IMC-PID方法及其在水厂浊度控制中的仿真研究

针对城市供水出水浊度过程的大惯性、大时滞、非线性以及时变等特点,将虚拟参考反馈整定数据驱动方法引入到IMC-PID控制器的整定中来,提出了一种不基于模型参数的VRFT-IMC参数整定方法.该方法集合了内模控制鲁棒性强和数据驱动控制的自适应性两方面的优点,仿真表明其控制性能优于普通IMC-PID控制器,可望用于出水浊度等...     

A method for robustness analysis of controlled nonlinear systems

This paper presents an approach to analyzing robustness properties of nonlinear systems under feedback control. The core idea is to apply numerical bifurcation analysis to the closed-loop process, using the controller/observer tuning parameters, the set points, and parameters describing model uncertainty (parametric as well as unmodeled dynamics) as bifurcation parameters. By analyzing the Hopf bifurcation and saddle-node bifurcation loci with respect to these parameters, bounds on the controller tuning are identified which can serve as a measure for the robustness of the controlled system. These bounds depend upon the type as well as the degree of mismatch that exists between the plant and the model used for controller design.The method is illustrated by analyzing three control systems which are applied to a continuously operated stirred tank reactor: a state feedback linearizing controller and two output feedback linearizing controllers. While model uncertainty has only a minor effect on the tuning of the state feedback linearizing controller, this does not represent a very realistic scenario. However, when an observer is implemented in addition to the controller and an output feedback linearizing scheme is investigated, it is found that the plant-model mismatch has a much more profound impact on the tuning of the observer than it has on the controller tuning. In addition, two observer designs with different level of complexity are investigated and it is found that a scheme which makes use of additional knowledge about the system will not necessarily result in better stability properties as the level of uncertainty in the model increases. These investigations are carried out using the robustness analysis scheme introduced in this paper.     

化工过程深度神经网络软测量的结构与参数自动调整方法

深度学习在流程工业的软测量领域已经得到了应用。然而,深度神经网络（DNN）的结构和参数需要人工调整,这需要扎实的机器学习知识基础和丰富的参数调整经验,烦琐的调整过程限制了深度学习在化工领域的推广应用。在大量实验的基础上,对DNN的每个关键参数的选取过程进行了系统化的分析,提出了几乎无须人工干预的基于DNN软测量的结构和参数自动调整方法,极大地简化了参数调整过程,能够给工程技术人员学习及应用深度学习提供参考。对原油蒸馏装置及煤气化装置的案例分析验证了所提出方法的有效性和通用性。     

On‐line Tuning of Model Predictive Controllers Using Fuzzy Logic

This paper addresses the problem of tuning model predictive controllers for good performance. An automatic online tuning strategy is developed to adjust the prediction horizon, P, the diagonal elements of the input weight matrix, Λ, and the diagonal elements of the output weight matrix, Γ. The control horizon is left constant because its relative value with respect to P is more important. The tuning algorithm is based on the fuzzy logic concepts. Predefined fuzzy rules that formulate the general tuning guidelines available in the literature and the performance violation measure in the form of fuzzy sets determine the new tuning parameter values. Therefore, the tuning algorithm is cast as a simple and straightforward mechanism with modest computational requirements. This feature makes it more appealing for online implementation. The effectiveness of the proposed tuning method is tested through simulated implementation on a binary distillation column example and on a non linear CSTR example. The result of the simulations revealed the success of such a method.     

An automatic pid controller tuning method by frequency response techniques

An alternative Ziegler-Nichols (1942) controller tuning technique was proposed in this study. Under the proportional control of a single-loop control system, an arbitrary pulse testing in the set point was introduced to the system. The ultimate frequency and gain could both be directly calculated from the transients by frequency response techniques without any trial and error procedures. PID controller settings were thus obtained according to the Ziegler and Nichols' rules. Furthermore, this technique was extended to the tuning of a cascade control system. A procedure for simultaneously tuning the primary and secondary controllers with both loops in proportional control from a single pulse testing also is presented.     

Study on dynamic behavior adjustment of nonlinear chemical processes

In nonlinear chemical processes, many economically desirable operating conditions are located in unstable regions, leading to product quality degradation and safety problems. Therefore, determining how to adjust the dynamic behavior to make the process stable within its desired operational range is a topic of common interest within industrial and academic communities. This article presents a dynamic behavior adjustment method based on a washout filter‐aided controller with an improved parameter‐tuning algorithm to stabilize parts of the equilibrium manifold of chemical processes. In addition, applying this method to industrial toluene liquid‐phase catalytic oxidation shows that, by combining a conventional proportional‐integral (PI) controller with the proposed improved washout filter‐aided controller, the performance of set‐point tracking is improved for cases with parameter uncertainty. In general, the proposed dynamic behavior adjustment method will be effective for most chemical processes. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3189–3198, 2016     

一类交互式偏好进化方法及其在化工过程控制器整定中的应用(英文)

In response to many multi-attribute decision-making (MADM) problems involved in chemical processes such as controller tuning, which suffer human's subjective preferential nature in human–computer interactions, a novel affective computing and preferential evolutionary solution is proposed to adapt human–computer interaction mechanism. Based on the stimulating response mechanism, an improved affective computing model is intro-duced to quantify decision maker's preference in selections of interactive evolutionary computing. In addition, the mathematical relationship between affective space and decision maker's preferences is constructed. Subse-quently, a human–computer interactive preferential evolutionary algorithm for MADM problems is proposed, which deals with attribute weights and optimal solutions based on preferential evolution metrics. To exemplify applications of the proposed methods, some test functions and, emphatical y, control er tuning issues associated with a chemical process are investigated, giving satisfactory results.     

Closed-loop identification of systems using hybrid Box-Jenkins structure and its application to PID tuning

The paper describes a closed-loop system identification procedure for hybrid continuous-time Box-Jenkins models and demonstrates howit can be used for IMC based PID controller tuning. An instrumental variable algorithmis used to identify hybrid continuous-time transfer function models of the Box-Jenkins formfromdiscretetime prefiltered data, where the process model is a continuous-time transfer function, while the noise is represented as a discrete-time ARMA process. A novel penalizedmaximum-likelihood approach is used for estimating the discrete-time ARMA process and a circulatory noise elimination identification method is employed to estimate process model. The input-output data of a process are affected by additive circulatory noise in a closedloop. The noise-free input-output data of the process are obtained using the proposed method by removing these circulatory noise components. The process model can be achieved by using instrumental variable estimation method with prefiltered noise-free input-output data. The performance of the proposed hybrid parameter estimation scheme is evaluated by the Monte Carlo simulation analysis. Simulation results illustrate the efficacy of the proposed procedure. The methodology has been successfully applied in tuning of IMCbased flowcontroller and a practical application demonstrates the applicability of the algorithm.     

OPTIMALITY CHARACTERISTICS OF PI/PID CONTROLLERS: A COMBINED MIN-MAX/ISE INTERPRETATION

This communication addresses the tuning of PI and PID controllers on the basis of the IMC approach. The tuning is based upon a first order plus time delay (FOPTD) model and aims to achieve a step response specification. Through analysis it has been found that by using the IMC approach we get a PI or a PID depending on the rational approximation used for the time delay term. This article raises the question that the use of a PID instead of a PI controller should be based on another reason more related to the control objectives rather than the use of a better approximation for the time delay. An alternative tuning is presented here, from within the IMC formulation, based on a min-max optimization. From the tuning rule provided by this approach the optimum settings from an integral squared error criterion point of view are derived. The optimal controller results in being a PI controller. From this optimal controller as the starting point, the introduction of the derivative action can be seen as a detuning procedure that can increase the robustness of the controller. This approach provides further insight into the tuning of PI and PID controllers giving the (alternative) parameters a precise engineering meaning.