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Autonomous Framework for Segmenting Robot Trajectories of Manipulation Task
In manipulation tasks, motion trajectories are characterized by a set of key phases (i.e., motion primitives). It is therefore important to learn the motion primitives embedded in such tasks from a complete demonstration. In this paper, we propose a core framework that autonomously segments motion trajectories to support the learning of motion primitives. For this purpose, a set of segmentation po
Simulated Mid-ranging Control of Propofol and Remifentanil using EEG-measured Hypnotic Depth of Anesthesia
This paper suggests an extension of an existing, clinically evaluated, closed-loop drug delivery system for hypnotic depth control using propofol. The extension introduces closed-loop administration of the analgesic drug remifentanil, thus forming a multiple input–single output (MISO) control system. Remifentanil acts and is metabolized at a significantly faster time scale than propofol. Direct co
A Game-Theoretic Resource Manager for RT Applications
The management of resources among competing QoS-aware applications is often solved by a resource manager (RM) that assigns both the resources and the application service levels. However, this approach requires all applications to inform the RM of the available service levels. Then, the RM has to maximize the "overall quality" by comparing service levels of different applications which are not nece
Topics in Machining with Industrial Robot Manipulators and Optimal Motion Control
Two main topics are considered in this thesis: Machining with industrial robot manipulators and optimal motion control of robots and vehicles. The motivation for research on the first subject is the need for flexible and accurate production processes employing industrial robots as their main component. The challenge to overcome here is to achieve high-accuracy machining solutions, in spite of the
Robotic Work-Space Sensing and Control
Industrial robots are traditionally programmed using only the internal joint position sensors, in a sense leaving the robot blind and numb. Using external sensors, such as cameras and force sensors, allows the robot to detect the existence and position of objects in an unstructured environment, and to handle contact situations not possible using only position control. This thesis presents work on
On Robotic Assembly using Contact Force Control and Estimation
Force sensing provides robots the capability to accomplish tasks where physical interaction with the environment is required, such as assembly. Small position uncertainties can then be corrected for by sensing the contact forces. This thesis considers the problem of force-controlled assembly, including how tasks can be specified in a simple and intuitive way and how robust task execution under unc
Treatment of packaging board whitewater in anaerobic/aerobic biokidney
Whitewater from production of packaging board was treated in a combined anaerobic/aerobic biokidney, both in laboratory scale and pilot plant experiments. Both the laboratory experiments and the pilot plant trial demonstrate that a combined anaerobic/aerobic process is suitable for treating whitewater from a packaging mill. It is also possible to operate the process at the prevailing whitewater te
A Dynamic Modelling Framework for Control-based Computing System Design
This manuscript proposes a novel viewpoint on computing systems' modelling. The classical approach is to consider fully functional systems and model them, aiming at closing some external loops to optimise their behaviour. On the contrary, we only model strictly physical phenomena, and realise the rest of the system as a set of controllers. Such an approach permits rigorous assessment of the obtain
On-line schedulability tests for adaptive reservations in fixed priority scheduling
Adaptive reservation is a real-time scheduling technique in which each application is associated a fraction of the computational resource (a reservation) that can be dynamically adapted to the varying requirements of the application by using appropriate feedback control algorithms. An adaptive reservation is typically implemented by using an aperiodic server (e.g. sporadic server) algorithm with f
Parametrized model reduction based on semidefinite programming
A parametrized model in addition to the control and state-space variables depends on time-independent design parameters, which essentially define a family of models. The goal of parametrized model reduction is to approximate this family of models. In this paper, a reduction method for linear time-invariant (LTI) parametrized models is presented, which constitutes the development of a recently prop
Execution time certification for gradient-based optimization in model predictive control
We consider model predictive control (MPC) problems with linear dynamics, polytopic constraints, and quadratic objective. The resulting optimization problem is solved by applying an accelerated gradient method to the dual problem. The focus of this paper is to provide bounds on the number of iterations needed in the algorithm to guarantee a prespecified accuracy of the dual function value and the
pyParticleEst – A Python Framework for Particle Based Estimation
Optimal On-line Sampling Period Assignment: Theory and Experiments
In embedded systems, the computing resources are often scarce and several control tasks may have to share the same computer. In this brief, we assume that a set of feedback controllers should be implemented on a single-CPU platform. We study the problem of optimal sampling period assignment, where the goal is to assign sampling rates to the controllers so that the overall control performance is ma
Performance analysis of operating systems schedulers realised as discrete-time controllers
Recent papers have proposed to design scheduling algorithms entirely as discrete-time controllers, i.e., to refrain from preserving the already installed scheduler, and replace it completely. At the cost of some system re-design impact, this new approach has been proved to yield significant advantages in terms of code size and simplicity, and above all to open the way to a system-theoretical analy
Mobile Manipulation with a Kinematically Redundant Manipulator for a Pick-and-Place Scenario
Mobile robots and robotic manipulators have traditionally been used separately performing different types of tasks. For example, industrial robots have typically been programmed to follow trajectories using position sensors. If combining the two types of robots and adding sensors new possibilities emerge. This enables new applications, but it also raises the question of how to combine the sensors
Automatic Single-View Character Model Reconstruction
Integral Quadratic Constraints
Observer-Based Strictly Positive Real (SPR) Variable Structure Output Feedback Control
This paper considers switching output feedback control of linear systems and variable structure systems. Theory for stability analysis and design for a class of observer-based feedback control systems is presented. A circle-criterion approach can be used to design an observer-based state feedback control which yields a closed-loop system with specified robustness characteristics. The approach is r
Performance Improvement of a Phase Space Detection Algorithm for Electrocardiogram Wave Morphology Classification
An algorithm based on embedding phase space signal was developed by the authors in previous works. The algorithm detects the characteristic points of the waves of a multilead electroacardiogram (ECG). In the present work, the parameters of this algorithm are optimized to improve its performance. The algorithm uses 2 configurable parameters to obtain the phase spacethe dimension of the phase space
