Authors: Erik Dahlquist

Abstract: The purpose of this paper is to present modelling and design of a new type of black liquor gasification process with significant benefits compared to existing Tomlinson boilers and wet gasification processes. The organics are gasified by mainly steam reforming, as the temperature is relatively low (below 850°C) and the water content of the black liquor relatively high (> 20 % water). The gasification can be with or without direct caustization. Sulphates are reduced to first Na2S, and then most of the sulphur is evaporated as H2S (Hydrogen sulphide), after reaction with CO2 + H2O. The hydrogen sulphide is absorbed in a and used for preimpregnation of the wood chips, to give modified cooking with stronger and brighter fibres out from the digester. With TiO2 added, sodium carbonate is converted into Na2O.TiO2, which dissolved in water gives 4 NaOH + Na2O.(TiO2)3. The direct caustization makes the lime kiln unnecessary. The gas may be combusted in a gas turbine/steam turbine cycle, to produce 2-3 times more electricity than conventional recovery boilers, that is an electrical efficiency of 30-35.

Keywords: black liquor,gasification,system,direct caustization,modelling

Digital Object Identifier (DOI): 10.3182/20060830-2-SF-4903.00012

Conference: 1st IFAC Workshop on Applications of Large Scale Industrial Systems, 2006

Location: Cruise liner M/S Silja Line, Finland

Start Date: Wed Aug 30 2006 - End Date: Thu Aug 31 2006

Page Numbers: 64-69

Authors: A. Borowa; M. A. Brdys; K. Mazur

Abstract: Most of industrial processes are nonlinear, not stationary, and dynamical with at least few different time scales in their internal dynamics and hardly measured states. A biological wastewater treatment plant falls into this category. The paper considers modelling such processes for monitorning and control purposes by using State - Space Wavelet Neural Networks (SSWN). The modelling method is illustrated based on bioreactors of the wastewater treatment plant. The learning algorithms and basis function (multidimensional wavelets) are also proposed. The simulation results based on real data record are presented.

Keywords: neural network models,model approximation,learning algorithms,waste treatment

Digital Object Identifier (DOI): 10.3182/20060830-2-SF-4903.00044

Conference: 1st IFAC Workshop on Applications of Large Scale Industrial Systems, 2006

Location: Cruise liner M/S Silja Line, Finland

Start Date: Wed Aug 30 2006 - End Date: Thu Aug 31 2006

Page Numbers: 250-255

Authors: J. Alatalo; E. Saarelainen; S. Sihvo

Abstract: The paper covers main design principles and description of optimization algorithms for cutting steel at continuous casting plant. The aim is to produce maximum amount of customer bars from liquid steel. The static cutting plan from production planning is dynamically updated taking into account unexpected deviations in steel quality. The optimizing problem type is mixed integer non-linear programming (MINLP).

Keywords: steel industry,continuous casting,production systems,dynamic models,control algorithms,optimization problems,mathematical models

Digital Object Identifier (DOI): 10.3182/20060830-2-SF-4903.00020

Conference: 1st IFAC Workshop on Applications of Large Scale Industrial Systems, 2006

Location: Cruise liner M/S Silja Line, Finland

Start Date: Wed Aug 30 2006 - End Date: Thu Aug 31 2006

Page Numbers: 112-117

Authors: Farida Kessal; Kamel Hariche

Abstract: This work is concerned with the choice of the form of the closed-loop block poles in multivariable control design. The criteria used for the selection are robustness, time response and magnitude of feedback gain.

Keywords: multivariable systems,solvents,matrix polynomial,robust stability,robust performance,state feedback gain

Digital Object Identifier (DOI): 10.3182/20060830-2-SF-4903.00011

Conference: 1st IFAC Workshop on Applications of Large Scale Industrial Systems, 2006

Location: Cruise liner M/S Silja Line, Finland

Start Date: Wed Aug 30 2006 - End Date: Thu Aug 31 2006

Page Numbers: 59-63

Authors: W. Kurek; Mietek A. Brdys

Abstract: Providing water meeting strict quality conditions is now a number one priority for the water authorities. Water chlorination only at water treatment plants forced the usage of high concentration of disinfectant which resulted in bad taste of water near them and still did not solve the quality issues at the far points of the network. The answer to this problems is booster chlorination - placing booster station throughout the network allowing a significant reduction of chlorine concentration and at the same time ensuring proper water quality in the network. The booster chlorination is highly dependent from the demand scenarios.

Keywords: multiobjective optimizations,genetic algorithms,decision making,optimization problems,quality control,environmental engineering

Digital Object Identifier (DOI): 10.3182/20060830-2-SF-4903.00041

Conference: 1st IFAC Workshop on Applications of Large Scale Industrial Systems, 2006

Location: Cruise liner M/S Silja Line, Finland

Start Date: Wed Aug 30 2006 - End Date: Thu Aug 31 2006

Page Numbers: 232-237

Authors: Branislav Rehák

Abstract: The problem of design of a controller for a large-scale system is studied. The design objective is to achieve behavior comparable with the standard controller that is LQ optimal. On the other hand the amount of interconnections between subsystems should be kept as small as possible. This is guaranteed by solving of an optimization problem where the number of interconnections is minimized while the difference in the values of the cost functional for the standard and decentralized controller is a constraint. To find the value of the cost of the decentralized control in presence of interconnections one can use linear matrix inequalities.

Keywords: decomposition,decentralized control,linear matrix inequalities

Digital Object Identifier (DOI): 10.3182/20060830-2-SF-4903.00009

Conference: 1st IFAC Workshop on Applications of Large Scale Industrial Systems, 2006

Location: Cruise liner M/S Silja Line, Finland

Start Date: Wed Aug 30 2006 - End Date: Thu Aug 31 2006

Page Numbers: 47-52

Authors: Sergiu Caraman; Mihaela Sbarciog; Marian Barbu

Abstract: The paper deals with the design of a predictive controller for a wastewater treatment process. In the considered process, the wastewater is treated in order to obtain an effluent having the substrate concentration within the standard limits established by law (below 20 mg/l). This goal is achieved by controlling the concentration of dissolved oxygen to a certain value. The predictive controller uses a neural network as internal model of the process and alters the dilution rate in order to fulfill the control objective. This control strategy offers various possibilities for the control law adjustment by means of the following parameters: the prediction horizon, the control horizon, the weights of the error and the command. The predictive control structure has been tested in three functioning regimes, considered essential due to the frequency of occurrence in current practice.

Keywords: predictive control,wastewater treatment,neural network,bioreactor

Digital Object Identifier (DOI): 10.3182/20060830-2-SF-4903.00028

Conference: 1st IFAC Workshop on Applications of Large Scale Industrial Systems, 2006

Location: Cruise liner M/S Silja Line, Finland

Start Date: Wed Aug 30 2006 - End Date: Thu Aug 31 2006

Page Numbers: 155-160

Authors: Hans Aalto

Abstract: Natural gas pipeline systems are very complicated. From a dynamic modelling, control and optimisation perspective, the number of model states is typically many thousands, the number of disturbance variables can be several hundred and the length of the prediction horizon for predictive control and optimsation must be long enough to include the very slow dynamics and the predicted important future events - typically gas consumption changes- in the system. Simplifications and approximations made to the original large-scale real-time optimisation problem results in a simplified receding horizon quadratic programming problem.

Keywords: real-time systems,optimal control,optimisation

Digital Object Identifier (DOI): 10.3182/20060830-2-SF-4903.00030

Conference: 1st IFAC Workshop on Applications of Large Scale Industrial Systems, 2006

Location: Cruise liner M/S Silja Line, Finland

Start Date: Wed Aug 30 2006 - End Date: Thu Aug 31 2006

Page Numbers: 167-172

Authors: Matti Paljakka; Olli Venta

Abstract: In today's industry, the requirements concerning the cost effectiveness of the production as well as end product quality are becoming even harder. Companies operating at real time in globalized business require agile production that quickly responds to changes in the business environment. The build-up, operation and maintenance of large scale industrial production systems require a whole network of experts of different domains. In setting up such a network, one must carefully design the roles of the actors in a manner that the network supports the overall performance of the system. Also the views through which each actor accesses the system must be designed to efficiently support his decision making. Recent research has made great advancement in data mining and information discovery in large sets of data. Also the modelling and simulation is slowly but surely being taken up in different phases of the plant life span. The standardization of plant life cycle data as well as on-line interfaces for the exchange of data and events has taken steps forward. Furthermore, mobile solutions and advanced visualization are entering the industry. All of this is surely helpful in managing large scale industrial systems. Often the question remains: what is the overall good performance of the system. What is now needed from the research is practical methods for selecting appropriate performance metrics and for implementing decision support systems for managing and controlling of the operative state in a large scale industrial system. The methods must take into account the network nature of the organization and the human-technology interaction of each actor in the network.

Keywords: large-scale systems,decision support systems,models,standards

Digital Object Identifier (DOI): 10.3182/20060830-2-SF-4903.00024

Conference: 1st IFAC Workshop on Applications of Large Scale Industrial Systems, 2006

Location: Cruise liner M/S Silja Line, Finland

Start Date: Wed Aug 30 2006 - End Date: Thu Aug 31 2006

Page Numbers: 136-136

Authors: Kozakova Alena; Vesely Vojtech

Abstract: The paper deals with the frequency domain robust decentralized controller design technique for continuous-time uncertain systems given as a set of transfer function matrices. By applying the independent designs to individual subsystems modified by pertinent entries of a suitably chosen diagonal transfer function matrix, nominal stability and fulfillment of the M - Δ structure based robust stability conditions modified for decentralized systems are guaranteed.

Keywords: robust control,linear systems,frequency domain

Digital Object Identifier (DOI): 10.3182/20060830-2-SF-4903.00008

Conference: 1st IFAC Workshop on Applications of Large Scale Industrial Systems, 2006

Location: Cruise liner M/S Silja Line, Finland

Start Date: Wed Aug 30 2006 - End Date: Thu Aug 31 2006

Page Numbers: 41-46

Authors: Danica Rosinova; Vojtech Vesely

Abstract: The new LMI based method for robust stability analysis for linear uncertain system with PID controller is proposed. The general constrained structure of controller matrix is considered appropriate for both output feedback and decentralized control and the respective guaranteed cost control design scheme is presented. The sufficient robust stability condition is developed for extended quadratic performance index including first derivative of the state vector to damp oscillations. The obtained stability condition is formulated for parameter-dependent Lyapunov function.

Keywords: uncertain systems,robust stability,decentralized control,linear matrix inequalities (LMI),Lyapunov function

Digital Object Identifier (DOI): 10.3182/20060830-2-SF-4903.00010

Conference: 1st IFAC Workshop on Applications of Large Scale Industrial Systems, 2006

Location: Cruise liner M/S Silja Line, Finland

Start Date: Wed Aug 30 2006 - End Date: Thu Aug 31 2006

Page Numbers: 53-58

Authors: Mikko Heikkinen; Ville Nurminen; Yrjo Hiltunen

Abstract: Self-organizing maps (SOM) have been successfully applied in many fields of research. In this paper, we demonstrate the use of SOM-based method for the analysis of EPS-batch process. A data set of EPS-batch process was used for training a SOM. This SOM could be used for estimating the optimal amounts of the stabilisation agent. The results of a validation data set showed a good agreement between the actual and estimated amounts of the stabilisation agent. Based on this model a Web application was made for test use at the plant. The results indicate that the SOM method can also be efficiently applied to the analysis of the batch process.

Keywords: artificial intelligence,neural networks,self-organizing systems,process control,process identification

Digital Object Identifier (DOI): 10.3182/20060830-2-SF-4903.00034

Conference: 1st IFAC Workshop on Applications of Large Scale Industrial Systems, 2006

Location: Cruise liner M/S Silja Line, Finland

Start Date: Wed Aug 30 2006 - End Date: Thu Aug 31 2006

Page Numbers: 191-195

Authors: T. Yucelen; O. Kaymakci; S. Kurtulan

Abstract: In this paper a modified PID controller is presented as a dynamic system controller. Here Ziegler-Nichols process reaction method is clarified to designate self-tuning, and advantages of self-tunining are also explained in detail. Moreover, simulation results of self-tuning PID controller using Ziegler-Nichols are acquired from programmable logic controller (PLC), and then are given in related topics. Finally, the complete algorithm is tested in an industrial thermal system, and results of this test are offered and explained.

Keywords: PID control,Ziegler Nichols process reaction method,robustness,self-tuning control

Digital Object Identifier (DOI): 10.3182/20060830-2-SF-4903.00003

Conference: 1st IFAC Workshop on Applications of Large Scale Industrial Systems, 2006

Location: Cruise liner M/S Silja Line, Finland

Start Date: Wed Aug 30 2006 - End Date: Thu Aug 31 2006

Page Numbers: 11-16

Authors: Jingsong Wang; Mietek A. Brdys

Abstract: In operational control of hybrid systems, control objectives often change with current operating conditions and switching among a number of control strategies is then inevitable. The proposed softly switched hybrid predictive control utilizes mixed integer programming techniques and achieves better switching transient performance both in system output/state and control input than the traditional hard switching method. Stability of the designed soft switching process is analysed and sufficient stabilization conditions are derived. Numerical examples with simulation results show that the proposed approach can be useful in practical applications.

Keywords: predictive control,hybrid systems,mixed integer programming,constraints,stability analysis,supervisory control,sequential switching

Digital Object Identifier (DOI): 10.3182/20060830-2-SF-4903.00006

Conference: 1st IFAC Workshop on Applications of Large Scale Industrial Systems, 2006

Location: Cruise liner M/S Silja Line, Finland

Start Date: Wed Aug 30 2006 - End Date: Thu Aug 31 2006

Page Numbers: 29-34

Authors: Duc T. Nguyen; Mietek A. Brdys

Abstract: A dynamic neural network based algorithm for learning control of an unknown nonlinear continuous-time multiple-input-multiple-output plant with unmeasurable states is proposed in this paper. A new dynamic neural network structure is utilised to model the unknown plant dynamics through modelling the input-output mapping. A feedback linearization is applied to design controller for the neural model and the neural states are used as a source of precious information about current plant dynamics. A gradient based update of the weights is performed at discrete time instants over a moving measurement window in order to reduce the model output - real output mismatch. The learning controller is applied to a double link robot arm. Stability of the system is analysed through ultimate boundedness of all signals.

Keywords: dynamic neural networks,robotic manipulators,on-line learning,non-linear control systems,feedback linearization,ultimate boundedness

Digital Object Identifier (DOI): 10.3182/20060830-2-SF-4903.00005

Conference: 1st IFAC Workshop on Applications of Large Scale Industrial Systems, 2006

Location: Cruise liner M/S Silja Line, Finland

Start Date: Wed Aug 30 2006 - End Date: Thu Aug 31 2006

Page Numbers: 23-28

Authors: Mats Nikus; Mikko Vermasvuori; Nikolai Vatanski; Sirkka-Liisa Jamsa-Jounela

Abstract: The aim of the work presented in this paper is to assess the ability of support vector machines (SVM) for detecting measurement faults. Two different support vector machine approaches for detecting faults are tested and compared to neural networks. The first method is based on a SVM regression model together with an analysis of the residuals whereas the second method is based on a SVM classifier. The methods were applied to a rigorous first principles based dynamic simulator of a dearomatization process.

Keywords: fault detection,monitoring,support vector machines,classification,regression,dearomatization process

Digital Object Identifier (DOI): 10.3182/20060830-2-SF-4903.00040

Conference: 1st IFAC Workshop on Applications of Large Scale Industrial Systems, 2006

Location: Cruise liner M/S Silja Line, Finland

Start Date: Wed Aug 30 2006 - End Date: Thu Aug 31 2006

Page Numbers: 226-231

Authors: Fisera Peter; Holler Manfred

Abstract: The control task of the bleaching process is complicated by long retention time and strong process nonlinearity. The classical control tools are ineffective because of long retention time and new neuronal control systems have serious difficulties with process nonlinearity. After process change, they have to learn again to find parameters for the new working point. To support learning process of the multivariable controllers, the mathematical model of the bleaching process has been designed. The basic kinetic model is the reaction of dissociated HOO- molecules with chromophore groups. Ongoing reaction decreases HOO- concentration and changes bleaching conditions for following reactions. The NaOH creates conditions for peroxide dissociation and also attacks the lignin molecules, decreasing yield of bleaching process. The yellowing reaction due to high concentration of NaOH is included, as well. The peroxide decomposition process caused by high temperature or heavy metals is also part of the bleaching model. To simplify solution of complicated system of partial differential equations, the whole volume of the bleaching tower has been vertically divided to thin slices. The bleaching conditions in one slice are considered to be homogenous an constant during time t and t+? t. The chromophore are divided into the light, difficult bleachable and non bleachable groups with corresponding consumption of HOO- molecules. The supporting chemical reactions are also calculated in each slice separately creating conditions for next calculation step. The parameters of the chemical reactions have to be found using laboratory results. The model of peroxide bleaching process forecasts the bleaching results with an accuracy of ±1% taking into consideration, of course, that the main process variables are measured. Bigger deviation between calculated and measured results means significant changes in not measured process variables. This fact can be used as alarm. The model of the bleaching process integrated into multivariable model predictive controller enables setting of controller parameters in short time instead to learn controller from process. The model of bleaching process was tuned according to the results of laboratory bleaching trials. After setting of model parameters the model reached laboratory values for final brightness, pH, residual peroxide and COD. Model has been tuned to several different bleaching trials of mechanical pulps and also to results of laboratory bleaching of waste paper has been used to prove model universality. In all cases it was possible to tune model to meet bleaching results according to the used bleaching recipe. The model was also tested on-line in field-side reference HC Bleach Plant. Model parameters were tuned according to the laboratory results. Measured process values like pulp flow, consistency, charging of bleaching chemical and incoming brightness have been used as model variables. The Model calculated bleaching reactions and the out coming calculated brightness was over 90% of tested period very closed to the measured one (±1% ).

Keywords: mechanical pulp,peroxide,chromophore groups,bleaching process,brightness,delignification,model predictive controller

Digital Object Identifier (DOI): 10.3182/20060830-2-SF-4903.00013

Conference: 1st IFAC Workshop on Applications of Large Scale Industrial Systems, 2006

Location: Cruise liner M/S Silja Line, Finland

Start Date: Wed Aug 30 2006 - End Date: Thu Aug 31 2006

Page Numbers: 70-75

Authors: E. Ikonen; E. Gomez-Ramirez; K. Najim

Abstract: This paper deals with the open-loop tracking control of batch and repetitive chemical reactors on the basis of a genealogical decision trees (GDT). GDT are a population-based random search technique for solving trajectory tracking problems. The idea behind the GDT consists of associating Gaussian distributions to the norms of the control actions and the tracking errors. This stochastic search model can be interpreted as a simple genetic particle evolution model with a natural birth and death interpretation. It converges in probability. Numerical examples dealing with temperature control of two simulated reactors illustrate the feasibility and the e ?ciency of this control algorithm. An extension to regulation based on on-line state information is briefly outlined.

Keywords: Monte Carlo method,optimal control,optimization problems,particle filtering,population-based search

Digital Object Identifier (DOI): 10.3182/20060830-2-SF-4903.00033

Conference: 1st IFAC Workshop on Applications of Large Scale Industrial Systems, 2006

Location: Cruise liner M/S Silja Line, Finland

Start Date: Wed Aug 30 2006 - End Date: Thu Aug 31 2006

Page Numbers: 185-190

Authors: Vladimir Jovan; Sebastjan Zorzut; Alenka Znidarsic

Abstract: A synthesis of plant-wide control structures is recognized as one of the most important design problem in production management in process industries. This paper proposes a closed-loop control structure with the utilisation of production Key Performance Indicators (KPIs) as possible solution to this problem. Production KPIs represent the translation of operating objectives, such as minimization of production costs, to a set of measurable variables that can then be used in a feedback control. The idea of production feedback control using production KPIs as referenced controlled variables was implemented on a procedural model of a production process for a polymerisation plant. Some preliminary results show usefulness of proposed methodology.

Keywords: production control,productivity,decision support systems,closed-loop control,model-based control

Digital Object Identifier (DOI): 10.3182/20060830-2-SF-4903.00031

Conference: 1st IFAC Workshop on Applications of Large Scale Industrial Systems, 2006

Location: Cruise liner M/S Silja Line, Finland

Start Date: Wed Aug 30 2006 - End Date: Thu Aug 31 2006

Page Numbers: 173-178

Authors: Timo Ahola; Esko Juuso; Kauko Leiviskä

Abstract: This paper describes the possibilities of variable selection in large-scale industrial systems. It introduces knowledge-based, data-based and model-based methods for this purpose. As an example, Case-Based Reasoning application for the evaluation of the web break sensitivity in a paper machine is introduced. The application uses Linguistic Equations approach and basic Fuzzy Logic. The indicator combines the information of on-line measurements with expert knowledge and provides a continuous indication of the break sensitivity. The web break sensitivity defines the current operating situation at the paper mill and gives new information to the operators. Together with information of the most important variables this prediction gives operators enough time to react to the changing operating situation.

Keywords: variable selection,grouping,paper machine,web breaks

Digital Object Identifier (DOI): 10.3182/20060830-2-SF-4903.00016

Conference: 1st IFAC Workshop on Applications of Large Scale Industrial Systems, 2006

Location: Cruise liner M/S Silja Line, Finland

Start Date: Wed Aug 30 2006 - End Date: Thu Aug 31 2006

Page Numbers: 88-93