http://www.ifac-papersonline.net/ en Copyright 11:24 PM Wednesday 10, 2010 IFAC-PapersOnline http://www.ifacpapersonline.com 11:24 PM Wednesday 10, 2010 11:24 PM Wednesday 10, 2010 ET webmaster@ifac-papersonline.net webmaster@ifac-papersonline.net http://www.ifac-papersonline.net/Detailed/32000.html 04:00 PM Wednesday 31, 1969 A new method for the spatial discretization of complex multiscale systems described by partial differential equations is presented. This method allows to preserve the global power balance equation and the geometric structure of the system. The modelling of the adsorption column is based on a network approach. The key notions are the energy function and the description of the power transfers within the system and through its boundaries with the help of a power-conserving geometric structure. The proposed discretization method preserves this geometric structure and is thermodynamically consistent. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/32068.html 04:00 PM Wednesday 31, 1969 Plant-wide oscillations are common in many processes. Their effects propagate to many units and may impact the overall process performance. It is important to detect and diagnose the oscillations early in order to rectify the situation. This paper proposes a new procedure to detect and diagnose plant-wide oscillations. A technique called spectral envelope is used to detect the oscillations. Two kinds of plots - scaling and power plots - are proposed to identify the variables exhibiting common oscillation(s). These plots are also useful in isolating the key variables as the candidates of the root cause. An industrial case study is presented to demonstrate the applicability of the proposed procedure. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/32069.html 04:00 PM Wednesday 31, 1969 This article demonstrates the use of agglomerative hierarchical clustering to detect the structure within a data set. When combined with spectral principal component analysis to capture the main spectral features of a data set it allows visualization of the structure of a model with an optimum number of principal components. The paper presents the theory and methods for construction of the tree and gives an example using industrial data. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/32067.html 04:00 PM Wednesday 31, 1969 In this paper, a modified independent component analysis (ICA) and its application to process monitoring are proposed. The basic idea of this approach is to use the modified ICA to extract some dominant independent components from normal operating process data and to combine them with statistical process monitoring techniques. The proposed monitoring method is applied to fault detection and identification in the Tennessee Eastman process and is compared with the conventional PCA based monitoring method. The monitoring results demonstrate that the proposed method outperforms PCA in terms of the fault detection rate while attaining comparable false alarm rate. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/32071.html 04:00 PM Wednesday 31, 1969 Oscillations in control loops lead to poor controller performance. Stiction in control valves is one of the major causes of such oscillations. Therefore, the correct diagnosis of stiction is important. There are several methods for detecting stiction, but quantification of stiction still remains a challenge. Two parameters are used to model the stiction phenomenon successfully, namely, deadband plus stickband, ′S′, and slipjump, ′J′. It has been observed that the main cause of valve deterioration is the presence of slip-jump, ′J′. The higher the value of ′J′, the more severe is the level of deterioration of controller performance. Thus, in addition to the estimation of ′S′, an estimate of ′J′ is the main challenge in monitoring the condition of a control valve. In this work a method is proposed to estimate both ′S′ and ′J′ simultaneously unlike existing quantification methods where stiction is quantified as a single parameter. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/32070.html 04:00 PM Wednesday 31, 1969 Oscillation in a single control loop can propagate to many units and can cause several control loops to oscillate. In this work, an approach that uses detailed oscillation characterization in combination with signed digraphs is proposed for isolating the source loop that causes plant-wide oscillation. The success of this approach is built on a new oscillation characterization technique that identifies the zero-crossings of each oscillating measurement. A signed digraph that embeds the temporal information obtained from the zero-crossings of the data is analyzed to isolate the root cause for oscillation. A simulation case study illustrates the applicability of the proposed approach. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/31998.html 04:00 PM Wednesday 31, 1969 A significant research work hasbeen carried out on modeling, identification and control of processes represented by Wiener models. These models include a cascade connection of a linear time invariant system and a static nonlinearity. Several approaches can be found in the literature to perform the identification process. In this article, we describe a param etric description for the system, that allows to describe the uncertainty as a set of parameters. The proposed algorithm is illustrated through a pH neutralization process. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/31999.html 04:00 PM Wednesday 31, 1969 This paper presents empirical modelling approach in predicting elemental composition of coal. The model is developed to estimate carbon, hydrogen and oxygen content of coal. In the present work, several methods are applied to formulate the model including multiple regression (MR), principal component regression (PCR), partial least squares (PLS) and back propagation neural networks (BP-ANN). The use of BP-ANN shows the best result among the tested methods and appears to be a promising tool for predicting elemental composition of coal because it gave the least root mean square of error (RMSE) and the highest correlation coefficient (R2). http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/32025.html 04:00 PM Wednesday 31, 1969 This work introduces a novel methodology to quantify the profit gain due to reduction in the product variability. The base of the proposed approach is the variability matrix (VM), which relates how the loop variance of main loops is changed when the variance of the other loops are changed. Based on the potential reduction on the main loop variance, it is possible to quantify the economic impact produced by improving the tuning of given control loop. Based on the VM, it is possible to select the control loops responsible for the major impact in the variability of the products and which should be the vocation of the loop: good performance of robustness. The VM concept is applied to a simple distillation process. This example shows how the plant profitability can be improved by utility reduction and by selling products more impure. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/31975.html 04:00 PM Wednesday 31, 1969 This paper describes the application of Parametric Model Predictive Control to small processing units, in particular small Air Separation plants. Multiparametric optimization techniques are used to rigorously solve the MPC problem in two steps: an offline solution which generates a parametric mapping of the optimal control adjustments, and an online solution which reduces to a simple lookup operation. Because of the speed and simplicity of this lookup operation we are able to implement MPC in low-end computing devices such as PLCs, reaping the benefits of model-based control by implementing it at low cost in small plants where otherwise it would not be justified by the cost/benefit ratio. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/31958.html 04:00 PM Wednesday 31, 1969 This paper exploits a gradient-based model predictive control technique to solve an optimal switching time problem over periodic orbits. Drug delivery scheduling applications, where it is desired to maximize the averaged effect of a drug over time, motivate the study for this type of online optimization problem. The objective is to find the optimal time-switching policy between full treatment and no treatment periods. It is shown, by a numerical application to a simple drug delivery problem, that the resulting predictive algorithm drives the system to the optimal periodic orbit in the state space. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/31967.html 04:00 PM Wednesday 31, 1969 The problem of estimating effluent compositions from temperature measurements in ternary distillation columns is addressed within a geometric estimation framework where the estimation structure and the algorithm are jointly designed. The employment of passive estimation structures and error propagation measures yields criteria to choose the sensor number and locations as well as the set of innovated states. The proposed approach is tested with experimental data from a 32-stage pilot column (tert-butanol-ethanol-water system). With 64 on-line dynamical equations and a straightforward tuning scheme, the proposed estimator yields the same behaviour than the one of an Extended Kalman Filter with 2144 equations and an optimization-based tuning procedure. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/31972.html 04:00 PM Wednesday 31, 1969 The quality control of the wafer is becoming more and more important as the wafer becomes larger and the feature size shrinks. An advanced IC fabrication process consists of 300+ steps with scarce and usually difficult quality measurements. Thus product yield may not be realized until months into production while in-line measurements are available on the order of a millisecond. The series production nature and measurement setup lead to a unique process control problem. In this work, typical disturbances are explained and possibility for inferential control is explored. This leads to a control architecture with multiple layers in a cascade structure. Next, rapid thermal processing (RTP) is used to illustrate recipe generation and control structure design at the tool level. The resultant multivariable controller gives satisfactory setpoint tracking for a triangular-like temperature program. In order to reduce downtime, process trend monitoring of a tool is essential. Instead of using entire batch data, a key process variable is identified and an index is computed to capture the dynamic behavior of the tool. An RTP example is used to illustrate this approach and results clearly indicate that process trend is well predicted using the index-based time-series model. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/32003.html 04:00 PM Wednesday 31, 1969 Supervisory control schemes of (complex) plants utilize diferent forms of automata or related structures such as Petri-nets. Empirical, knowledge-based mapping of the plant's operation into such a structure cannot be complete or correct. These automata can be computed by a model-based approach, which guarantees completeness and correctness within the limits of the given model. The result is a non-deterministic automaton (Philips 2001), which how ever contains no information about the range of transition time that may be expected. This inform ation would be extremely useful for the design of the derived operational procedures such as supervisory controllers on all levels and fault detection and fault isolation schemes. The problem has been formulated several times in the past, for example (Kowalewsky 1999, Engell 1997). Here a solution to the problem is described, which applies to plants generating a monotone flow field for constant inputs. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/31970.html 04:00 PM Wednesday 31, 1969 This paper presents an approach to estimate the outputs and the uncertainty associated to the forecast for discrete dynamic systems represented by state-space models. The complete strategy includes three steps: 1. process identification based on a data sample; 2. estimation of the current process state based on the information available during a moving past horizon, which may contain lack of observations; 3. forecast of process states, process outputs and uncertainty along the future horizon. This procedure can be incorporated in control strategies that explicitly consider model uncertainty. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/32044.html 04:00 PM Wednesday 31, 1969 Membrane filtration processes are often operated cyclically, where one cycle comprises a filtration and a backwashing phase. Due to the complex mechanisms involved, these filtration processes are mostly operated with xed values of the manipulated variables. In this paper, a model-based process control approach is introduced, which is based upon run-to-run control theory. To evaluate the controller, a suitable model of submerged membrane filtration in wastewater applications is developed, which describes the main process phenomena while being computationally inexpensive. The model-based controller is then tested in a simulation environment employing a validated reference model. Excellent results with respect to prediction quality and optimality are obtained. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/31989.html 04:00 PM Wednesday 31, 1969 Steady-state detection has been an important tool in data processing, for nonlinear model identification, real time optimization, variability analysis, and so on. In this article, it is proposed a new methodology applied to multivariate systems for steadystate detection based on PCA and wavelets. The proposed approach is applied to an industrial distillation column. The combination of PCA and wavelets allows quantifying the steady-state considering a single variable generated by a PCA projection. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/32049.html 04:00 PM Wednesday 31, 1969 The developments in technologies are expanding the boundaries and broadening the domain of what is technically and economically feasible to achieve in the application of data reconciliation activities in manufacturing plants. They also, naturally, incorporate additional issues and open the opportunities for new research activities. For example, recent developments on model-centric technologies to support plant operations based on advanced process modelling technologies opened the opportunities for performing large-scale parameter estimation - data reconciliation applications in complex dynamic industrial environments. On the other hand, new sensor technologies are becoming available based on recent advances in microprocessor-based instrumentation and digital communications. They provide opportunities for the realization of novel sensor network architectures towards a truly distributed environment for data processing and reconciliation. In this presentation we will discuss current research activities combining efforts in these areas towards the future operation of manufacturing plants. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/32024.html 04:00 PM Wednesday 31, 1969 This article aims to construct an "inference model" (IM) that assesses the closed loop performance and robustness for SISO controllers, with no need of intrusive tests (i.e. set-point changes or open-loop step tests). The IM is generated for a large set of plants, disturbances, and tuning parameters. The possible inputs for the IM are 9 standard assessment measurements (e.g., FCOR, standard deviation, etc) on-line available, commonly present in commercial tools. Three IMs were developed for the following targets: the closed loop and open loop rise time ratio (RtR), Gain Margin (GM), and normalized integral of square error (ISE). These values are obtained by intrusive tests. Four different classes of inferential models (i.e., Neural Networks, Neuro Fuzzy, PLS, and QPLS) are compared. The best results are obtained by Neural Network IM. The results obtained show that the methodology is very promising. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/31955.html 04:00 PM Wednesday 31, 1969 A mathematical model of the changes in plasma glucose and insulin concentrations during mild-to-moderate physiological exercise was developed for insulin dependent diabetic patients. From a metabolic prospective, the significant exercise induced effects are: increased glucose uptake rate by the working tissues; increased hepatic glucose production to maintain overall glucose homeostasis; and decreased plasma insulin concentration. The minimal mathematical model developed by Bergman et al. (1981) was extended to include the major exercise effects on plasma glucose and insulin levels. Model predictions of glucose and insulin dynamics were consistent with the existing literature data. This extended model provides a new disturbance test platform for the development of closed-loop glucose control algorithms. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/32004.html 04:00 PM Wednesday 31, 1969 This paper describes the development of a hybrid model based on artificial neural network and its industrial application to the ironmaking at Companhia Siderúrgica Nacional (CSN -Volta Redonda/Brazil). The Iron Blast Furnace is highly complex process subject to oscillations in raw material characteristics. A precise model is essential to adjust © 2002 charging and blow conditions to match productivity, chemical quality and costs targets. A neural model was developed in order to estimate chemical and thermal parameters to feed a first principles model capable of evaluating alternative operation standards. As a consequence, operation efficiency is enhanced leading to higher productivity and lower costs. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/32048.html 04:00 PM Wednesday 31, 1969 The method presented here offers an effective and time saving tool for robust low order multivariable controller design. The relation between controller complexity and closed loop performance can easily be evaluated. The method consists of five steps: 1. A desired behavior of the closed loop system is specified. Considering the nonminimum phase part of the process model the closed loop attainable performance is determined. 2. The process model and the attainable performance are scaled by the RPN-scaling procedure. 3. This defines an "ideal" scaled controller, which is usually too complex to be realized. 4. The frequency response of the ideal scaled compensator is approximated by a simpler one with structure and order chosen by the user. 5. Since the approximation in frequency response is performed with the scaled system, it is necessary to return to the original system's units. This procedure can be implemented using a multimodel approach, what increase the robustness of synthesized controller. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/32043.html 04:00 PM Wednesday 31, 1969 This work presents the results from dynamic modeling and control of an azeotropic distillation system. The model was validated with experimental data from a packed distillation unit. The physically-based process dynamic model, developed in HYSYS, was linked online with the control software used in the process. Model parameters were modified online using a feedback configuration to eliminate the difference between the process and model outputs. The fundamental model was used in the implementation of different control strategies, including a multivariable control strategy using model predictive control (MPC) software Predict Pro, via an inferential control strategy to treat missing process measurements. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/32042.html 04:00 PM Wednesday 31, 1969 Non-square process control systems, with fewer inputs than the controlled outputs, are quite common in chemical processes. In these systems, it is impossible to control all measured variables at specific set points and many of the outputs are controlled within an interval. The objective of this paper is to introduce a multivariable Operability methodology for such non-square systems to be used in the design of nonsquare constrained controllers. In order to motivate the new concepts, we examine some simple non-square systems obtained from the control system of a Steam Methane Reformer process. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/32064.html 04:00 PM Wednesday 31, 1969 In this work, linear, quadratic, and nonlinear empirical models were built and compared with a dynamic nonlinear phenomenological model with respect to the capability of predicting the melt index and polymer yield rate of a low density polyethylene production process. Based on steady-state gains and on known first and second order time constants of the process, the empirical models were generated using PLS, QPLS, and BTPLS methods in order to predict the system dynamics. As the quadratic model provided more reliable predictions, it was used as melt index virtual analyzer of an advanced control strategy for an industrial plant, improving the controller action and the polymer quality by reducing significantly the process variability. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif