Over the past decades, congestion and emission problems has increased remarkablywhich escalates the demands on vehicles. The advancements withinthe eld of information and communication systems gives the opportunity todeal with the aforementioned problems. The concept of platooning shows tobe an attractive way of reducing both congestion and emissions by having ashort inter-vehicle spacing. The ndings in studies show that fuel reductionpotentials of 5-20 % are viable as a result of the lowered air drag by drivingin platoon. This thesis investigates the state of the art within the areaof intelligent transport systems (ITS) along with advanced driver assistancesystems (ADAS). Furthermore, the prosecuted work results in a proposedcontrol design for a longitudinal control in a platoon of vehicles. The platoonconsists of two homogeneous radio controlled vehicles (RCV) which aremodelled by taking advantage of system identication methods. The identi-ed plant models are implemented into a Simulink model where the controlsystem is developed. Moreover, the developed control system is implementedinto a real-time demonstrator for experimental evaluation. The results showsthat the modelled dynamics corresponds reasonably well with the real dynamicsof the system. The developed control system proves to work well andagree with the expectations of its performance obtained from simulations.The performance of the proposed controller has been evaluated by means ofsimulations and real experiments. The resulting control system consists ofPID controllers for both speed and spacing control. / Under de senaste decennierna har mangden trakstockningar och problemmed utslapp okat - darmed aven kraven pa vara fordon. Samtidigt skaparframstegen inom informations- och kommunikationssystem mojligheter foratt hantera ovannamnda problem. Kolonnkorning, eller platooning har visatsig vara en eektiv metod for att minska saval trakstockningar som utslappsom en foljd av kortare avstand mellan fordon. Resultat fran studier visarhur en branslereduktion runt 5-20 % ar mojlig till foljd av det sankta luftmotstandet vid kolonnkorning. Avhandlingen undersoker teknikens standpunktinom intelligenta transportsystem (ITS) tillsammans med avancerade drivhjalpsystem(ADAS). Vidare resulterar arbetet i ett forslag till regleringsdesignfor en longitudinell kontroll i en kolonn av fordon. Kolonnen bestar av tvahomogena radiostyrda fordon (RCV) som modelleras genom att utnyttjametoder for systemidentiering. De identierade systemmodellerna implementerasi en Simulink-modell dar styrsystemet utvecklas. Dessutom implementerasdet utvecklade styrsystemet i en realtids-demonstration for experimentellutvardering. Resultaten visar att den modellerade dynamikenstammer bra overens med systemets verkliga dynamik. Det utvecklade styrsystemetvisar sig fungera bra och overensstammer med forvantningarna pa dessprestanda som erhallits genom simuleringar. Den foreslagna regulatorns prestandahar utvarderats med hjalp av simuleringar och verkliga experiment.Det resulterande styrsystemet bestar av PID regulatorer for bade hastighetsochavstandskontroll.

<p dir="ltr">To establish a long-term human presence on the Moon, it is necessary to have habitat systems that function effectively under challenging conditions and have sufficient autonomous technologies for fault detection and intervention. However, evaluating these habitats presents challenges due to their pervasive interdependencies and the harsh environmental conditions they must withstand. Thus, innovative testing techniques are vital to understanding and capturing the complexities these systems will encounter. </p><p dir="ltr">Thermomechanical real-time hybrid simulation (RTHS) provides unique opportunities to observe realistic behaviors and interdependencies, train models, test ideas, and validate methods. It is a cost-effective and accessible cyber-physical testing method that allows for the simultaneous experimental and computational modeling of systems, offering a comprehensive observation of their behavior under extreme dynamic conditions. This dissertation presents the development and experimental validation of a novel thermomechanical RTHS method to assess the multi-physics response of lunar habitat systems due to disruptive events. It outlines the conceptual framework, modeling approaches, and experimental considerations crucial to establishing the two-way coupling between a numerical and a physical subsystem through an innovative thermal transfer system. </p><p dir="ltr">The thermal transfer system utilizes a thermal actuator to impose distributed thermal loads on the experimental subsystem. The thermal actuator is identified considering switching-mode continuous dynamics for cooling and heating conditions. A switching control system is then developed to experimentally enforce the desired thermal conditions across different thermal cycles with minimum tracking error, adjusting the gains of the controller in response to varying temperature conditions. Furthermore, this dissertation demonstrates how to establish control and performance requirements for RTHS methods to effectively evaluate the realization of interface boundary conditions and determine acceptance criteria to perform RTHS tests with high confidence. </p><p dir="ltr">The RTHS method is experimentally implemented and validated through a series of scenario tests that simulate the cascading thermomechanical effects on a lunar habitat after a micrometeorite impact that damages its structural protective layer. These realistic tests aim to evaluate fault detection and decision-making methods in response to such disruptive events. Thus, using switching dynamic modeling, the RTHS problem formulation is designed to have numerical damage and repair capabilities, allowing interaction with these fault detection and intervention methods. The scenario results obtained through thermomechanical RTHS reveal behaviors and interactions that are not captured through purely numerical simulation or traditional experimental approaches. Through the experimental implementation of these scenario case studies, the thermomechanical RTHS method developed is the first of its kind to experimentally execute the effects of damage and repair intervention strategies in real-time on a numerical subsystem while simultaneously imposing the cascading effects on a physical specimen. </p><p dir="ltr">The findings of this dissertation advance our knowledge and offer insights into developing cost-effective and accessible cyber-physical methods to test novel ideas and technologies, thereby empowering and supporting space resilience and autonomy research. </p>

Cieľom práce je aplikácia lokálnych aproximátorov pre riadenie reálnych mechatronických sústav pomocou metódy dopredného riadenia predstavujúcej zaujímavú alternatívu k metódam využívajúcim globálne aproximátory. Po ukážkových príkladoch funkcie lokálnych aproximátorov bol navrhnutý algoritmus implementovaný pre riadenie dvoch sústav, elektronickej škrtiacej klapky a výukového modelu magnetickej levitácie, predstavujúcich vysoko nelineárne a nestabilné sústavy. Skúmali sme, či riadiaci algoritmus bude mať pozitívny vplyv na presnosť regulácie, ďalej bola skúmaná jeho schopnosť prispôsobiť sa zmene parametrov sústavy a tiež prípadná možnosť jeho implementácie pre mikrokontrolér znížením vzorkovacej frekvencie. Výsledky ukázali, že riadenie založené na lokálnych modeloch zlepšilo riadenie v porovnaní s jednoduchým PID regulátorom a že má schopnosť adaptability. Veľmi výhodné sa zdá byť jeho použitie pre zariadenia umožnujúce vzorkovaciu frekvenciu do 1 kHz.

Today the majority of the driver assistance systems are rule-basedcontrol systems that help the driver control the truck. But driversare looking for something more personal and exible that can controlthe truck in a human way with their own preferences. Machine learningand articial intelligence can help achieve this aim. In this studyArticial Neural Networks are used to model the driver steering behaviourin the Scania Lane Keeping Assist. Based on this, trajectoryplanning and steering wheel torque response are modelled to t thedriver preference. A model predictive controller can be used to maintainstate limitations and to weigh the two modelled driver preferencestogether. Due to the diculties in obtaining an internal plant modelfor the model predictive controller a variant of a PI-controller is addedfor integral action instead. The articial neural network also containsan online learning feature to further customize the t to the driverpreference over time. / Idag används till största del regelbaserade reglersystem förförarassistanssystem i lastbilar. Men lastbilschaufförer vill ha någotmer personligt och flexibelt, som kan styra lastbilen på ett mänskligtsätt med förarens egna preferenser. Maskininlärning och artificiell intelligenskan hjälpa till för att uppnå detta mål. I denna studie användsartificiella neurala nätverk för att modellera förarens styrbeteende genomScania Lane Keeping Assist. Med användning av detta modellerasförarens preferenser med avseende på placering på vägbanan och momentpåslag på ratten. En modell prediktiv kontroller kan användas föratt begränsa tillstånd och för att väga de två modellerade preferensernamot varann. Eftersom det var mycket svårt att ta fram den internaprocessmodellen som krävdes för regulatorn används istället en variantav en PI-kontroller för att styra lastbilen. De artificiella neuralanätverken kan också tillåtas att lära sig under körning för att anpassasig till förarens preferenser över tid.