Adaptive generalised predictive control of high purity internal thermally coupled distillation column

Internal thermally coupled distillation column (ITCDIC) is a frontier in the energy‐saving distillation researches. One of the bottlenecks to prevent the column from being commercialised is the difficulty in control design due to the high sensitivity to disturbances, strong asymmetric nonlinearity and inverse response especially under high purity. An adaptive multivariable generalised predictive control (AM‐GPC) strategy of ITCDIC process is proposed to solve the difficulties in high purity. The simulation results of AM‐GPC are compared with single input and single output GPC (S‐GPC), multivariable GPC (M‐GPC), modified IMC (M‐IMC) and traditional PID control in detail. The performances confirm the accuracy and validity of AM‐GPC for the high‐purity ITCDIC process. © 2011 Canadian Society for Chemical Engineering     

基于神经网络和多模型的非线性自适应PID控制及应用

针对一类未知的单输入单输出离散非线性系统,提出了基于神经网络和多模型的非线性自适应PID控制方法。该方法由线性自适应PID控制器、神经网络非线性自适应PID控制器以及切换机构组成。采用线性自适应PID控制器可保证闭环系统所有信号有界;采用神经网络非线性自适应PID控制器可改善系统性能;通过引入合理的切换机制,能够在保证闭环系统稳定的同时,提高系统性能。理论分析表明,该方法能够保证闭环系统所有信号有界,如果适当地选择神经网络的结构和参数,系统的跟踪误差将收敛于任意给定的紧集。将所提出的方法应用于连续搅拌反应釜,仿真结果验证了所提出方法的有效性。由于该方法基于增量式数字PID控制器,在工业过程中有着广阔的应用前景。     

电弧炉电极调节PDF自适应控制系统

将鲁棒性强、超调小、响应速度快、易实现的PDF控制方法运用到电炉电极系统的控制上,其中在电极控制系统的设计方面,采用双闭环模式--速度环作为内环,电极的电流环作为外环.并对PID控制和PDF自适应控制进行了仿真,仿真结果表明PDF自适应控制优于PID控制.     

An energy effective PID tuning method for the control of polybutadiene latex reactor based on closed-loop identification

The PBL (Polybutadiene Latex) production process is a typical batch process. Changes of the reactor characteristics due to the accumulated scaling with the increase of batch cycles require adaptive tuning of the PID controller being used. In this work we propose a tuning method for PID controllers based on the closed-loop identification and the genetic algorithm (GA) and apply it to control the PBL process. An approximated process transfer function for the PBL reactor is obtained from the closed-loop data by using a suitable closed-loop identification method. Tuning is performed by GA optimization in which the objective function is given by ITAE for the setpoint change. The proposed tuning method showed good control performance in actual operations.     

Closed-loop step response identification of integrating and unstable processes

Motivated by the fact that integrating and unstable processes are usually operated in a closed-loop manner for safety and economic reasons, this paper proposes a systematic closed-loop identification method based on step response test to facilitate closed-loop system operation and on-line optimization. To avoid jeopardizing the closed-loop system stability of such a process, guidelines are given for proper implementation of a closed-loop step test for model identification. By introducing a damping factor to the closed-loop step response for realization of the Laplace transform in frequency domain, a frequency response estimation algorithm is developed in terms of the closed-loop control structure used for identification. Accordingly, three model identification algorithms are derived analytically in frequency domain to obtain the widely used low-order process models of first-order-plus-dead-time (FOPDT) and second-order-plus-dead-time (SOPDT). To enhance fitting accuracy for a higher order process, in particular for a specified frequency range interested to control design and on-line tuning, a weighted least-squares fitting algorithm is also given based on the estimated process frequency response points. Illustrative examples from the recent literature are used to demonstrate the effectiveness and merits of the proposed identification algorithms.     

PID controller tuning for desired closed-loop responses for SISO systems using impulse response

Most of the proportional-integral-derivative (PID) controller tuning methods reported in literature are based on the approximate plant models (FOPDT or SOPDT models) derived from the step response of the plant. In this paper, a new method of designing PID controllers using ‘impulse response’ instead of ‘step response’ of the plant is presented. Treating the impulse response of the plant as a statistical distribution, the ‘mean’ and the ‘variance’ of the distribution are calculated and used in the calculation of PID controller parameters. Thus, the proposed method requires no approximation of the plant by any model. In this paper, a direct synthesis approach to PID controller design is proposed that makes use of Maclaurin series of the desired closed-loop transfer function, truncated up to the first three terms. PID controller parameters are synthesized to match the closed-loop response of the plant to the desired closed-loop response. Formulae for the calculation of PID controller tuning parameters are derived for the desired closed-loop response models of the types FOPDT and SOPDT. Only stable SISO systems are considered. The PID controllers tuned result in closed-loop responses very close to the desired response and perform equally well compared to other tuning methods reported in literature.     

Synthesis of PID controller for unstable and integrating processes

Properly designed controllers provide stable closed-loop response for open-loop unstable processes. Internal model controller equivalent PID tuning rules for low order unstable plus dead time systems are synthesized in this work. The controller is approximated near the vicinity of zero (origin). Controller parameters are derived by equating the closed-loop response to a control-signature (desired closed-loop response) involving a user defined tuning parameter, λ. Simulations are carried out to show the performance of the proposed tuning scheme for both set point and disturbance rejection cases.     

非线性多变量系统的多模型广义预测解耦控制

针对实际工业过程中多变量系统存在着非线性、工况范围广、耦合强的特点,提出基于设定值观测器的非线性多模型广义预测解耦控制算法。该方法由线性广义预测控制器、一种新的设定值观测器和切换机构组成。理论分析和仿真结果表明,该控制策略不但可以保证闭环系统B IBO稳定和渐近收敛,而且能够得到很好的控制效果。     

基于ANFIS模型的Pr/Nd萃取过程预测控制

针对稀土萃取过程自动化程度低、经验控制误差大、手动调节效率不高的问题,建立了萃取过程ANFIS模型,实现了各控制流量的自动调节。考虑稀土萃取过程非线性和动态特性,采用自适应神经模糊推理系统(ANFIS)对Pr/Nd萃取过程进行描述,在保证高精度的组分含量预测输出基础上,运用广义预测控制方法(GPC)实现各控制流量的优化控制;最后,基于Pr/Nd萃取过程动态数据进行仿真实验。通过与传统PID方法的实验对比,表明了本文方法的有效性。     

Improving ceramic additive manufacturing via machine learning-enabled closed-loop control

Advanced ceramic products are widely used in aerospace, automotive, electronic, laboratory equipment, and other industries. To achieve the geometric complexity and desirable properties that are difficult to obtain by conventional manufacturing methods, ceramic additive manufacturing (AM) methods have been studied intensively in recent years. However, the adaptive control with feedback is not currently implemented in any commercially available ceramic three-dimensional printer. Robocasting is one of the most widely utilized constant-volumetric-flow AM processes for creating various ceramic materials at a low cost. This study employed robocasting as a model to implement an adaptive control with a feedback loop in the ceramic AM process. In this research, processing load that was proportional to the processing pressure, width of the print, and length of extrusion were selected to be representative of process signal, quality signal, and control parameter, respectively. First, a database of the load and extrusion length was established. An artificial neural network model was created using that established database. The data-driven, closed-loop control was integrated into the robocasting process. Finally, the improvement was validated by comparing the quality of the prints produced by both the closed-loop process with the adaptive control and the open-loop process without the adaptive control.     

Observer-based control algorithms for a distillation column

This paper studies the synthesis of nonlinear observer-based globally linearizing control (GLC) algorithms for a multivariable distillation column. Two closed-loop observers/estimators, namely extended Kalman filter (EKF) and adaptive state observer (ASO), have been designed within the GLC framework to estimate the state variables along with the poorly known parameters. Exactly same basic model structure was used for developing the observers. The model structure is so simple that the estimator design was performed based on only two component balance equations around the condenser-reflux drum and the reboiler-column base systems of the distillation column. To construct these observers, the poorly known parameters, namely component vapor flow rate leaving top tray, component liquid flow rate leaving bottom tray and distribution coefficient in the reboiler, were considered as extra states with no dynamics. The comparative study has been carried out between the proposed GLC in conjunction with ASO (GLC-ASO) and that coupled with EKF (GLC-EKF). The GLC-ASO control scheme showed comparatively better performance in terms of set point tracking and disturbance as well as noise rejections. The control performance of GLC-ASO and a dual-loop proportional integral derivative (PID) controller was also compared under set point step changes and modeling uncertainty. The proposed GLC-ASO structure provided better closed-loop response than the PID controller.     

COMPARISON AMONG PI,DMC, QDMC,AND GPC ALGORITHMS IN THE CONTROL OF THE SPOUTED BED DRYER

This article presents comparative analysis between the classical PI (proportional-integral control) and MPC (model predictive control) techniques for a drying process on spouted beds. The on-line experimental setups were carried out in a laboratory-scale plant of a spouted bed dryer. The main objective was to optimize the plant operation by searching for the best control structure to be used in future scale enlargement. The major drawbacks encountered in this kind of system were high interactivity among variables, a malfunction as a result of calculated variables out of the operational window, and modeling mismatch. Despite the robustness of the operational PI, the control actions of this strategy did not overcome the variable interactions. The DMC (dynamic matrix control) and the QDMC (quadratic dynamic matrix control) algorithms performed satisfactorily over the major drawbacks. Special attention was given to the latter algorithm due to its ability to hold the variables under constrained oscillations. However, the best results were found for the adaptive GPC (generalized predictive control) algorithm whose actions prevailed over the modeling mismatch due to the strong nonlinear behavior intrinsic to the process. The main goal of the present work is to describe a procedure that can be standardized for other types of dryers and different scales. This is especially the case for the adaptive GPC, whose control structure is independent of the dryer nature and scale and whose implementation does not require previous identification procedures (self-tuning) and/or structural changes.     

COMPARISON AMONG PI, DMC, QDMC, AND GPC ALGORITHMS IN THE CONTROL OF THE SPOUTED BED DRYER

This article presents comparative analysis between the classical PI (proportional-integral control) and MPC (model predictive control) techniques for a drying process on spouted beds. The on-line experimental setups were carried out in a laboratory-scale plant of a spouted bed dryer. The main objective was to optimize the plant operation by searching for the best control structure to be used in future scale enlargement. The major drawbacks encountered in this kind of system were high interactivity among variables, a malfunction as a result of calculated variables out of the operational window, and modeling mismatch. Despite the robustness of the operational PI, the control actions of this strategy did not overcome the variable interactions. The DMC (dynamic matrix control) and the QDMC (quadratic dynamic matrix control) algorithms performed satisfactorily over the major drawbacks. Special attention was given to the latter algorithm due to its ability to hold the variables under constrained oscillations. However, the best results were found for the adaptive GPC (generalized predictive control) algorithm whose actions prevailed over the modeling mismatch due to the strong nonlinear behavior intrinsic to the process. The main goal of the present work is to describe a procedure that can be standardized for other types of dryers and different scales. This is especially the case for the adaptive GPC, whose control structure is independent of the dryer nature and scale and whose implementation does not require previous identification procedures (self-tuning) and/or structural changes.     

Adaptive Linear Dynamic Matrix Control applied to an integrating process

Dynamic Matrix Control (DMC) has proven to be a powerful tool for optimal regulation of chemical processes under constrained conditions. It is based on a linear convolution model derived from step-response measurements. A model predictive control algorithm optimises closed-loop performance for a nominal operating point. However, as the process moves away from this point, control usually becomes sub-optimal due to process non-linearity. As seen in this work, the DMC algorithm can be made adaptive, to establish a new local model, by recursive estimation of the local step response parameters from normal plant variations. However, when used for control of plants containing integrating process units, steady-state offsets occur for sustained changes. Thus, a novel Adaptive Linear Dynamic Matrix Control (ALDMC) algorithm has been developed and used to control a 2-input/2-output system with an integrating behaviour. Comparisons of model control and plant control with and without these features demonstrated the importance of integral compensation for integrating processes, and model adaptation in the case of plant/model mismatch. Some cross-compensation of integration by the adaptive feature was also noted. An holistic technique is demonstrated which simultaneously recognises residual integration disturbances and matrix parameter variations, whereas previous techniques which recognise only one of these will fail in the presence of the other.     

Nonlinear state estimation and control of a batch reactive distillation

This paper deals with the advanced adaptive control of a batch reactive distillation (RD) column for the production of ethyl acetate. The nonlinear adaptive control law consists of the generic model controller (GMC) and an adaptive state estimator (ASE). In the first part of the present work, the design approach of the ASE scheme in two different forms, namely ASE1 and ASE2, has been addressed for a batch reactive rectifier. The predictor model of both the ASE estimators includes only a component mole balance equation around the condenser-reflux drum system and an extra state equation having no dynamics, and therefore, there is a large process/predictor mismatch. In presence of this structural discrepancy, the adaptive estimation schemes compute the imprecisely known parameters quite accurately based on the measured distillate composition under initialization error, disturbance and uncertainty. In the subsequent part, the adaptive GMC–ASE1 control structure has been formulated for the sample reactive column. This nonlinear control strategy shows comparatively better closed-loop performance than the gain-scheduled proportional integral (GSPI) controller due to the exponential error convergence capability of the estimation scheme and the high-quality control of the GMC law.     

Prediction of polyethylene melt rheological properties from molecular weight distribution data obtained by gel permeation chromatography

A method is presented for predicting rheological characteristics, such as shear dependent (non-Newtonian) viscosity and components of linear oscillatory (complex) response functions for polyethylene melts from molecular weight distribution data obtained from gel permeation chromatographic (GPC) analysis. The results are compared with measured values of the rheological functions obtained from a variety of instruments over an extensive range of shear rates-and frequencies. The agreement between predicted and measured rheological functions is quite good for high density resins. However, for a low density resin the agreement is not as good, although still reasonable over a considerable range of conditions. It is concluded that the quality of the GPC data is the key factor in the degree of success of the method.     

基于广义预测控制策略的微生物燃料电池控制

针对MFC系统启动阶段输出响应不稳定以及调节时间较长的问题,结合微生物燃料电池自身特性,提出了基于广义预测控制(generalized predictive control,GPC)的微生物燃料电池(microbial fuel cell,MFC)控制策略。与加入PID控制方法对比得知,加入GPC的MFC系统输出能够避免响应出现大幅度的抖动,且响应速度快,动态调节鲁棒性好,保证了动态输出曲线快速准确地跟踪系统设定值。在给定外电阻为恒值和醋酸盐浓度随时间阶梯变化时,通过带遗忘因子的最小二乘法进行模型辨识,将所得线性模型作为预测模型,采用GPC算法进行控制。仿真表明,GPC能在控制响应速度方面取得好的控制效果以及系统调节过程中的鲁棒性也有了较大的改善。有效地实现了对微生物燃料电池系统的动态性能以及鲁棒性能的优化,验证了所提出的算法有效可行。     

A self-tuning control method for Wiener nonlinear systems and its application to process control problems

Many chemical processes can be modeled as Wiener models, which consist of a linear dynamic subsystem follow-ed by a static nonlinear block. In this paper, an effective discrete-time adaptive control method is proposed for Wiener nonlinear systems with uncertainties. The parameterization model is derived based on the inverse of the nonlinear function block. The adaptive control method is motivated by self-tuning control and is derived from a modified Clarke criterion function, which considers both tracking properties and control efforts. The un-certain parameters are updated by a recursive least squares algorithm and the control law exhibits an explicit form. The closed-loop system stability properties are discussed. To demonstrate the effectiveness of the obtained results, two groups of simulation examples including an application to composition control in a continuously stirred tank reactor (CSTR) system are studied.     

A theoretical examination of closed-loop properties and tuning methods of single-loop PI controllers

The dependence of the dominant closed-loop poles on the controller parameters is quantitatively elucidated by a Taylor expansion about the critical (ultimate) gain. The leading expansion coefficients are estimated from the critical (ultimate) gain and frequency and one or two closed-loop measurements of the decay ratio and frequency of system response to set-point/load changes or natural disturbances. An explicit model for the process transfer function is not required. By relating controller performance criteria to the leading poles, optimal gain settings to achieve these criteria can then be determined. In the present work, three tuning methods of increasing accuracy (the modified Ziegler-Nichols rule and Methods A and B) are constructed to satisfy a performance criterion (D.R. = 0.25) and a stability consideration. Method A is presented in a convenient chart and is especially easy to use on line. Stability robustness as measured by the Doyle-Stein index and the estimated closed-loop frequency at the proposed setting are also presented in the same chart.     

Characterization of bisphenol A–based epoxy resins by HPLC,GPC, GPC–MALLS,VPO, viscometry,and end group analysis: On the identification of 2,3‐dihydroxypropyl‐containing compounds,determination of molar mass distribution,and branching

Reversed‐phase high performance liquid chromatography (HPLC), conventional gel permeation chromatography (GPC), and gel permeation chromatography coupled with a multiangle laser light scattering photometer (GPC–MALLS) were used for the analysis of epoxy resins based on bisphenol A. Compounds containing 2,3‐dihydroxypropyl group were identified in HPLC chromatograms by means of the derivatization of sample by acetone. The presence of branched molecules was proved by GPC–MALLS using a molar mass versus root mean square (RMS) radius plot or molar mass versus elution volume plot. The molar mass distribution determined by HPLC was compared with that obtained by GPC–MALLS. Molar mass averages measured by means of GPC, GPC–MALLS, vapor pressure osmometry (VPO), and end group analysis (EG) were compared and the differences of results obtained by particular methods were discussed. An appropriate GPC calibration was found on the basis of literature data and the comparison of molar mass averages measured by GPC, VPO, and GPC–MALLS. The refractive index increment of epoxy resins was determined. © 1999 John Wiley & Sons, Inc. J Appl Polym Sci 74: 2432–2438, 1999