Authors: Ruiyun Qi; Mietek A. Brdys

Abstract: A Takagi-Sugeno (T-S) fuzzy model based adaptive control algorithm for a class of multiple-input-multiple-output (MIMO) nonlinear uncertain systems is presented in this paper. The T-S model consists of a set of linear local models which can be considered as the linearization models of the nonlinear systems in different operating regions. Local integral controllers are designed based on local linear fuzzy models and combined to generate the overall controller using fuzzy weighted integration. The consequent parameters of the T-S model can be updated online in the presence of external disturbances and parameter perturbations. Stability analysis shows all the signals in the closed-loop system are bounded. Simulation results on tracking control of a two-link robot manipulator are given to illustrate the effectiveness of the proposed method.

Keywords: indirect adaptive control,fuzzy control,Takagi-Sugeno (T-S) models,local linear controller

Digital Object Identifier (DOI): 10.3182/20060830-2-SF-4903.00025

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: 137-142

Authors: M. Kettunen; S-L. Jamsa-Jounela

Abstract: The fault detection and isolation (FDI) in industrial processes has been under an active study during the last decade, but fault tolerant control applications relying to the traditional FDI methods have been scarce. In this paper a fault tolerant model predictive controller (MPC) with an embedded FDI system is developed for controlling a simulated heavy oil fractionator process, the Shell Control Problem (SCP). Two different kinds of FDI systems are used for achieving the fault tolerance in co-operation with MPC: system based on Principal Component Analysis (PCA) and Partial Least Squares (PLS) and a system based on Subspace Model Identification (SMI). The effectiveness of selected methods was successfully tested by introducing bias and drift faults to simulated process measurements. Finally the results are presented and discussed.

Keywords: FTC,FDI,PCA,PLS,SMI,MPC,fault tolerance,simulation,shell control problem

Digital Object Identifier (DOI): 10.3182/20060830-2-SF-4903.00026

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: 143-148

Authors: Bernt M. Akesson; Mats J. Nikus; Hannu T. Toivonen

Abstract: The objective of this work is to study the capabilities of support vector machines for approximating the complex control law arising from model predictive control of a hybrid MIMO-system. By approximating the control law, an explicit formulation can be obtained, which is computationally less intensive for on-line use. The explicit model predictive control approach is applied to a simulated hybrid systemconsisting of two tanks in series. The system has real-valued, integer-valued, and binary-valued control inputs. A model predictive controller is first designed to control the entire system. This controller is then approximated using support vector machines, with separate approximators for each control input. Reasonable control results were achieved with the approximators.

Keywords: model predictive control,hybrid systems,support vector machines,approximations

Digital Object Identifier (DOI): 10.3182/20060830-2-SF-4903.00027

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: 149-154

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: J. Vettenranta; S. Smeds; K. Yli-Opas; M. Sourander; V. Vanhamaki; K. Aaljoki; S. Bergman; M. Ojala

Abstract: Realtime economical optimization of production plants has traditionally relied on steady state process models. Because real plants are normally in transient states, such models could be adapted to measurements only occasionally. Neste Jacobs Oy has developed a new closed loop dynamic realtime optimization (DRTO) technology, which optimizes the plants also during transient states. The technology permits optimization practically in realtime, which contributes to quickly reaching optimum. The DRTO application example is in the Ethylene Plant of Borealis Polymers Oy, Porvoo, Finland. The DRTO is in continuous use since 2004 and the experience has been outstanding.

Keywords: optimization,dynamic,closed loop,nonlinear,process models,adaptation

Digital Object Identifier (DOI): 10.3182/20060830-2-SF-4903.00029

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: 161-166

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: 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: Jaakko Fonselius

Abstract: A modern paper machine is a very complicated piece of machinery and full of automation. Paper machine specialists can be in different locations around the world and that is why efficient communication networks are needed to transfer technical information between them. This paper specifies the terminology to cope with information transfer in a paper machine project. The information transfer techniques and system architecture during different generations of the paper mill automation systems are described briefly. Limitations of different generations of remote services are also discussed. The need for different communication networks is specified as well as the need for changes in management of cooperation between different partners in paper industry. The use of Internet technology is described in the communication systems.

Keywords: communication networks,database,diagnostic,documentation,integration

Digital Object Identifier (DOI): 10.3182/20060830-2-SF-4903.00032

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: 179-184

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: 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: Fu-Shiung Hsieh

Abstract: Holonic manufacturing systems (HMS) provide a flexible and decentralized manufacturing environment to accommodate changes and to meet customers' requirements dynamically. HMS is based on the notion of holon, an autonomous, co-operative and intelligent entity able to collaborate with other holon to process the tasks. It enables the construction of very complex systems that are nonetheless efficient in the use of resources, highly resilient to disturbances and adaptable to changes in the environment. To perform a task in HMS requires a minimal set of holons to form a collaborative network. As individual holons may be unreliable, this adds complexity in modeling and analysis of HMS. How to dynamically form a minimal cost collaborative network for a task and analyze the effects of resource failures on the system operation are challenging issues. In this paper, we consider holonic assembly/disassembly systems with unreliable resource holons. We propose a Petri net to model a collaborative network and study its robustness. Robustness analysis concerns with the ability for a system to maintain operation in case of resource failures. Existing results on robustness analysis are developed based on ordinary Petri net models. However, non-ordinary controlled Petri nets have the advantages to compactly model assembly/disassembly systems where multiple identical resources may be required to perform an operation. This motivates us to propose a non-ordinary collaborative Petri net (NCPN) for this class of systems and extend the robustness analysis to NCPN.

Keywords: holonic manufacturing systems,collaborative network Petri-nets,robustness

Digital Object Identifier (DOI): 10.3182/20060830-2-SF-4903.00035

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: 196-201

Authors: Eric Duviella; Pascale Chiron; Philippe Charbonnaud

Abstract: The Hybrid Control Accommodation (HCA) strategy was proposed to improve the water asset management of hydraulic systems by resource allocation and setpoint assignment. Hydraulic system dynamics are taking into account during the setpoint assignment step which consists in controlling gates for larges operating conditions. For hydraulic systems subjected to strong disturbances, transfer delays are variable, thus different operating modes must be considered. A multimodelling method associated with a transfer delay selection technique allowing for the determination of the number of models, is proposed. The simulation results on the first reach of the Neste canal show the effectiveness of the HCA strategy.

Keywords: hybrid control accommodation,resource allocation,setpoint assignment,multimodelling,water management

Digital Object Identifier (DOI): 10.3182/20060830-2-SF-4903.00036

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: 202-207

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

Abstract: Monitoring of multidimensional, sophisticated processes still can be a challenge. The paper presents tools to handle such cases, which are based on the Principal Component Analysis with the adaptive enhancement. A novel PCA algorithm is derived with the adaptive supervisor. It is applied to monitoring operation of wastewater treatment plant and tested by simulation based on real data records.

Keywords: monitoring,detection algorithms,statistical process control,frequency signal analysis,multidimensional systems,wastewater treatment

Digital Object Identifier (DOI): 10.3182/20060830-2-SF-4903.00037

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: 208-213

Authors: Hui Cheng; Mats Nikus; Sirkka-Liisa Jamsa-Jounela

Abstract: The aim of the work presented in this paper is to evaluate the ability of the causal digraph method to detect and isolate faults on a simulated paper machine process. A causal digraph model for the short circulation process of the paper machine was constructed, identified and used to detect and isolate artificial faults in the simulation environment. The fault of headbox slice opening was studied and diagnosed.

Keywords: fault detection,fault isolation,causal digraph,papermaking,APROS simulator

Digital Object Identifier (DOI): 10.3182/20060830-2-SF-4903.00038

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: 214-219

Authors: Jesus Mina; Cristina Verde

Abstract: The Dynamic Principal Component Analysis is an adequate tool for the monitoring of large scale systems based on the model of multivariate historical data under the assumption of stationarity, however, false alarms occur for non-stationary new observations during the monitoring phase. In order to reduce the false alarms rate, this paper extends the DPCA based monitoring for non-stationary data of linear dynamic systems, including an on-line means estimator for the standardizing of the observations according to the estimated means. The effectiveness of the proposed methodology is evaluated for fault detection in a interconnected tanks system.

Keywords: fault detection,statistical analysis,dynamic principal component analysis,time series analysis,non-stationary signals

Digital Object Identifier (DOI): 10.3182/20060830-2-SF-4903.00039

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: 220-225

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: 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: G. Ewald; W. Kurek; Mietek A. Brdys

Abstract: There is a group of problems that require big amount of computing power to solve. Computer grids allow building effective computing platforms at relatively low cost. It is expected that algorithms like Genetic Algorithm will perform well on the grid. In this paper, grid implementation of multiobjective distributed genetic algorithm is proposed. A distributed version of the algorithm is based on a modified island algorithm where genetic data exchange is replaced by introduced new Forgetting Island Elitism. The algorithm is applied to booster station allocation in Chojnice water distribution system.

Keywords: parallel algorithms,parallel computation,multiobjective optimizations,genetic algorithms,computing systems,decision making,quality control,environmental engineering

Digital Object Identifier (DOI): 10.3182/20060830-2-SF-4903.00042

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: 238-243

Authors: K. Duzinkiewicz; A. Ciminski

Abstract: An optimisation based approach to simplification of a network model of pressurized drinking water distribution systems (DWDS), called skeletonization, has been proposed. DWDS simulation has been improved considerably during the last decades. There are two major aspects in modelling, monitoring and control of DWDS: quantity (water hydraulics) and quality. In the following paper the modelling of the water hydraulics in DWDS is considered. There is a need to build a simplified model of the drinking water network that preserves relation between flows and pressures in the main pipes and contains elements essentials for control - tanks, pumps, valves or others. The degree of simplification should be a compromise between needed model's accuracy and computational efficiency of the monitoring and control algorithms. Different approaches are proposed for DWDS model simplification. In the proposed method some parts of the network structure remain unchanged and the others are replaced by a simple radial structure. Parameters of the radial structure are calculated by solving dedicated optimisation problem. The simplification results based on the proposed method are illustrated by simulation case study for physical drinking-water distribution system and a comparison with the result obtained based on common sense method are presented.

Keywords: drinking water distribution network,model simplification,optimization,simulation

Digital Object Identifier (DOI): 10.3182/20060830-2-SF-4903.00043

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: 244-249

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