| 1. |
- Birk, Wolfgang, 1968-, et al.
(författare)
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Track Geometry Estimation and Prediction Tool Combining Onboard Monitoring and Measurement Vehicle Data
- 2021
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Ingår i: Proceedings of the AREMA 2021 Virtual Conference. - Lanham, Maryland, USA : American Railway Engineering and Maintenance-of-Way Association (AREMA).
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Konferensbidrag (refereegranskat)abstract
- Infrastructure owners monitor changes in the track geometry to safeguard operation and to plan maintenance activities. Usually, track geometry is monitored using specialized measurement vehicles assessing the track several times a year to establish information on the development of a specific locations along the track. In this paper, a prediction tool is proposed and described that combines information from the measurement vehicles with measurements of onboard monitoring systems on regular trains to estimate and predict the properties longitudinal level and twist. Further, static asset configuration and information on the infrastructure is used in the decision making to provide actionable insights. The tool provides an improved resolution in time for track geometry properties and predictions on how these properties develop in the future including information on the uncertainties.It will be discussed how data from different sources with irregular sampling need to be preprocessed to be combined and harmonized. Moreover, in what way different principles from data science, machine learning and estimation theory can be combined with domain knowledge to enable a better analytics and decision making. To support engineers, it is shown how a decision support tool for maintenance can be tailored and used. Finally, the tool and approach are showcased and benchmarked on track systems in Europe, where both onboard monitoring data and data from measurement trains is available. The results indicate that such a tool provide improved actionable insights to practitioners.
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| 2. |
- Al-Kahwati, Kammal, et al.
(författare)
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Condition Monitoring of Rollers in Belt Conveyor Systems
- 2021
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Ingår i: 2021 5th International Conference on Control and Fault-Tolerant Systems (SysTol). - : IEEE.
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Konferensbidrag (refereegranskat)abstract
- 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.
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| 3. |
- Al-Kahwati, Kammal, et al.
(författare)
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Experiences of a Digital Twin Based Predictive Maintenance Solution for Belt Conveyor Systems
- 2022
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Ingår i: PHME 2022: Proceedings of the 7th European Conference of the Prognostics and Health Management Society 2022. - : PHM Society. ; , s. 1-8
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Konferensbidrag (refereegranskat)abstract
- 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.
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| 4. |
- Birk, Wolfgang, 1968-, et al.
(författare)
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Automatic generation and updating of process industrial digital twins for estimation and control - A review
- 2022
-
Ingår i: Frontiers in Control Engineering. - : Frontiers Media S.A.. - 2673-6268. ; 3
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Forskningsöversikt (refereegranskat)abstract
- 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.
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| 5. |
- Birk, Wolfgang, 1968-, et al.
(författare)
-
Novel Detection And Prediction Tool For Bearing Damages On Heavy Haul Vehicles Using Way-Side Detectors
- 2020
-
Ingår i: AREMA 2020 Virtual Conference & Expo. - Online Conference.
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Konferensbidrag (refereegranskat)abstract
- 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.
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| 6. |
- Birk, Wolfgang, 1968-, et al.
(författare)
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Reinforcement of knowledge acquisition in course chains using student-held seminars
- 2020
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Ingår i: Bidrag från 7:e utvecklingskonferensen för Sveriges ingenjörsutbildningar. - : Luleå tekniska universitet. ; , s. 164-165
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- 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.
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| 7. |
- Groemer, Michael, et al.
(författare)
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Digital Twins : Analyse und Optimierung von Cyber-Physical Systems
- 2020
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Ingår i: 16. Symposium Energieinnovation, 12.-14.02.2020, Graz/Austria. - Graz, Austria : Verlag der Technischen Universität Graz. ; , s. 322-322
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Digital Twins und Cyber-Physikalische Systeme spielen eine wichtige Rolle in zukünftigen intelligenten Systemen wie Industrie 4.0 oder Energiesystemen. Sowohl bei Digital Twins als auch bei Cyber-Physikalischen Systemen sind Modellierung und Simulation zentrale Werkzeuge. Ein Trend in der modellbasierten Analyse und Optimierung ist die zunehmende Komplexität der betrachteten Systeme, wodurch etablierte Methoden an ihre Grenzen stoßen. Des weiteren erfordern viele Anwendungen die Kombination von datengetriebene Techniken mit First-Principle-Modellen. Aktuelle Studien haben gezeigt, dass die Co-Simulation ein vielversprechender Ansatz für die Modellierung und Simulation komplexer Systeme ist. In diesem Paper wird ein physikalisches Modell einer industriellen Energieversorgung und ein datengetriebenes Modell einer Photovoltaikanlage co-simuliert.
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| 8. |
- Jafari, Seyyed Reza, et al.
(författare)
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Adaptive multi-objective control allocation with online actuator selection for over-actuated systems
- 2023
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Ingår i: International Journal of Dynamics and Control. - : Springer Nature. - 2195-268X .- 2195-2698. ; 11:3, s. 1220-1229
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents an adaptive control allocation technique for over-actuated systems. The online actuator selection algorithm is used to select the best group of actuators. Also, a multi-objective cost function is utilized for the allocation unit. The virtual and actual control signals in the control allocation methodologies are linked by the effectiveness matrix. In many practical systems, the elements of the effectiveness matrix may vary due to changing operating conditions, nonlinearities, ageing, disturbances and faults. Hence, an online algorithm for estimation of the entries of the effectiveness matrix is presented in this paper. Estimation of the effectiveness matrix will be used for the proposed adaptive actuator selection strategy, employing the Actuator Effectiveness Index (AEI). The AEI is calculated for all the actuators, and the best group of actuators will be subsequently selected. Finally, simulation results are used to show the effectiveness of the proposed methodology.
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| 9. |
- Lindström, John, et al.
(författare)
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An Initial Model for Zero Defect Manufacturing
- 2020
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Ingår i: Applied Sciences. - Basel, Switzerland : MDPI. - 2076-3417. ; 10:13
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Tidskriftsartikel (refereegranskat)abstract
- This paper investigates an initial model for Zero Defect Manufacturing (ZDM) using a cost function where the operation and condition of a production process are reflected, and the quality of the output/product and the production process (as well as safety aspects) can be considered. The outset of the study is based on empirical data collected from five manufacturing companies, and proposes an initial model for ZDM with an Industry 4.0 perspective. The initial ZDM model has a generic setup for a real-life system and its replication as a digital twin using system models based on a representation of a generic production process with its connected control system, and potential interconnections between unit processes. It is based on concepts from system theory of dynamic systems and principles from condition monitoring and fault detection. In that way the model is deemed as highly generalizable for manufacturing and process industry companies as well as for some critical infrastructures with production and distribution systems. The proposed model with its cost function setup is analyzed and discussed in the context of ZDM. It is concluded that production processes in the manufacturing and process industry can be made more intelligent and interoperable using this approach. Improved sustainability, competitiveness, efficiency and profitability of companies are foreseen welcomed secondary effects. Finally, the proposed ZDM model further develops the ZDM by adding to it a systematic approach based on a solid mathematical foundation.
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| 10. |
- Lindström, John, et al.
(författare)
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Zero Defect Manufacturing in an Industry 4.0 Context : A Case Study of Requirements for Change and Desired Effects
- 2020
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Ingår i: TESConf 2020 - 9th International Conference on Through-life Engineering Services. - : Elsevier BV.
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Konferensbidrag (refereegranskat)abstract
- The paper addresses, based on a case study comprising six process- and manufacturing industry companies, requirements for change and desired effects from Zero Defect Manufacturing in an Industry 4.0 context. The results outline seven problems and five needs perceived by the companies. Further, the results also outline four desired effects. The results are aligned with existing literature and studies but also bring up new aspects of Zero Defect Manufacturing in terms of problems, needs and desired effects. Noteworthy new desired effects are increased trust for the production process and improved gender equality.
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| 11. |
- Lucchese, Riccardo, et al.
(författare)
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Computing the allowable uncertainty of sparse control configurations
- 2020
-
Ingår i: Journal of Process Control. - : Elsevier. - 0959-1524 .- 1873-2771. ; 87, s. 108-119
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Tidskriftsartikel (refereegranskat)abstract
- Given a generic Control Configuration Selection (CCS) protocol and a plant uncertainty description isomorph to a unit ball in a finite-dimensional Lp space, we search for the largest perturbation radius for which the nominal configuration remains the preferred one. To this aim, we develop a randomized search algorithm based on sampling the uncertain plants and characterize its statistical performance. By adopting an intuitive accuracy measure that relates to the volume of points in which the preferred configuration differs from the nominal one, we devise a generally applicable strategy that allows for arbitrarily accurate estimates, in a specific probabilistic sense, depending on the number of uncertain plants that are sampled. We benchmark the proposed algorithm using examples from the literature and in a data center flow provisioning problem. In the latter setting, we identify the uncertainty description with the space of controls and sample the “uncertain” plants from an underlying nonlinear model.
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| 12. |
- Lucchese, Riccardo, et al.
(författare)
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On Economic Cooling of Contained Server Racks using an Indirect Adiabatic Air Handler
- 2020
-
Ingår i: Thirty Sixth Annual Semiconductor Thermal Measurment, Modeling and Management Symposium. - : IEEE. ; , s. 24-31
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Konferensbidrag (refereegranskat)abstract
- We study the economic operation of a free-cooling setup in which an Indirect Adiabatic Air Handler (IAAH) recovers heat from an array of server racks placed in a contained aisle. For this setting we propose two different control policies: in the first approach, the airflow supply rate to the racks is maintained constant while only the process- side operations of the IAAH are optimized. In the second approach, also the room-side rate is updated adaptively. Building on calibrated models of the IAAH and the servers, we design experimental trials considering different outdoor temperatures and humidity conditions as well as varying computational workloads. The in silico analysis contributes actionable insights on the optimal thermal and cost operations of the system.
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| 13. |
- Moaveni, Bijan, et al.
(författare)
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An Improved Gramian-based Interaction Measure for Time-Delay Systems
- 2020
-
Ingår i: Proceedings of the IFAC World Congress 2020. - : Elsevier. ; , s. 11735-11739
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Konferensbidrag (refereegranskat)abstract
- In this paper, a modified Gramian based control configuration selection (CCS) method for linear multi-input multi-output (MIMO) plants with time delays in input-output channels is proposed. In contrast to the typical approach of approximating the delayed system, the time delay is directly integrated in the method by using the finite-time H2 norm for the time- delay system (TDS). The methodology is based on an explicit formula for computing the finite-time H2 norm for stable SISO systems. Gramian-based CCS methods are either insensitive to time delays or favor channels with large delays, while the proposed method suggests configuration which are more reasonable. A numerical examples is used to discuss and benchmark the method. It is concluded that the proposed methods provides adequate configuration suggestions and circumvents a well-known shortcoming.
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| 14. |
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| 15. |
- Schweiger, G., et al.
(författare)
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Modeling and simulation of large-scale systems : A systematic comparison of modeling paradigms
- 2020
-
Ingår i: Applied Mathematics and Computation. - : Elsevier BV. - 0096-3003 .- 1873-5649. ; 365
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Tidskriftsartikel (refereegranskat)abstract
- A trend across most areas where simulation-driven development is used is the ever increasing size and complexity of the systems under consideration, pushing established methods of modeling and simulation towards their limits. This paper complements existing surveys on large-scale modeling and simulation of physical systems by conducting expert surveys. We conducted a two-stage empirical survey in order to investigate research needs, current challenges as well as promising modeling and simulation paradigms. Furthermore, we applied the analytic hierarchy process method to prioritise the strengths and weakness of different modeling paradigms. The results of this study show that experts consider acausal modeling techniques to be suitable for modeling large scale systems, while causal techniques are considered less suitable.
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| 16. |
- Simonsson, Johan, et al.
(författare)
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A Graph Theoretical Approach to Modeling of District Energy Networks
- 2024
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Ingår i: IEEE Transactions on Control Systems Technology. - : IEEE. - 1063-6536 .- 1558-0865.
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Tidskriftsartikel (refereegranskat)abstract
- Simulation of thermal dynamics in city-scale district energy grids often becomes computationally prohibitive for long simulation runs. Most current model order reduction methods offer limited interpretability with regards to the nonreduced system and are not in general applicable for varying flow rates, multiple producers, or changing flow directions. This article presents a graph perspective on modeling of district energy networks. Based on spectral graph theory, a novel method for model order reduction of district energy systems is proposed. The method approximates the solution of an optimization problem, minimizing the coefficients of the local truncation error for the advection equation. Furthermore, a method for calculating the intracluster temperature distribution is presented. It is shown that the method can be used to reduce the thermal dynamic model of a city-scale energy grid, resulting in a coarser temporal and spatial resolution, with a significant decrease in simulation time. The relative root-mean-square error (rRMSE) was 2.5% for the temperature in the evaluation scenario, comparing the reduced-order system with the nonreduced system at the instances of the coarser time step.
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| 17. |
- Simonsson, Johan, 1980-, et al.
(författare)
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A latent variable approach to heat load prediction in thermal grids
- 2020
-
Ingår i: European Control Conference 2020. - : IEEE. - 9781728188133 - 9783907144022 ; , s. 344-349
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Konferensbidrag (refereegranskat)abstract
- In this paper a new method for heat load prediction in district energy systems is proposed. The method uses a nominal model for the prediction of the outdoor temperature dependent space heating load, and a data driven latent variable model to predict the time dependent residual heat load. The residual heat load arises mainly from time dependent operation of space heating and ventilation, and domestic hot water production. The resulting model is recursively updated on the basis of a hyper-parameter free implementation that results in a parsimonious model allowing for high computational performance. The approach is applied to a single multi-dwelling building in Luleå, Sweden, predicting the heat load using a relatively small number of model parameters and easily obtained measurements. The results are compared with predictions using an artificial neural network, showing that the proposed method achieves better prediction accuracy for the validation case. Additionally, the proposed methods exhibits explainable behavior through the use of an interpretable physical model.
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| 18. |
- Simonsson, Johan, et al.
(författare)
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Experiences from City-Scale Simulation of Thermal Grids
- 2021
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Ingår i: Resources. - : MDPI. - 2079-9276. ; 10:2
-
Tidskriftsartikel (refereegranskat)abstract
- Dynamic simulation of district heating and cooling networks has an increased importance in the transition towards renewable energy sources and lower temperature district heating grids, as both temporal and spatial behavior need to be considered. Even though much research and development has been performed in the field, there are several pitfalls and challenges towards dynamic district heating and cooling simulation for everyday use. This article presents the experiences from developing and working with a city-scale simulator of a district heating grid located in Luleå, Sweden. The grid model in the case study is a physics based white-box model, while consumer models are either data-driven black-box or gray-box models. The control system and operator models replicate the manual and automatic operation of the combined heat and power plant. Using the functional mock-up interface standard, a co-simulation environment integrates all the models. Further, the validation of the simulator is discussed. Lessons learned from the project are presented along with future research directions, corresponding to identified gaps and challenges.
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| 19. |
- Simonsson, Johan
(författare)
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On Efficient Modeling, Simulation and Control of District Energy Systems
- 2024
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Sustainable energy systems rely on a wide range of energy sources, where an integral part is to use the available energy as efficiently as possible. District energy systems are considered a key factor towards decarbonization as an efficient way of distributing heat and cold within urban areas and facilitating the utilization of renewable energy sources and heat recovery from, e.g., industrial plants and data centers.A dynamic model of the process can be used to achieve high-performing control and an increased understanding of the district energy system. However, a city-scale, automatically generated, and updated model that can be used for the plant's whole lifecycle remains a distant vision. Large-scale physics-based models are sometimes used for planning and validation, but using the same models for optimization and control, long-term simulation, or running a high number of simulation scenarios can be computationally prohibitive or impossible due to a lack of applicable methods. In the thesis, the physics of the district energy grid is presented along with modeling, simulation, and control methods, towards the goal of increasing the computational efficiency and flexibility of the models and methods. The grid is described using graph theoretical concepts and a linear parameter-varying state-space model representation, followed by an introduction to reduced-order models, heat load prediction, Gaussian process models, and feedback control with dead-time compensation for temperature control in district energy systems. The main contributions are the six research papers composing the thesis. Experiences, challenges, and possible methods to address the presented problems are summarized in the first paper of the thesis. In the second paper, a method for the prediction of heat load for buildings is presented, followed by a paper on a machine learning-based method for modeling of the thermal dynamics in a district heating pipe. In the following paper, a method for reduced order modeling of district energy grids using graph theoretical methods and spectral clustering is presented. The fifth paper suggests an integrated approach to spatial and energy planning using an optimization-based tool, and the final paper presents a method for decentralized temperature control in district heating networks using dead time compensation. Based on the work in the thesis, conclusions are finally given.
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| 20. |
- Simonsson, Johan, et al.
(författare)
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Probabilistic Modeling of Thermal Grids using Gaussian Processes
- 2020
-
Ingår i: 2020 59th IEEE Conference on Decision and Control (CDC). - : IEEE. ; , s. 36-41
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Konferensbidrag (refereegranskat)abstract
- Dynamic physics based modeling of district heating networks has gained importance due to an increased use of renewable energy sources and a transition towards lower temperature district heating networks. The modeling is enhanced by technologies for automatic model generation and co-simulation. These models are in general not suitable for automatic control and optimization methods, due to the complexity of the model. Moreover, there is no notion of uncertainty in the models, something that can be of importance for decision making, and that can be explicitly accounted for in e.g Bayesian Optimization and Stochastic Nonlinear Model Predictive Control. In this paper a data driven Gaussian process model for the thermal dynamics of the district heating grid is proposed, with a kernel derived using known physics and numerical methods. The model is trained and validated on a realistic first principle simulation model of a district heating pipe. Results show a good correspondence with the output from the training model on a validation dataset, providing explicit propagation of the input uncertainties. It is suggested that the method can be scaled up to larger parts of the grid for use in advanced control and optimization methods.
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| 21. |
- Simonsson, Johan, et al.
(författare)
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Reduced-Order Modeling of Thermal Dynamics in District Energy Networks using Spectral Clustering
- 2022
-
Ingår i: 2022 IEEE Conference on Control Technology and Applications (CCTA). - : IEEE. - 9781665473385 ; , s. 144-150
-
Konferensbidrag (refereegranskat)abstract
- Simulation of thermal dynamics in city-scale district energy grids often becomes computationally prohibitive for long simulation runs. Current model order reduction methods offer limited interpretability with regards to the nonreduced system, and are not in general applicable for e.g., varying flow rates, multiple producers, or changing flow directions. This article presents a novel method based on graph theory that approximates the solution of an optimization problem that minimizes the local truncation error for heat transport in the grid. It is shown that the method can be used to reduce the thermal dynamic model of a city-scale energy grid, resulting in a coarser temporal and spatial resolution. The relative root mean square error was 2.3 % for the temperature in the evaluation scenario, comparing the reduced-order system with the nonreduced system at the instances of the coarser time-step.
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| 22. |
- Simonsson, Johan
(författare)
-
Towards efficient modeling and simulation of district energy systems
- 2021
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Dynamic simulation of district energy systems has an increased importance in the transition towards renewable energy sources, lower temperature district heating grids and waste heat recovery from industrial plants and data centers. However, a city-scale, automatically generated and updated simulator that can be used for the whole lifecycle of the plant remains a distant vision. Physics based models are often used for planning and validation, but the complexity is too high to use the models for optimization and automatic control, or for longer time spans.In this thesis, the experiences and challenges from previous district heating simulation projects using a co-simulation approach are summarized, with corresponding research gaps and proposed research directions. Two of the identified shortcomings are investigated in more detail in the thesis: First, a robust and computationally efficient method for prediction of the heat load for buildings is proposed. A deterministic dynamic model is used to predict the space heating load, and a latent variable model using Fourier basis functions predicts the heat load used for e.g. hot tap water and ventilation. The prediction model validity is shown on a multi-dwelling building located in Luleå, Sweden. Second, a probabilistic model based on Gaussian Processes is used to simulate the temperature dynamics of a district heating pipe. The model is trained and validated against a state-of-the-art physics based pipe model. It is shown that the model both replicates the behavior of the reference model, and that it can account for uncertainty of the inputs. By employing a kernel exploiting the underlying physics, many shortcomings of Gaussian Process models can be mitigated. The results suggest that a mix of physics based and probabilistic methods can be one way forward towards a digital twin of a city-scale district energy system. Natural extensions to the published papers would be to research how the methods can be applied to a larger scale district energy system.
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| 23. |
- Yang, Shuanghua, et al.
(författare)
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A new controllability index based on Hankel singular value
- 2020
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Ingår i: 21th IFAC World Congress. - : Elsevier. ; , s. 4662-4667
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Konferensbidrag (refereegranskat)abstract
- This paper proposes a new controllability index based on the Hankel singular values (HSV) which is applicable for both single-input single-output (SISO) and multivariable processes. The new index quantifies the inherent performance limitation in terms of closed-loop response speed by associating it with the control effort, which is directly related to the inverse of the HSVs. It is also shown that for specific system there is a direct linear relationship between the inverse of the minimum Hankel singular value and desired closed loop pole locations. The controllability index is thereafter exemplified on several SISO examples systems to show some of its properties. Thereafter two well-known multivariable benchmark processes, quadruple tank and two-continuous-stirring-tank-reactor are used to show the effectiveness of the index. It is concluded that the index provides valuable insights to practitioners on the achievable performance of processes with actuator constraints, while being easy to use and requiring little computational effort.
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| 24. |
- Zaman, Amirreza, 1994-, et al.
(författare)
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Adaptive Decoupling of Multivariable Systems Using Extremum-Seeking Approach
- 2021
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Ingår i: 2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA). - : IEEE. ; , s. 01-07
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Konferensbidrag (refereegranskat)abstract
- Decentralized control of MIMO system is still the dominating control strategy in industry for its ease in design and maintenance, despite its known shortcomings in performance. In this article, an online decoupling scheme of MIMO processes using an extremum-seeking approach is proposed. By applying the developed method, at first, the system's loop interactions are estimated in real-time using phasor extremum seeking, and then, a pre-compensator matrix is calculated and augmented to the process by minimizing the loop interactions. The presented online decoupling approach is a model-free method, and only the plant's inputs and outputs are analyzed to provide the decentralized control protocol. Numerical results provide the effectiveness of the developed method for a two-input, two-output (TITO) control system.
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| 25. |
- Zaman, Amirreza, 1994-, et al.
(författare)
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Online estimation of PID controllers and plant dynamics via multi‐recursive least squares estimation from closed‐loop I/O data
- 2024
-
Ingår i: IET Control Theory & Applications. - : John Wiley & Sons. - 1751-8644 .- 1751-8652. ; 18:6, s. 688-709
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Tidskriftsartikel (refereegranskat)abstract
- This article proposes an online solution to address the problem of closed-loop system identification using multiple recursive least squares estimation protocols. Some control systems cannot be analysed in an open-loop form for stability reasons or the requirement for online control system operation. So, it is necessary to identify plant dynamics and controller parameters based on input–output data from the feedback structure. The presented method identifies real-time parameters of plant dynamics and controller parameters by utilising a series of recursive least square estimation algorithms that estimate open-loop data from noisy input–output data measured from the closed-loop feedback structure. The proposed method can effectively identify abrupt variations in both the controller parameters and plant dynamics. This capability makes it valuable for deployment as a supervisory component, enabling the detection of any faults that may arise in operating systems. Mathematical formulations and theorems are developed, and two numerical case studies are presented to examine the feasibility and performance of the presented closed-loop system identification protocol.
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| 26. |
- Zaman, Amirreza, 1994-, et al.
(författare)
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Security Analysis and Fault Detection Against Stealthy Replay Attacks
- 2022
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Ingår i: International Journal of Control. - : Taylor & Francis. - 0020-7179 .- 1366-5820. ; 95:6, s. 1562-1575
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Tidskriftsartikel (refereegranskat)abstract
- This paper investigates the security issue of the data replay attacks on the control systems. The attacker is assumed to interfere with the control system’s process in a steady-state case. The problem is presented as the standard way to attack, which is storing measurements and replaying them in further times to the system. The controller is assumed to be the LQG controller. The main novelty in this paper can be stated as proposing a different attack detection criterion by using the Kullback-Leibler (K-L) divergence method to cover more general control system problems with these attacks and with higher-order dynamics. Also, there exists a packet-dropout feature in transmitting the data as another contribution of the paper. Formulations and numerical simulations prove the effectiveness of the newly proposed attack detection procedure by having a quick response to occurred attacks with various values of the considered packet-dropout coefficient. Although, in previous approaches, the trade-off between attack detection delay or LQG the performance was significant, in this approach it is proved that the difference in this trade-off is not considered in early moments when the attack happens since the attack detection rate is rapid and thus, these attacks can be stopped with defense strategies in the first moments with the proposed attack detection criterion.
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- Zaman, Amirreza, 1994-
(författare)
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Towards the Development of Efficient Cooling Control Strategies for Edge Data Centers
- 2024
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Data centers, including edge data centers strategically positioned for critical applications, constitute vital components of today's technological infrastructure. Traditional data centers serve as centralized hubs supporting services like cloud computing, while edge centers, located nearer to end-users, play a pivotal role in applications such as augmented and virtual reality. These centers collectively ensure the efficient operation of digital services, providing necessary computing resources and minimizing delays for an optimal user experience. Addressing the dynamic challenges of these environments, effective cooling control strategies are imperative to mitigate energy consumption and optimize performance. Inadequate cooling not only impacts equipment functionality but also results in energy wastage, emphasizing the importance of tailored approaches to meet the dynamic demands of data center operations.The challenges in data center cooling, stemming from the dynamic workload and evolving computing demands, underscore the significance of developing model-based cooling control strategies. Traditional cooling methods may struggle to adapt, causing ineffective temperature regulation and potential hotspots. Intelligent cooling control strategies, rooted in models that dynamically adjust cooling resources based on real-time data and workload fluctuations, offer a solution. These model-based strategies enhance cooling efficiency, ensuring consistent temperature regulation while minimizing energy consumption. This approach becomes pivotal in supporting the sustainability and cost-effectiveness of data center operations amidst increasing computational demands.This licentiate thesis comprises three results that lead to solving the model-based data centers cooling controlproblems. The first result involves adaptive decoupling of multivariable systems,utilizing the extremum-seeking approach to dynamically adjust cooling resources based on real-time data, ensuring optimal efficiency. The second result focuses on online estimation of PID controllers and plant dynamics, enhancing precision and effectiveness through real-time adaptation to changing conditions within the dynamic landscape ofdata centers. The third result specifically applies empirical transfer function estimation for model fitting in a data center cooling model. These results provide guidance and insights to address cooling control design challenges that will be the future focus of this research.
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