http://www.ifac-papersonline.net/ en Copyright 08:01 PM Wednesday 22, 2012 IFAC-PapersOnline http://www.ifacpapersonline.com 08:01 PM Wednesday 22, 2012 08:01 PM Wednesday 22, 2012 ET webmaster@ifac-papersonline.net webmaster@ifac-papersonline.net http://www.ifac-papersonline.net/Detailed/46981.html 04:00 PM Wednesday 31, 1969 An ensemble modelling strategy, which is based on the genetic algorithm neural network (GA-NN) optimisation, is developed in this paper. A diversity index, defined by the dissimilarity between the current neural network (NN) and the set of existing NNs, is first introduced to facilitate the qualification of the current NN for being included in the ensemble network. A fitness-weighted assemble scheme is then proposed to form the GA-NN ensemble model. The unique advantage of this ensemble modelling scheme is its high efficiency, thanks to the full exploitation of information generated during the GA-NN optimisation. Preliminary results obtained for the prediction of the Charpy impact energy of heat-treated steel are promising, with the model performance being significantly improved as compared to previous modelling results. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/47009.html 04:00 PM Wednesday 31, 1969 Anglo Platinum’s control schema for crusher circuits follows a layered approach that includes basic control (regulatory, interlock and sequence control), fuzzy logic, rule-based and model predictive control. This allows for a robust approach to circuit optimization. This paper outlines a typical control schema for a crushing plant, and discusses the benefits that have been achieved over a wide range of fluctuating feed conditions and different equipment availabilities at two industrial installations. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/47007.html 04:00 PM Wednesday 31, 1969 Anglo Platinum’s control schema for a Run-of-Mine (ROM) ball milling comminution circuit follows a layered approach that involves basic control (regulatory, interlock and sequence control), fuzzy logic rule-based and model predictive control. This allows for a robust approach to optimization. This paper reviews the above control schema for a ROM ball milling circuit and discusses the benefits that have been achieved from implementing optimization using Mode Predictive Control (MPC) to cater for a wide range of feed conditions. C.W Steyn*, K.S Brooks**, P.G.R de Villiers***, D Muller†, G Humphries†† http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/47005.html 04:00 PM Wednesday 31, 1969 Anglo Platinum’s flotation circuit control solution includes a layered approach that involves base-layer, fuzzy logic rule-based and model predictive control that enables a robust approach to optimization. This paper reviews Anglo Platinum’s approach to the flotation mass pull and grade control problem and describes the benefits that have been derived from a wide range of feed conditions and equipment from four industrial installations. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/47003.html 04:00 PM Wednesday 31, 1969 An advanced process control (APC) system using G2 and AspenTech’s DMCplus controller was implemented on Anglo Platinum’s Precious metals refinery. The APC was implemented on a batch reactor where an exothermic reaction occurred. The APC controller was able to counter the effects of an integrating process model and long time delay to improve overall stability of the reactor. The APC controller resulted in improved temperature stability, reduction in total batch time and reduction in a regent consumption. A Singh*, P.G.R de Villiers**, P ***, G Gous† J de Klerk††, G Humphries††† http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/47001.html 04:00 PM Wednesday 31, 1969 Organizations in the mining industry with multiple operations in different geographical locations face the decision whether to manage automation and control standards independently at each operation, or whether this should be centralized to some extent. The selected approach will have an influence on several aspects of operating a mining or processing plant; this includes the execution of automation and control projects, and the provision of technical support to operations. The best approach for one organisation may well not suit another. This article presents the considerations, approach and experience of Anglo Platinum in selecting an appropriate degree of centralization of automation and control standards. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/46999.html 04:00 PM Wednesday 31, 1969 Anglo Platinum’s process control department has succeeded in establishing a robust, sustainable advanced control architecture that facilitates the rapid expansion of its automation and optimization strategy across its concentrator, smelter and refinery operations. This paper discusses the various components of this architecture that led to and contributes to the widely recognized impact that it has on driving Anglo Platinum’s mission to be the world’s number one producer of safe, profitable Platinum. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/46983.html 04:00 PM Wednesday 31, 1969 The problem of fault identification is considered using recent developments in machine learning that allow the use of unlabeled data to optimal define the decision boundary. Traditionally, fault identification uses either hardware redundancy or software redundancy for trouble-shooting the source of faults in a system. Unfortunately, this imposes a data redundancy cost on such systems. Instead of performing model inversion that requires an accurate model, in transduction estimates of the values of a function at specified points are required, instead of learning a general rule on the entire input domain. Transductive learning is motivated from similar arguments underlying state-of-the-art classification and regression methods such as support vector machines. However, transduction is more fundamental as it is a step used in proving learning error bounds in classical statistical learning theory. Use of transduction allows a flexible ordering of the classes of functions from which a model is selected and, therefore, the error bounds are provably tight. The potential of the proposed framework is assessed using data from metallurgical process systems. It is shown that for higher dimensional and large multiclass systems, the proposed framework gives better performances with respect to classification error minimization. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/46969.html 04:00 PM Wednesday 31, 1969 This paper proposes an advanced method to reduce fluctuations of strip tension and looper position in a steel rolling mill. We design a non-interactive controller to decouple the looper system into two subsystems. We consider uncertainties, disturbances and interactions as each nominal subsystem's disturbance. To reduce these disturbances, we use a nonlinear disturbance observer. We prove that the proposed method can reduces response time and fluctuations in strip tension in comparison with other methods. Simulation results and hardware experiment results are included. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/46979.html 04:00 PM Wednesday 31, 1969 The application of statistical methods is state-of-the-art in all steel companies worldwide to investigate data coming from technical processes. In many cases the aim of such an investigation is to find cause&effect relationships between process / plant variables and detected quality deficiencies. For these kinds of investigations special departments are responsible. They use complex statistical tools and in-house written procedures. The main disadvantage here is that the experience of the people at the production lines can not directly be used. On the other hand the mostly used uni-variate and linear statistical techniques are in many cases not sufficient to explain the behavior of the complex chain of steel production. Out of both reasons the development of automatic data mining technologies which can be handled by plant engineers without knowledge about statistics are under development at many places worldwide. This article presents some approaches of automatic and robust Data Mining which can be used by process and plant engineers. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/46997.html 04:00 PM Wednesday 31, 1969 A multiple coal fired boiler house provides steam for utility usage in various production plants. Maintaining stable header pressure and boiler availability is of critical importance for downstream consumers. Advanced Process Control comprising of a G2 based expert system and Model Predictive Control was implemented to improve the boiler house performance. The results yielded improvements in the main header pressure stability, reduction in boiler saturation and significant saving in coal consumption. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/46973.html 04:00 PM Wednesday 31, 1969 Often the most difficult step in establishing a control system is the development of a suitable dynamic process model. As such a model is not available elsewhere, a first principle dynamic mathematical model was developed for a coal dense medium separation circuit. Each unit operation was modelled individually and then integrated together to form a complete non-linear state space model for the circuit. This model was used to simulate the process and it was validated using real process data derived from a plant experiment. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/46987.html 04:00 PM Wednesday 31, 1969 The ever-present drive to safer, more cost-effective and cleaner processes motivates the exploration of a variety of process monitoring methods. In the domain of data-driven approaches, random forest models present a nonlinear framework. Random forest models consist of ensembles of classification and regression trees in which the model response is determined by voting committees of independent binary decision trees. Data-driven approaches to fault diagnosis often involve summarizing potentially large numbers of process variables in lower dimensional diagnostic sequences. Random forest feature extraction allows for the monitoring of process in feature and residual spaces, while random forest variable importance measures can potentially be used to identify process variables contribution to fault conditions. In this study, a framework for diagnosing steady state faults with random forests is proposed and demonstrated with a simple nonlinear system and the benchmark Tennessee Eastman process. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/46957.html 04:00 PM Wednesday 31, 1969 http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/46963.html 04:00 PM Wednesday 31, 1969 This paper deals with model based fault detection and isolation of a pickling process within the steel industry. The model is based on the grey box methodology and reflects the physical behaviour of the process. Possible faults are included in the model as parameters, which are estimated on line. The estimation is based on minimizing a loss function using past data from a defined moving time window. The procedure of finding the faults starts by estimate all defined fault parameters. One fault parameter is removed from the set of prospective list of faults by removing the parameter with the smallest saliency. The saliency is defined as the quote between the parameter estimate and the corresponding element of the inverse of the hessian matrix. The parameter with the smallest saliency gives a measure of the relevance of the estimated parameters relative all estimated parameters. The procedure is repeated until all fault parameters are eliminated from the list. To isolate the faults, the Akaike’s Information Criterion (AIC) is used to detect faults. This gives the threshold when a fault relevant parameter is removed from the list of prospective faults. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/46965.html 04:00 PM Wednesday 31, 1969 This paper is concerned with an advanced control system for tilting-ladle type automatic pouring robot used in metal-casting industry. The monitoring and control system to falling position of outflow liquid from the ladle are proposed in this paper. In the monitoring system, the images of outflow liquid are pictured by camera image sensor. The falling position of outflow liquid can be obtained by the edge processing to the outflow liquid in the images. Then, in order to develop the falling position control system, the mathematical model to the falling position is derived from the shape of the ladle and the pouring conditions. The proposed mathematical model is verified using the monitoring system for the falling position of outflow liquid. The falling position control is constructed by feedforward control using the proposed falling position mathematical model. The effectiveness of the proposed control system is verified through the experiments using the automatic pouring robot and the falling position monitoring system. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/46961.html 04:00 PM Wednesday 31, 1969 A metallurgical process generally processes some raw materials or ores into concentrates or primary metals using different technologies. However, the quality of the incoming raw materials has an effect on the process performance. Hence, engineers have to apply different set points in order to account or compensate for raw material quality variations. This is frequently performed using a set of univariate specifications. In this paper, a methodology to build multivariate specifications is presented and illustrated using a case study from an aluminum reduction smelter. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/46967.html 04:00 PM Wednesday 31, 1969 Gas dispersion properties have proven to be key variables of the flotation process. Among them, bubble surface area flux (BSAF) has been reported to linearly correlate with the flotation rate constant; therefore, it is a potential variable to achieve a desired metallurgical performance. BSAF can be represented as a combination of two other gas dispersion properties: superficial gas velocity and Sauter mean bubble diameter. Thus, controlling BSAF implies controlling bubble size and superficial gas velocity. This work focuses on the nonlinear control of the Sauter mean bubble diameter. Sauter bubble mean diameter was indirectly calculated from the bubble size distribution, estimated by using a Gaussian mixture model. To improve controllability, a so-called frit-and-sleeve sparger was installed to regulate bubble size independently from superficial gas velocity. With this device, the bubble size can be modified by manipulating the water flow rate circulating through the sleeve that surrounds the porous ring. A Wiener model is used to represent the dynamic relationship between the sleeve water flow rate and Sauter mean diameter. Wiener models consist of a linear system in series with a memory-less (static) nonlinear element. An IMC controller based on the identified Wiener model was implemented in a laboratory flotation column. Tracking performance and rejection of gas velocity and unmeasured frother concentration variations were then successfully evaluated. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/46985.html 04:00 PM Wednesday 31, 1969 Conductivity based sensors can be applied to monitor a wide range of processes in the mineral processing industry. This work compares the use of an Extended Kalman Filter and a Nonlinear Observer for tracking conductivity variations under dynamical conditions. Several simulations illustrate the main features and differences among these two methods. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/46989.html 04:00 PM Wednesday 31, 1969 Hydrocyclones are widely applied in both chemical and mineral processing industries. Despite its simple design, the flow behaviour that governs separation within the device is quite complex and therefore difficult to control. Overall process efficiency, together with economics, promotes the development of an effective monitoring technique. In the past, numerous techniques have been tried, with varied success, but none have found broad adoption yet. The reasons for this are that the techniques lack robustness, while others are intrusive to the process or completely uneconomical. Previous work has indicated that there exists a relationship between the underflow and the operating state of a hydrocyclone, which could be exploited for monitoring purposes. In view of this, the use of image analysis of the underflow is evaluated as an on-line monitoring technique. Underflow widths are determined from video recordings of two different data sets: gold ore and PGM (Platinum Group Metals) ore. Time series analysis of the data indicates identifiable clusters which relate to normal operating conditions as well as troublesome states like roping and blocking. Groups of scattered clusters further correspond to the oscillatory behaviour experienced during the transition from normal to roping (or blocking). The predictive potential of the gold ore data set was also investigated, and suggests that the technique can be used to forecast the onset of such troublesome states http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/46971.html 04:00 PM Wednesday 31, 1969 Model-based predictors and controllers frequently depend on efficient recursive estimation of model parameters. Similarly often, there are known hard bounds on parameter values. Adaptive control applied for rolling mills represents a typical example of such case. While common estimation algorithms are elaborated enough to be utilized in industrial practice, it is difficult to find implementation of bounded estimation, which is both formally consistent and suitable for reliable applications. Solution offered in this paper is based on simultaneous run of two or more proven estimators different in applied process models. Both simulated and real data examples are provided. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/46975.html 04:00 PM Wednesday 31, 1969 Saving energy and minimize environmental influence are ever so important issues for world industries today. To produce steel is one of the most energy intense activities, next to producing aluminum. The energy is consumed in many process steps, where heating and heat treatment uses the most of the fossil fuels in the industry. Saving energy in those processes is most important in terms of economical, environmental and the far from endless global resources. The Furnace Optimizing Control System (FOCS) decreases the fuel consumption and increases productivity and product quality in a number of different furnace applications, such as pit furnaces, batch normalizing furnaces, reheating furnaces and continuous annealing furnaces. The systems are based on online calculations of slab temperatures, that together with different levels of control complexity control the furnace temperature. This facilitates safer production, good product quality and higher productivity in a number of steel works in Scandinavia. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/46993.html 04:00 PM Wednesday 31, 1969 Mining, mineral and metal (MMM) processes present by its nature (multiphase, with solid particle properties distribution, high temperature) difficult scenarios to obtain high quality measurements of key variables. Furthermore, the characteristics of the feed are almost always changing over time, upsetting the process and giving a hard time to the stabilizing controllers. Then steady state operation condition is seldom met. Even more, some key measurements as metal grades and particle size are usually sparsely obtained with complex procedures involving sampling handling and correlations methods. All this characteristics put a lot of pressure on maintenance procedures of installed instrumentation. In summary, there are plenty of opportunities that sets of observations collected from a data base may contain all kind of pitfalls. Multivariate statistics can provide us with very powerful tools to analyze large set of data, and to efficiently extract the relevant information. However, the set of data must contain this information with the less degree of confusion as possible, for example as the result of a designed experiment. In this work, the application of these methods to smelters and flotation plants data are discussed. Special emphasis is put on how the previous work to assure the quality of the data, used in building such models, plays an important role on the success or failure of a powerful methodology. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/46991.html 04:00 PM Wednesday 31, 1969 This paper describes the design of an inclination- and azimuth-hold controller for directional drilling tools typically used in the oil industry. A control input transformation that partially linearizes and decouples the plant dynamics is proposed. A pole-placement method is used to design the controller and an analysis of the stability robustness is performed using the small gain theorem. Results for a transient simulation of the proposed controller are also presented. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/46977.html 04:00 PM Wednesday 31, 1969 Variables in a process are interacting, thus they can be described as an SDG in which arcs show causal relations between variables. Based on the SDG, the fault propagation can be tracked along consistent paths. Hence the SDG modeling can form the basis of fault propagation analysis. Regarding the modeling issue, this paper suggests a knowledge-based method to capture connectivity information between and within units from piping and instrumentation diagrams and other process knowledge. On the other hand, process data can be employed to construct SDGs by correlation analysis. An SDG generation procedure is proposed in this paper. The individual disadvantages of these two methods are summarized. However it is shown that they complement each other when combined. The SDG modeling and fault propagation analysis are applied to a tailings pumping process to illustrate and validate the methods proposed in this paper. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif