Sökning: "Model-Based Control Optimization"

Visar resultat 1 - 5 av 23 uppsatser innehållade orden Model-Based Control Optimization.

  1. 1. Optimal Gait Control of Soft Quadruped Robot by Model-based Reinforcement Learning

    Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)

    Författare :Niu Xuezhi; [2023]
    Nyckelord :Quadruped Robots; Soft Robotics; Reinforcement Learning; Gait Control; Model-Based Control Optimization; Kvadrupedroboter; Mjukrobotik; Förstärkningsinlärning; Gångkontroll; Optimering av robotkontroll;

    Sammanfattning : Quadruped robots offer distinct advantages in navigating challenging terrains due to their flexible and shock-absorbing characteristics. This flexibility allows them to adapt to uneven surfaces, enhancing their maneuverability. LÄS MER

  3. 2. Control Method for an Automated Forest Machine Based on Deep Reinforcement Learning

    Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)

    Författare :Youchen Sun; [2023]
    Nyckelord :;

    Sammanfattning : An automated forest machine was designed in order to improve the working environment of today’s forest machine operators. In order to realize the autonomous control of the forest machine, model-based methods such as A* and dynamic window were used in previous projects. LÄS MER

  4. 3. On the Equivalence of Time-Varying CBF-Based Control and Prescribed Performance Control : Conversion and Qualitative Comparison

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Ryo Namerikawa; [2023]
    Nyckelord :Control Barrier Function; Invariance control; Nonlinear control; Prescribed Performance Control; Safety-critical system; Icke-linjär reglering; invariansreglering; säkerhetskritiska system; prestandasäkring;

    Sammanfattning : These days, a wide range of autonomous systems, such as automobiles, delivery drones, and embedded household systems, are becoming more and more common in our society. This trend is projected to continue in the future. To effectively manage these dynamic systems, ensuring their safe operation is crucial for the well-being of our lives. LÄS MER

  5. 4. Model-based Residual Policy Learning for Sample Efficient Mobile Network Optimization

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Viktor Eriksson Möllerstedt; [2022]
    Nyckelord :Reinforcement Learning; Sample Efficiency; Model-based; Expert Policy; Remote Electrical Tilt; Telecommunication; Förstärkande inlärning; dataeffektivitet; modell-baserad; expert-policy; fjärrstyrning av antenners nedåtlutning; telekommunikation;

    Sammanfattning : Reinforcement learning is a powerful tool which enables an agent to learn how to control complex systems. However, during the early phases of training, the performance is often poor. LÄS MER

  7. 5. Modelling and Run-Time Control of Localization System for Resource-Constrained Devices

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Albin Mosskull; [2022]
    Nyckelord :Cross-layer optimization; Resource-constrained devices; Automatic hyperparameter tuning; Runtime control; Visual-inertial localization; Korsskiktsoptimering; Resursbegränsade enheter; Automatisk hyperparameterreglering; Körtidsreglering; Visuell-tröghets lokalisering;

    Sammanfattning : As resource-constrained autonomous vehicles are used for more and more applications, their ability to achieve the lowest possible localization error without expending more power than needed is crucial. Despite this, the parameter settings of the localization systems, both for the platform and the application, are often set arbitrarily. LÄS MER