Availability of belt conveyor systems is essential in production and logistic lines to safeguard production and delivery targets to customers. In this paper, experiences from commissioning, validation, and operation of an interactive predictive maintenance solution are reported. The solution and its development is formerly presented in Al-Kahwati et.al. (Al-Kahwati, Saari, Birk, & Atta, 2021), where the principles to derive a digital twin of a typical belt conveyor system comprising component-level degradation models, estimation schemes for the remaining useful life and the degradation rate, and vision-based hazardous object detection.
Furthermore, the validation approach of modifying the belt conveyor and thus exploiting the idler misalignment load (IML) for the degradation predictions for individual components (including long-lasting ones) together with the actionable insights for the decision support is presented and assessed. Moreover, the approach to testing and validation of the object detection and its performance is assessed and presented in the same manner. An overall system assessment is then given and concludes the paper together with lessons learned.
As pilot site for the study a belt conveyor system at LKAB Narvik in northern Norway is used.
Predictive maintenance strategies for the mining sector are of utmost importance considering the automated behavior of industrial systems and the oftentimes inaccessible environment around belt conveyor systems. In this paper, we present a model combining IoT sensors and dead-reckoning modeling, focused on early theoretical work in the field of modeling the behavior of belt conveyor systems to act as a decision support tool in maintenance strategies, by estimating the remaining useful life (RUL) of rotating components in a belt conveyor system. The estimation of RUL is a function of the degradation of the ball bearings in idler rollers due to the forces acting on the rollers during the conveyance of material. The forces occur due to the material loading, the belt weight, roller shell weight, and the idler misalignment load (IML). Furthermore, the dynamics of bulk material during conveyance can be modeled in several ways considering earth pressure theory. A model considering this is derived from the Krausse Hettler method to determine the forces acting on the wing rollers of a thee-roll idler trough set by the notion that the bulk material undergoes active and passive stress states during conveyance. The model is further compared and extended to the works of Sokolovski, to get a bounded delta RUL reduction estimate on the roller bearings in each idler set of a belt conveyor system.
District heating and cooling (DHC) networks are large scale complex systems which aregenerally difficult to operate and optimize. The large thermal inertia in the systems leadsto long reaction times on changes at the consumer side, which means that forecasting ofconsumer behaviour is a needed tool for efficient operation. Within the European Unionmany major research project target the energy reduction on the consumption side and peakload management while maintaining customer satisfaction.The optimal operation of a DHC network can therefore be considered as an interestingarea of investigation due to a number of aspects, like (i) the vast amount of the energy that is distributed by these networks, (ii) the demand to provide a better quality of services by the operators of these networks, and (iii) compliance with new environmental regulations. In this presentation, we discuss a possible conceptual method that utilizes a simpliedstatic model of different types of consumers in the network to design a decision supportsystem that will guide the operators of the DHC network to optimally operate the networkwith different operational scenarios that include but not limited to: (i) energy consumptionminimization, (ii) economic operation, (iii) peak load reduction/shifting, and (iv) environmentally friendly operation. In its current form, the operator will be informed, while in thefuture these actions could be fully automated in a closed loop context.The DHC network in Luleå, Sweden will be used as a test case which represents a typicalmedium size network. The case has a number of properties which motivate its study likee.g. the distributed generation possibilities, the geographical distribution of the consumers,and the different types of consumers in the area. The presentation will be concluded with anoutlook on future tracks of research and development
In this paper, we propose a perturbation amplitude adaption scheme for phasor extremum seeking control based on the plant's estimated gradient. By using phasor extremum seeking instead of classical extremum seeking, the problem of algebraic loops in the controller formulation is avoided. Furthermore, a stability analysis for the proposed method is provided, which is the first stability analysis for extremum seeking controllers using adaptive amplitudes. The proposed method is illustrated using numerical examples and it is found that changes in optimum can be tracked accurately while the steady-state perturbations can be reduced significantly.
In the face of environmental regulations, optimization of industrial processes becomes necessary. This doctoral thesis summarizes the results of three application-driven projects in automatic control that were aimed at process optimization in the steel industry. The objective of the projects was to apply advanced control strategies to two important processes in steel making, namely pulverized coal injection (PCI) in blast furnaces and LD converters. Firstly, an LQ multivariable controller with gas leakage detection system for PCI vessels is designed and analyzed. Secondly, a foam level control system for the LD converter process using an audio signal for measurement is designed. Thirdly, it is attempted to create a single line flow control system for PCI using a video camera. In the latter two cases the conservative approach of inferring unmeasurable physical quantities from the audio and video sources is used. Moreover, all the designs are tested through implementation or experiments at the industrial plant. The control and gas leakage detection system ended up as a full-scale industrial implementation, whereas the projects comprising audio and video information is still at an experimental stage. Work with implementation and experiments pays off in experiences and further insights in the application of control theory, and reveals weaknesses and gaps in the existing theory. Thus, application-driven projects lead to practical solutions and at the same time pose new theoretical challenges. Consequently, this chain of events is favorable to both practitioners and theoreticians, and in turn stimulates the collaboration of industry and academia. Unfortunately, in many research projects this sequence is reversed which complicates technology transfer into industry. As a spin-off effect from the multivariable control project of the PCI process two topics are addressed anew. In the problem of measurement/actuator pairs assignment for decentralized control, the geometrical background of Gramian-based interaction measures is clarified. It is shown that weighted Gramian-based interaction measures can be effectively used for control structure design. In control structure improvement of multivariable control systems, it is shown that improvement potentials can be deduced from coarse models of the closed-loop system. Finally, in the projects comprising audio and video signals in control applications, it is concluded that the theory is rather undeveloped and that these sources should be treated as a multivariable system.
Intelligent Industrial Processes is an area of excellence in research and innovation at Luleå University of Technology (LTU), which was formed to promote multi-disciplinary research and innovation relating to Process Industrial Automation, also referred to as ProcessIT. LTU has a strong track record of research in close collaboration with process industries, where research results have often found their way into products and services strengthening the industries position on the global market.For this area of excellence a road mapping study with respect to Automatic Control research was conducted and is summarized in this white paper. The study shows that current research activities in Automatic Control are very relevant to Intelligent Industrial Processes, dealing with techniques for process understanding (modeling), design and implementation of control systems, and process monitoring, only to mention some.It is concluded that the design and establishment of an Open Research and Innovation Platform is essential for collaborative and multi-disciplinary research in the area. Such a software platform will enable industry partners to more efficiently work with their industrial processes and that in close collaboration with researchers and engineering businesses. At the same time researchers and innovators will have the opportunity to test and validate their results and innovations on real-life cases, enabling a swift exploitation of results. Some key principles for this software platform are the open source, open data and open innovation principles that need to be captured in the platform.The results of that study suggest initial automatic control research activities and a time line for stepping stones towards a full scale implementation of an Open Research and Innovation Platform by 2030.
A steering system (100) and a control algorithm for vehicle servo-steering which acts so that a steering-wheel torque applied by the driver is transformed to a vehicle behaviour. The steering system (100) consists of a steering rack (124), and tie rods (125) connected to the steered wheels of the vehicle (127). The vehicle's steering wheel (120) is connected to the rack (124) via a steering column (121). The steering column (121) contains a torsion bar (128) with a torque sensor in order to measure the steering torque applied by the driver. An assistance torque is given by an actuator (115) which is controlled by a control system (110). The control system (110) contains a control algorithm which translates the steering torque applied by the driver to a reference value in the form of a yaw and/or lateral vehicle state. The servo-system is controlled so that this reference value is attained
This licentiate thesis deals with a multivariable controller of a pneumatic conveying system. The industrial process used to illustrate design, analysis and implementation of a multivariable controller is the injection of fine coal into a blast furnace. In the blast furnace process, coke is replaced by fine coal because of economical and environmental reasons. The coal mass flow to the blast furnace becomes a crucial parameter for its operation and hence a control system should be in place to maintain a constant flow. An optimal multivariable linear-quadratic controller has been designed in order to replace the conventional PI-controllers, which were not able to reach the desired control objectives. The design is analyzed by deriving the sensitivity functions of the closed loop system to noise, disturbances and uncertainties. The multivariable controller is then validated through experiments and test operation at the coal injection plant at SSAB Tunnplåt AB in Luleå, Sweden. The reached performance improvements compared with the conventional PI-controllers account for up to 80%. Finally, the controller is combined with a gas-leakage detection system to the commercially available product SafePCI, which is now installed and in operation at SSAB Tunnplåt AB in Luleå, Sweden.
This paper deals with the optimisation of control structures for multivariable process control systems. Incremental optimisation of control structures is the task of improving the performance of an existing control structure by incrementally introducing or removing dynamic connections in the control structure. A preliminary method for the detection of an improving structural change in an existing control structure is presented. The method is applied to the control of a pulverized coal injection process to show its validity and has proven to give good results.
This paper deals with physical modelling and control of dynamic foaming in the LD-converter process. An experimental setup consisting of a water model, DSP and PC hardware is built up and shown to be useful for studying dynamic foaming. Furthermore, a foam height estimation algorithm is presented and validated through experiments. Finally, sound signals from the LD-converter and water model are compared and similarities between them are found.
This paper deals with physical modeling and control of dynamic foaming in the LD-converter process. An experimental setup consisting of a water model, digital signal processor, and PC hardware is built and shown to be useful for studying dynamic foaming. Furthermore, a foam height estimation algorithm is presented and validated through experiments. Finally, sound signals from the LD-converter and water model are compared and similarities between them are found.
This paper deals with estimation and control of foam level in dynamic foaming. An improved foam level estimation methodology from a microphone signal and its automatic calibration is presented. The dynamical reaction of the foam level on air lance movements is modelled using system identification. Based on the resulting mathematical model, a controller for foam level stabilisation is designed and applied to a water model, representing the LD converter process. It is shown that the foam level can be controlled using a microphone as the measurement device and air lance movement as the actuator.
The main contribution of this paper is to study the feasibility of an automated approach to the assessment and synthesis of control loops in substations of a district heating and cooling system. The low-level controllers in substation are usually PID-type controllers and can not easily be changed. Moreover, the tuning of these controllers is often done in an ad-hoc manner and remains in the initial tuning despite changes in the substation over their operational life. Consequently, insufficient control performance due to false tuning can be misinterpreted as a hardware issue and lead to unnecessary replacement of parts.
In order to solve this problem, the paper proposes an approach to assess the control loop performance based on logged data from substations, and to subsequently tune the current substation controllers, when no hardware issues are detected. The approach is applied to a well-known building substation model in simulation, which indicates that the approach is feasible.
Analysis of acquired data from a number of substations in the DHC system of Luleå Energi AB, provides evidence for the problem and how the approach can be applied in its future implementation. Moreover, a number of challenges and future work are indicated.
This work in progress paper presents an approach for knowledge reinforcement of students by introducing student-held course seminars reflecting back on the knowledge from prior courses relevant to current course topics. The paper discusses the motivation of the approach, its practical implementation, and observation made during two consecutive course instances. Further, course evaluations are used to reflect on the efficacy of the proposed approach and its future refinement.
This paper discusses the joint use of control configuration selection and adaptive model predictive control for the reconfiguration and improvement of a control system for the heat generation and distribution in a district heating system. The traditional PID-type multi-loop controller configuration is assessed from its feasibility and potential to be improved, on the basis of automatically generated models. The studied test case is the district heating system in Luleå, Sweden.
It is found that a multivariable controller for a subsystem of the complete system could largely improve the performance of the system and thereby addressing confirmed oscillations in the system. An adaptive model predictive controller is implemented in the realistic simulator OPTi-Sim for the district heating system in Luleå, Simulation results confirm that the oscillations which are present in the simulation with the current control scheme can be largely reduced through the use of the proposed controlled.
An active safety system (10) for a vehicle comprising: - an external object sensor system (24) arranged on a host vehicle (12), said sensor system (24) being arranged to, within a detecting range (22) of said sensor system (24), sense objects (14 - 20) external to said host vehicle (12) and generate input data relating to said objects (14 - 20), wherein said input data include an object position ((R,È rel )(t)), - a threat indicator (26) which is arranged to assign a threat level (T k (t)) to each external object (k; 14 - 20) detected by the sensor system (24); and a method run in an active safety system.
The invention relates to an onboard warning system for a host vehicle (1), a system comprising a sensor system detecting a presence of external objects (2) within a sensor detection area (3) and an external object movement determination unit (5) arranged to determine a measure of a relative movement of said external objects to said host vehicle. The invention is characterized in that the warning system further includes: a host vehicle movement determination unit (4) arranged to determine a relative movement of said host vehicle to a ground-fixed coordinate system; a unit (6) for determination of a measure of a absolute acceleration of said external objects to said ground-fixed coordinate system by transformation of the measure of the relative movement of said external objects to said host vehicle into said ground-fixed coordinate system using the relative movement of said host vehicle determined by said host vehicle movement determination unit; and a warning signal generator (7) arranged to generate a warning signal when said measure of absolute acceleration of said external objects relative to said fixed ground acceleration system in the sensor detection area exceeds a threshold value.
The invention relates to a method for determining a measure for evaluation of the behaviour of a driver of a vehicle comprising: determining the lateral position of the vehicle in relation to a lane and the state of the vehicle at a first instant (t1), determining the planned path which the vehicle would be expected follow from said first instant t1 considering the state of the vehicle at said first instant (t1), determining the planned lateral position of the vehicle in relation to a lane at a second instant (t2) being a time interval ( t PD ) after t1, if said planned path were followed, and determining a planned deviation being the difference between the planned lateral position at the second instant (t2) with the lateral position at the first instant (t1).
The invention relates to a method for estimating a traffic situation in relation to a vehicle comprising retrieving and storing data representative of the vehicle's state and retrieving and storing data representative of the environment surrounding the vehicle at a first instant (t1), retrieving and storing data representative of the vehicle's state and retrieving and storing data representative of environment surrounding the vehicle during an estimation period ( t TS ) following said first instant (t1), and using the data retrieved during the estimation period ( t TS ) to estimate the traffic situation at the first instant (t1).
Styrsystemen i bruken består av tusentals reglerloopar och det är svårt att få en helhetssyn, och förstå de komplicerade sambanden mellan de olika processtegen. Med de nya verktygen blir det möjligt att analysera strukturen och generera helhetsstrategier för optimal styrning från ved till färdig pappersprodukt.
The PiCCS workshop took place at Luleå University of Technology on 16th and 17th of August 2017. In total 20 researcher and engineers from industry participated in the event.
The main aim of the workshop was to bring together expert in the field of Control Configuration Selection (CCS), which is a sub-field in the research area Automatic Control, to discuss the current state of the art and identify remaining challenges in the field. The identified challenges were formulated as future directions and are summarized in this report, together with an account of the discussion during these two days.
The workshop explored the following topics Implementing optimal operation using simple control elements, Real time optimisation approach in control structure design and benchmarking, Data driven control configuration selection, and Reconfiguration of control structures. Based on the outcome of the discussion, a group of participants proposed an invited session for the 2018 IFAC AdChem Symposium, which has been accepted at the time of the publication of this report and consists of 6 papers addressing challenges discussed during the workshop.
This paper presents a new application software for control conguration selection of interconnected industrial processes,called ProMoVis. Moreover, ProMoVis is able to visualize process models and process layout at the physical leveltogether with the control system dynamics. The software consists of a builder part where the visual representationof the interconnected process is created and an analyzer part where the process is analyzed using dierent controlconguration selection tools.The conceptual idea of the software is presented and the subsequent design and implementation of ProMoVis isdiscussed. The implemented analysis methods are briey described including their usage and implementation aspects.The use of ProMoVis is demonstrated by an application study on the stock preparation process at SCA Obbola AB,Sweden. The results of this study are compared with the currently used control strategy.The study indicates that ProMoVis introduces a systematic and comprehensive way to perform control congurationselection. ProMoVis has been released under the Apache Open Source license.
In this paper two methods for the reconfiguration of multivariable decentralized controllers are evaluated for their feasibility in real life applications. As real-life case the air control system of a waste-to-energy plant in the pulp and paper industry is used. The first method is based on the factorization of the closed loop sensitivity transfer matrix and the second on degeneration factors of the closed loop system. The two candidate methods are evaluated by comparing their results with the results obtained from established interaction measures. Thereafter the reconfiguration of the control system is performed and subsequently re-assessed. The results show that both methods can be used to derive reasonable indications on how controllers can be reconfigured to achieve better performance of the closed loop system. It is also estimated that the performance of the air control system can be improved by 3% when a feed forward link is introduced in the current control structure
In this paper the problem of reconfiguration of controllers in the air control system of a bark boiler is addressed. The air control system of a bark boiler is considered as an interconnected multivariable system and the configuration of the controllers is adapted with the perspective to improve the closed loop performance of the system. The paper proposes a generic procedure for the reconfiguration of controllers using a combination of established theories together with rather recently proposed methods. The procedure is applied to a model of the air flow system, which is derived in this study. The results indicate that a significant performance improvement can be achieved by reconfiguring the control system instead of re-design the process. The improvement is quantified through theoretical assessment, simulation studies, and performance assessment of pilot tests at the bark boiler at SCA Obbola Sweden. It can be concluded that the proposed procedure is both efficient and easy to apply.
An object awareness determination system comprising: - an external object sensor system (10) arranged on a host vehicle (14), said sensor system (10) being arranged to, within a detecting range (16) of said sensor system, sense objects (18) and generate input data relating to objects external to said host vehicle, wherein said input data include an object position (x,y), an object velocity ¦(x ,y )¦ and an object direction of movement ((x ,y )/¦(x ,y )¦) associated with each object in said detecting range (16), characterised in that said object awareness determination system further comprises; a controller (20) for determining awareness of the user to an object (22) that recently has entered the detecting range (16) of the external object sensor system, and a method for determining awareness of an object that recently has entered into a detecting range (16) of the external object sensor system
The increased need for mobility has led to transportation problems like congestion, accidents and pollution. In order to provide safe and efficient transport systems great efforts are currently being put into developing Intelligent Transport Systems (ITS) and cooperative systems. In this paper we extend proposed solutions with autonomous on-road sensors and actuators forming a wireless Road Surface Network (RSN). We present the RSN architecture and design methodology and demonstrate its applicability to queue-end detection. For the use case we discuss the requirements and technological solutions to sensor technology, data processing and communication. In particular the MAC protocol is detailed and its performance assessed through theoretical verification. The RSN architecture is shown to offer a scalable solution, where increased node density offers more precise sensing as well as increased redundancy for safety critical applications. The use-case demonstrates that RSN solutions may be deployed as standalone systems potentially integrated into current and future ITS. RSN may provide both easily deployable and cost effective alternatives to traditional ITS (with a direct impact independent of penetration rate of other ITS infrastructures - i.e., smart vehicles, safe spots etc.) as well as provide fine grain sensory information directly from the road surface to back-end and cooperative systems, thus enabling a wide range of ITS applications beyond current state of the art.
This review aims at assessing the opportunities and challenges of creating and using digital twins for process industrial systems over their life-cycle in the context of estimation and control. The scope is, therefore, to provide a survey on mechanisms to generate models for process industrial systems using machine learning (purely data-driven) and automated equation-based modeling. In particular, we consider learning, validation, and updating of large-scale (i.e., plant-wide or plant-stage but not component-wide) equation-based process models. These aspects are discussed in relation to typical application cases for the digital twins creating value for users both on the operational and planning level for process industrial systems. These application cases are also connected to the needed technologies and the maturity of those as given by the state of the art. Combining all aspects, a way forward to enable the automatic generation and updating of digital twins is proposed, outlining the required research and development activities. The paper is the outcome of the research project AutoTwin-PRE funded by Strategic Innovation Program PiiA within the Swedish Innovation Agency VINNOVA and the academic version of an industry report prior published by PiiA.
This paper discusses a new approach to interactive modeling, visualization and analysis of complex industrial processes. A theoretical framework based on signal flow graphs for modeling and visualization is presented. Using this framework a software tool is designed, called ProMoVis, which can be used to model a process, to visualize the models together with process construction and control system, and to perform analysis regarding e.g. feasible control strategies for the process. Moreover, a case study is conducted, where ProMoVis is used to model, visualize and analyze a stock preparation plant. The results indicate that the proposed methods and tools improve work flows, increase process understanding and simplify decision making on control strategies for complex process.
This paper summarizes the implementation and industrial experiences of a model-based control and gas-leakage detection system in a coal injection plant. It describes how advanced control and monitoring can be implemented in an industrial environment while taking human–machine interface aspects into consideration. The operation of the advanced and the conventional concept are compared regarding evaluation data, experiences and observations of operators and maintenance personnel. It is shown that the advanced control and monitoring system improves plant performance without disturbing routines in plant operation and, moreover, is positively accepted by the plant operators.
This paper deals with design and implementation of a combined model-based control and gas leakage detection system applied to the pulverized coal injection plant at SSAB Tunnplåt AB in Luleå, Sweden. The structure and functions of the in-house control and process monitoring system SafePCI are described. SafePCI is experimentally tested and has successfully completed two weeks test operation. The evaluation of the test operation indicate that combined model-based control and gas leakage detection is a major improvement for control systems in the process industry.
Modeling, control, and gas leakage detection in the coal injection process are discussed. It is shown that by use of model-based methods, the flow and pressure of the coal injection vessel are reliably controlled. With the new control law, the coal mass flow can be used as a control parameter for the blast furnace. High injection rates can be used and more coke substituted, This is expected to yield a cost reduction in the iron production. An experimental comparison of the conventional control unit with the one suggested in this article shows that an improvement of the process efficiency can be reached by other means than increasing the capacity of the plant
Experiences from field tests of a model-based molten metal analysis estimation system for the LD converter process are reported. Experiments have been carried out during a six-months long period on two converters at SSAB Tunnplat AB in Lulea, Sweden. The results achieved prove the viability of the approach taken and indicate its high potential regarding estimation accuracy and robustness. It is also concluded that some further system development is necessary to enable modeling of additives and lance level before the system can be recommended for permanent installation
Experiences from field tests of a model-based molten metal analysis estimation system for the Linz and Donawitz converter process are reported. Experiments have been carried out during a six-month-long period on two converters at SSAB Tunnplat AB, Lulea, Sweden. The achieved results prove viability of the approach taken and indicate its high potential regarding estimation accuracy and robustness. It is also concluded that some further system development is necessary to enable modeling of additives and lance level before the system can be recommended for permanent installation
A novel approach for monitoring and control of the coal powder injection in a blast furnace is presented and discussed. Image analysis of video recordings is used as a means to estimate the instantaneous coal flow. Initial experiments at the blast furnace no 3 of SSAB Tunnplat AB Lulea, Sweden, have been performed and first hand results on modelling and control of a single injection line are given.
A novel approach to monitoring and control of the coal powder injection in a blast furnace is presented and discussed. Image analysis of video recordings is used as a means to estimate the instantaneous coal flow. Initial experiments at blast furnace number 3 of SSAB Tunnplat AB, Lulea, Sweden, are reported and firsthand results on modeling and control of a single injection line are given.
This note deals with recently developed gramian based interaction measures. The measures are used for the choice of measurement/actuator pairs for decentralized control, where the controller remains unspecified. The theoretical background of these measures is clarified and a geometrical interpretation is given. Moreover, a generalization of the Hankel interaction index array to different gramian based system norms is proposed and it is shown that the introduction of weighted gramians makes the criteria more flexible and superior compared to the augmenting with additional filter dynamics. Finally, some examples are given to illustrate the usefulness of the generalized measures.
Deals with model-based pressure and flow control of a fine coal injection vessel for the use of the blast furnace injection process. By means of system modeling and identification, the structure and behavior of the coal injection vessel are analyzed. It is shown that by use of model-based design, the control goals can be reached and the control performance can be significantly improved compared to the conventional PI-controllers. Several dynamic models of the plant are developed. A number of control strategies are presented and compared by means of practical tests. The LQG design method is used to design the controllers. All the controllers are validated through experiments on the coal injection plant at SSAB Tunnplat in Lulea, Sweden
This paper deals with model-based pressure and flow control of a fine coal injection vessel for the use of the blast furnace process. A control system should be in place to maintain a constant coal mass flow from the injection vessel to the blast furnace, since irregularities in the coal mass flow cause significant variations in the hot metal quality. By means of system modeling, the structure and behavior of the coal injection vessel are analyzed. It is shown that by use of a model-based design, the control objectives can be reached and the control performance can be significantly improved compared to the proportional integral (PI) controllers. Alternative control strategies are discussed and compared with the conventional design. The linear quadratic Gaussian (LQG) design method is used to design a multi-input multi-output (MIMO) controller which is validated through experiments on the coal injection plant at SSAB Tunnplat, Lulea, Sweden.
This paper deals with a sensitivity analysis of a linear quadratic optimal multivariable controller for a fine coal injection vessel used in the blast furnace process. The multivariable controller from a previous work is briefly presented and the closed-loop system is studied by means of a sensitivity analysis. Effects of disturbances and uncertainty on the closed-loop system are studied based on analysis of the singular values of the sensitivity and the complementary sensitivity functions, the relative gain array, and the minimized condition numbers. Finally, the sensitivity analysis is validated by the use of logged data from test operation at the coal injection plant at SSAB Tunnplat AB, Lulea, Sweden
This paper deals with a sensitivity analysis of an LQ optimal multivariable controller for a fine coal injection vessel used in the blast furnace process. The multivariable controller from a previous work is briefly presented and the closed loop system is studied by means of a sensitivity analysis. Effects of disturbances and uncertainty on the closed loop system are studied based on analysis of the singular values of the sensitivity and the complementary sensitivity functions, the relative gain array and the minimized condition numbers. Finally, the sensitivity analysis is validated by the use of logged data from test operation at the coal injection plant at SSAB Tunnplat Lulea, Sweden
This paper discusses the design of cooperative road infrastructure systems for infrastructure-based driving support functions. The background of such systems is mapped out and it is shown that there is a need for a cross disciplinary approach. Using an example of a support function, namely the overtaking support, it is shown that such a system is feasible. The different challenges and technological problems that are identified are given and the future work is indicated.
This paper discusses the design and implementation of a cooperative road infrastructure systems, which uses an intelligent road surface. Using an overtaking assist feature as an example it is shown how such a feature can be designed and implemented on a road infrastructure and integrated with drivers and passengers using IMS. The feasibility of this feature is assessed from a functional and communication perspective. Moreover, first results from real-life tests on the Swedish highway E4 are presented which motivate the next research and development steps.
In this deliverable we present a systematic approach towards designing modularized protocols and rank a contribution of their components to the overall system performance. In the nutshell, this approach is based onthree steps: 1.) identifying adjustable parameters in existing protocols, 2.) ranking their influence on the system-level performance metrics and 3.) defining protocol modules exposing the parameters of the highest rank. To this end we present the definition of the components for constructing MAC protocols based on ranking of the impact of adjustable parameters on the overall system performance. We also overview a ranking method for functional blocks of protocols on the routing layer.
Incipient bearing damages on heavy haul vehicles can lead to detrimental disruptions in heavy haul operation and even to derailment of trains. The consequences are damage of the railway infrastructure, loss of freight and equity, and an interruption of traffic. This paper presents a novel method to detect and predict the onset of bearing damages using a combination of multiple way-side detectors. The method is based on a statistical normalization of detector information and subsequent generation of a bearing damage score time series reflecting the abnormal condition of a specific bearing on a rail car. The method is implemented in a cloud-based service solution which reflects each bearing as a digital twin and tracks the condition throughout the operation of a railcar. The solution is applied to a heavy haul operation in Scandinavia to quantify performance of the analytics in terms of true and false positives is currently ongoing.