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Sub-Optimality Bound on a Gradient Method for Iterative Distributed Control Synthesis
A previous paper introduced an online gradient method to iteratively update local controllers for improved performance. In this paper we modify that method to get an offline method for distributed control synthesis. The complexity of the method is linear in the number of neighbors to each agent. Since the controllers are constructed to be distributed and the method is an iterative scheme, the con
Back to the Past: Screenings of Swedish Films in the Swedish-American Community until 1950
Java Simulations of Embedded Control Systems
This paper introduces a new Open Source Java library suited for the simulation of embedded control systems. The library is based on the ideas and architecture of TrueTime, a toolbox of Matlab devoted to this topic, and allows Java programmers to simulate the performance of control processes which run in a real time environment. Such simulations can improve considerably the learning and design of m
Control-Based Load-Balancing Techniques: Analysis and Performance Evaluation via a Randomized Optimization Approach
Cloud applications are often subject to unexpected events like flashcrowds and hardware failures. Users that expect a predictable behavior may abandon an unresponsive application when these events occur. Researchers and engineers addressed this problem on two separate fronts: first, they introduced replicas - copies of the application with the same functionality - for redundancy and scalability; s
Infrastructure at Automatic Control
Virtual Machine Migration in Cloud Infrastructures: Problem Formalization and Policies Proposal
Cloud computing has dramatically simplified the deployment of new software and, indeed, the number of applications that are hosted by cloud providers every day is increasing. The data center owner should provide computing capacity to a set of customers, each of them powering up and down virtual machines dynamically, to handle variations in the incoming requests. Cloud providers, however, should al
Iterative Learning Control for Machining with Industrial Robots
We consider an iterative learning control (ILC) approach to machining with industrial robots. The robot and the milling process are modeled using system identification methods with a data-driven approach. Two different model-based ILC algorithms are proposed and subsequently experimentally verified in a milling scenario. The difference between the two approaches is the required sensors for acquiri
Towards Lane-Keeping Electronic Stability Control for Road-Vehicles
The emerging new idea of lane-keeping electronic stability control is investigated. In a critical situation, such as entering a road curve at excessive speed, the optimal behavior may differ from the behavior of traditional ESC, for example, by prioritizing braking over steering response. The important question that naturally arises is if this has a significant effect on safety. The main contribut
Studying the Influence of Roll and Pitch Dynamics in Optimal Road-Vehicle Maneuvers
A comparative analysis shows how vehicle motion models of different complexity, capturing various characteristics, influence the solution when used in time-critical optimal maneuvering problems. Vehicle models with combinations of roll and pitch dynamics as well as load transfer are considered, ranging from a single-track model to a double-track model with roll and pitch dynamics combined with loa
Modeling and Control of a Piezo-Actuated High-Dynamic Compensation Mechanism for Industrial Robots
This paper presents a method for modeling and control of a piezo-actuated high-dynamic compensation mechanism (HDCM) for usage together with an industrial robot during a machining operation, such as milling in aluminum. The spindle is attached to the compensation mechanism and the robot holds the workpiece. Due to the inherent resonant character of mechanical constructions of this type, and the no
Optimal Tracking and Identification of Paths for Industrial Robots
This paper presents results from time-optimal path tracking for industrial robots. More specifically, three subproblems are studied and experimentally evaluated. The first is a contact-force control approach for determining the geometric robot motion, such that the tool centre point of the robot is moved according to the specification. The second problem is off-line solution of the optimisation pr
Modeling and Control of Server-based Systems
When deploying networked computing-based applications, proper resource management of the server-side resources is essential for maintaining quality of service and cost efficiency. The work presented in this thesis is based on six papers, all investigating problems that relate to resource management of server-based systems. Using a queueing system approach we model the performance of a database sys
Control Strategies for Improving Cloud Service Robustness
This thesis addresses challenges in increasing the robustness of cloud-deployed applications and services to unexpected events and dynamic workloads. Without precautions, hardware failures and unpredictable large traffic variations can quickly degrade the performance of an application due to mismatch between provisioned resources and capacity needs. Similarly, disasters, such as power outages and
On optimal low-rank approximation of non-negative matrices
For low-rank Frobenius-norm approximations of matrices with non-negative entries, it is shown that the Lagrange dual is computable by semi-definite programming. Under certain assumptions the duality gap is zero. Even when the duality gap is non-zero, several new insights are provided.
Pictorial Human Spaces : A Computational Study on the Human Perception of 3D Articulated Poses
Human motion analysis in images and video, with its deeply inter-related 2D and 3D inference components, is a central computer vision problem. Yet, there are no studies that reveal how humans perceive other people in images and how accurate they are. In this paper we aim to unveil some of the processing—as well as the levels of accuracy—involved in the 3D perception of people from images by assess
On Scalable H-infinity Control
Many of the classical approaches to controller synthesis do not scale well for large and complex systems. This is mainly due to computational complexity and the lack of distributed structure in the resulting controllers. It is important that limitations on the information given and processed by sensors and actuators can be incorporated into the design procedure. However, such constraints may great
Exploiting Job Response-Time Information in the Co-Design of Real-Time Control Systems
We consider a real-time system of multiple tasks, each task having a plant to control. The overall quadratic control cost is to be optimized. We exploit the periodicity of the task response time, which corresponds to a periodic delay pattern in the feedback control loop. Perturbed periods are used as a tool to find a finite hyperperiod. We present an analytical procedure to design a periodic linea
Recovery of Uniform Samples and Spectrum of Band-limited Irregularly Sampled Signals
This paper presents a straightforward method to convert non-uniformly sampled data to uniform samples in order to be processed by some off-line techniques such as system identification. In such scenarios, we deal with a finite-length measurement sequence. We assume periodic extension of the signals, which results in a simple system of linear equations. Furthermore, we take into account a number of
Asymmetric relay autotuning - Practical features for industrial use
The relay autotuner provides a simple way of finding PID controller parameters. Even though relay autotuning is much investigated in the literature, the practical aspects are not that well-documented. In this paper an asymmetric relay autotuner with features such as a startup procedure and adaptive relay amplitudes is proposed. Parameter choices and handling of noise, disturbances, start in non-st
