Linköping Electronic Conference Proceedings
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Nonlinearity analysis of variables for modelling and control
Get PDFNonlinearities become essential in various systems when the operating area widens. The linear models are special cases for narrow areas. The behaviour is often asymmetric and can become gradually steeper or flatter depending on the case. These nonlinear effects can be analysed from data distributions for chosen operating areas. Further extensions require recursive analysis. The widely used Gaussian distribution is seldom valid for a wide area. The variable specific scaling can be presented with two second order polynomial defined by five parameters interpreted as the operating point and four corner points of the feasible range. These parameters define the shape factors which may require adjusting to fill the only requirement that the functions need to be monotonously increasing. Alternative constraints provide good solutions for combining expert knowledge with the data-based analysis. If the nonlinear behaviour is analysed correctly, only linear interactions are needed in the models. As the analysis is based on the same methodology, different applications can be combined by using appropriate process data. The smooth operation and high quality of products is the main goal of all these applications, and this can be achieved by combining these indicators with process control in the same way as it has been one for smaller indicators used in lime kiln control and water treatment. Different parts of the methodology have been tested in versatile applications. The main benefit is that the same structures can be used in various applications since the scaling functions take care of linking to the real world
A Gaussian Mixture Model Approach for Characterizing Playing Styles of Ice Hockey Players
Get PDFPlayer categorization based on playing style is a highly important task in professional ice hockey, aiding scouting, player development, and strategic decision-making. Traditional methods often rely on simple metrics like goals or assists, which fail to capture the full complexity of a player’s style and contributions. Motivated by the increasing availability of detailed event data and advances in machine learning based modeling techniques, this paper explores a richer, data-driven approach to player categorization. We build on recent work in player vector representations and apply Gaussian Mixture Models (GMMs) to cluster forwards and defenders based on event data from five seasons of the Swedish Hockey League (SHL). Our contributions are threefold: (1) we construct detailed player vectors that summarize a wide range of offensive and defensive skills, (2) we apply GMMs to identify soft clusters of players, allowing for nuanced overlapping playing styles, and (3) we analyze the resulting clusters to interpret distinct player profiles and provide concrete examples. Our results offer a more flexible and realistic view of player roles, reflecting the continuous and multi-dimensional nature of playing styles. The approach helps enhance talent evaluation and roster building, and offers an efficient framework for future analyses across leagues and seasons
Sally Jones + the Chief = A Relationship Counteracting Species Boundaries
Get PDFThis study analyses the interspecies relationship between Sally Jones, a gorilla, and her human companion, the Chief, in three novels by Jakob Wegelius, focusing on this dynamic relationship and how it reframes the narrative. The research explores three main questions: the modes of interspecies communication, the core elements of their companionship and how their mutual dependency subverts notions of human supremacy. The theoretical framework integrates perspectives from human-animal studies, including Donovan’s critique of speciesist ideologies that separate human and animal communication (2017), Haraway’s concepts of mutual dependence (2003) and contact zones (2008) in interspecies relations and Derrida's carnofallogocentrism, which interrogates anthropocentric hierarchies (2002). Methodologically, the study employs close reading of the texts paying attention to details in the texts, based on the research questions, theories and previous research, analyzing verbal and non-verbal communication between Sally and the Chief, as well as their interdependent relationship. Findings reveal that their companionship is rooted in mutual respect and understanding, transcending human-animal hierarchies. This relationship critiques notions of human supremacy, as the Chief and Sally navigate their lives as equals, disrupting conventional ideas of ownership and superiority, as well as species and societal boundaries and fostering empathy for ‘the Other’. The study contributes to the broader discourse on interspecies relationships, showing how narratives can shape ethical understandings of human-animal relations and potentially reshape perceptions of human-animal relationships in children’s literature. 
Chemical 2.0 (Free open-source Modelica library)
Get PDFFree open-source Modelica library called Chemical 2.0(https://github.com/MarekMatejak/Chemical) providesexpressions between chemical substances and processes.These robust and unified definitions allow users to choosewhether define processes or substances in their dynamic(electro-)chemical models. Propagation of substancedefinition and chemical solution through connectedcomponents simplify configuration. Chemical pathways canstart even with unknown substances. Chemical kinetics wasrewritten.The possibilities and performance of chemical pathwaysmodeling are increased using a new type of connectors basedon inertial electro-chemical potential. Chemical processescan be directly connected without need to add unsignificantstates. Parameterization of chemical reactions is alsostreamlined, e.g. using forward rate and dissociationcoefficient
Enhancing Collocation-Based Dynamic Optimization through Adaptive Mesh Refinement
Get PDFDirect collocation-based dynamic optimization plays animportant role in the optimization of equation-basedmodels. With this approach, continuous problems aretranscribed into sparse nonlinear programs (NLPs) that canbe solved efficiently. The open-source Modelica environmentOpenModelica provides an implementation using Radau IIAcollocation, but has major limitations, such as the lack ofparameter optimization, no adaptive mesh refinement, and nosupport for higher-order integration schemes. This paperpresents (1) a comprehensive reimplementation thataddresses these limitations and (2) a novel -method meshrefinement algorithm. Implemented in the custom Python /C++ optimization framework GDOPT, the approach demonstratessignificant performance improvements, solving typicalproblems 2 to 3 times faster than OpenModelica underequivalent conditions. Using the proposed mesh refinementalgorithm, the framework correctly identifies non-smoothregions and increases resolution accordingly, requiringonly a small increase in computation time. Theimplementation lays the foundation for a future integrationinto the OpenModelica toolchain
Comparing the Predictive Event Handling Algorithm LookAhead to Rollback and Early Return
Get PDFLookAhead is a lightweight algorithm that improves eventhandling in co-simulation by predicting events andadjusting the communication step size beforehand. Itoperates without requiring subsystem event handlingcapabilities. This paper compares LookAhead with otherevent handling methods, namely Rollback and Early Return,from the perspective of performance and applicability.Results from the presented example show that LookAheadperforms on par with iterative co-simulation methods and isparticularly well-suited for handling shared state events
Enhancing Large-Scale Power Systems Simulations through Functional Mockup Unit-based Grid-Forming Inverter Models
Get PDFNew York State (NYS) faces significant challenges inmeeting the Climate Act’s bold goals of 70% renewableenergy generation by 2030 and total decarbonization of theelectric grid by 2040. Extensive simulations are requiredto assess the impact of numerous inverter-based resources(IBRs) deployed to the large-scale NYS power grid, aimingto evaluate their dynamic behavior and mitigate anynegative interactions with their control schemes. However,the modeling efforts required are huge and thecomputational burden of large-scale simulations isextensive, and often limited by the capabilities of domain-specific tools. This work addresses these limitations bydeveloping a Functional Mockup Unit (FMU) of Grid- Forming(GFM) Inverters for IBR control and integrating them withan electromechanical phasor-domain power system solver. Theproposed FMU facilitates the simulation and parametricstudies needed to analyze large- scale IBR usage withsignificantly improved manual modeling and computationalefforts. The paper details the process of developing andFMU model for GFM IBRs, including all relevant controlloops implemented in the Modelica language and FMUintegrated in OPAL-RT’s ePHASORSIM software. Our FMU modelsare used to successfully deploy and study the impacts of upto 6, 200+ MVA from IBRs on the 5000-bus NYS transmissionsystem
Physics-Based Dynamic Modeling of Solar-Powered Off-Grid Cold Storage for Perishables Using Modelica: A Case Study – Xingalool, Somalia
Get PDFThis paper presents a dynamic, physics-based Modelica modelfor simulating solar-powered, off-grid cold storage systemsused to preserve perishables. A preliminary componentlibrary, developed using the Modelica Standard Library,supports modular modeling of PV-powered chillers, thermalloads, and latent thermal energy storage (LTES), whichmaintains cooling during non-solar hours. The library isapplied to a 200 m³ cold room in Xingalool, Somalia,designed to stay at 5 °C. A case study simulating 500 kg ofcrop loading at 8:00 and unloading at 17:00 demonstratesthe system’s dynamic behavior under realistic solar andambient conditions.** This paper is intended to be presented as a poster
Modelica2Pyomo: a tool to translate Modelica models into Pyomo optimization models
Get PDFTasks involving Modelica models often do not simplyinvestigate the dynamic behavior of a system, but ratherwant to characterize also possible optimal controlstrategies according to suitable criteria. Unfortunately,since Modelica does not support out-of-the-box optimizationfeatures, users are often forced to use other tools tocode again the system model for optimization studies. Forthis reason, the authors present Modelica2Pyomo, anopen-source tool to translate Modelica models into Pyomooptimization programs, leveraging on their flat BaseModelica representation. This work illustrates the mainfeatures of Modelica2Pyomo, including automatic variablesand constraints normalization, expressions manipulation andinitialization via Modelica simulation results. Todemonstrate the capabilities of this framework, twoexamples are showcased, including an industrial relevantopen-loop optimal control problem of a solid-oxide fuelcell
Safe and Efficient Control of a Brayton Cycle Heat Pump Using Reinforcement Learning
Get PDFDecarbonizing industrial process heating will increasinglydepend on high-temperature heat pumps. In particular,Brayton cycle heat pumps, which can reach temperaturesabove 250 °C, are viewed as a promising technology.However, ensuring safe operation and optimal controlremains challenging. This study presents an experimentallyvalidated dynamic model of a Brayton cycle heat pump, asystem with multiple control inputs for regulating itsthermal output. Using this model as a training environment,several control concepts integrating Reinforcement Learning(RL) and traditional PI controllers were implemented toachieve desired heat supply at target temperatures. Domainrandomization was employed to improve the controllerrobustness against model uncertainties in preparation fordeployment on the physical system. The results demonstratethat RL controllers can not only achieve the desiredset-point temperature under varying loads while maintainingrequired safety margins, but also discovered a novel, moreenergy-efficient operational strategy