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Contributions to Event-triggered and Distributed Model Predictive Control

2019 Predictive control
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Release : 2019
Genre : Predictive control
Kind : eBook
Book Rating : 350/5 ( reviews)

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Book Synopsis Contributions to Event-triggered and Distributed Model Predictive Control by : Felix Berkel

Download or read book Contributions to Event-triggered and Distributed Model Predictive Control written by Felix Berkel. This book was released on 2019. Available in PDF, EPUB and Kindle. Book excerpt: This thesis deals with event-triggered model predictive control (MPC) strategies for constrained networked and distributed control systems. A networked control system usually consists of spatially distributed sensors, actuators and controllers that communicate over a shared communication network. Event-triggered control approaches consider the network utilization in the controller design to provide a compromise between control performance and communication effort. In this thesis a holistic output-based MPC scheme for constrained linear systems with event-triggered communication over the sensor-to-controller and controller-to-actuator channels of a network is presented. The proposed approach can be applied to centralized as well as decentralized setups and handles bounded time-varying sampling intervals and transmission delays for the control of constrained sampled-data systems. In distributed control set-ups the overall plant is decomposed into subsystems which are controlled by local controllers. Different distributed model predictive control (DMPC) approaches with reduced communication effort are presented in this thesis. The first approach is non-iterative and uses event-triggered communication for the exchange of state measurements. In the second approach, an event-triggered cooperation strategy for DMPC based on distributed optimization is introduced. Finally, an economic DMPC scheme for linear periodically time-varying systems which is motivated by two real-world applications, the control of a water distribution network and a medium voltage power grid, is presented.

Distributed Cooperative Model Predictive Control of Networked Systems

2022-10-03 Technology & Engineering
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Release : 2022-10-03
Genre : Technology & Engineering
Kind : eBook
Book Rating : 844/5 ( reviews)

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Book Synopsis Distributed Cooperative Model Predictive Control of Networked Systems by : Yuanyuan Zou

Download or read book Distributed Cooperative Model Predictive Control of Networked Systems written by Yuanyuan Zou. This book was released on 2022-10-03. Available in PDF, EPUB and Kindle. Book excerpt: This book is inspired by the development of distributed model predictive control of networked systems to save computation and communication sources. The significant new contribution is to show how to design efficient DMPCs that can be coordinated asynchronously with the increasing effectiveness of the event-triggering mechanism and how to improve the event-triggered DMPC for different requirements improvement of control performance, extension to interconnected networked systems, etc. The book is likely to be of interest to the persons who are engaged in researching control theory in academic institutes, the persons who go in for developing control systems in R&D institutes or companies, the control engineers who are engaged in the implementation of control algorithms, and people who are interested in the distributed MPC.

Distributed Model Predictive Control with Event-Based Communication

2015-02-25
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Release : 2015-02-25
Genre :
Kind : eBook
Book Rating : 10X/5 ( reviews)

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Book Synopsis Distributed Model Predictive Control with Event-Based Communication by : Groß, Dominic

Download or read book Distributed Model Predictive Control with Event-Based Communication written by Groß, Dominic. This book was released on 2015-02-25. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis, several algorithms for distributed model predictive control over digital communication networks with parallel computation are developed and analyzed. Distributed control aims at efficiently controlling large scale dynamical systems which consist of interconnected dynamical systems by means of communicating local controllers. Such distributed control problems arise in applications such as chemical processes, formation control, and control of power grids. In distributed model predictive control the underlying idea is to solve a large scale model predictive control problem in a distributed fashion in order to achieve faster computation and better robustness against local failures. Distributed model predictive control often heavily relies on frequent communication between the local model predictive controllers. However, a digital communication network may induce uncertainties such as a communication delays, especially if the load on the communication network is high. One topic of this thesis is to develop a distributed model predictive control algorithm for subsystems interconnected by constraints and common control goals which is robust with respect to time-varying communication delays.

Contributions to Networked and Event-Triggered Control of Linear Systems

2016-05-28 Technology & Engineering
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Release : 2016-05-28
Genre : Technology & Engineering
Kind : eBook
Book Rating : 816/5 ( reviews)

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Book Synopsis Contributions to Networked and Event-Triggered Control of Linear Systems by : María Guinaldo Losada

Download or read book Contributions to Networked and Event-Triggered Control of Linear Systems written by María Guinaldo Losada. This book was released on 2016-05-28. Available in PDF, EPUB and Kindle. Book excerpt: This book reports on a set of new techniques for resolving current issues in networked control systems. The main focus is on strategies for event-based control, for both centralized and decentralized architectures. The first part of the book addresses the problem of single-loop networked control systems and proposes an anticipative remote controller for dealing with delays and packet losses. The second part of the book proposes a distributed event-based control strategy for networked dynamical systems, which has been implemented in a test-bed of mobile robots, and provides readers with a thorough description of an interactive simulator used to validate the results. This thesis, examined at the Universidad Nacional de Educación a Distancia in 2013, received the award for best thesis in control engineering from the Control Engineering group of the Spanish Committee of Automatic Control in 2015.

A Hybrid Physical and Data-drivApproach to Motion Prediction and Control in Human-Robot Collaboration

2022-06-14 Technology & Engineering
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Release : 2022-06-14
Genre : Technology & Engineering
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Book Rating : 84X/5 ( reviews)

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Book Synopsis A Hybrid Physical and Data-drivApproach to Motion Prediction and Control in Human-Robot Collaboration by : Min Wu

Download or read book A Hybrid Physical and Data-drivApproach to Motion Prediction and Control in Human-Robot Collaboration written by Min Wu . This book was released on 2022-06-14. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, researchers have achieved great success in guaranteeing safety in human-robot interaction, yielding a new generation of robots that can work with humans in close proximity, known as collaborative robots (cobots). However, due to the lack of ability to understand and coordinate with their human partners, the ``co'' in most cobots still refers to ``coexistence'' rather than ``collaboration''. This thesis aims to develop an adaptive learning and control framework with a novel physical and data-driven approach towards a real collaborative robot. The first part focuses on online human motion prediction. A comprehensive study on various motion prediction techniques is presented, including their scope of application, accuracy in different time scales, and implementation complexity. Based on this study, a hybrid approach that combines physically well-understood models with data-driven learning techniques is proposed and validated through a motion data set. The second part addresses interaction control in human-robot collaboration. An adaptive impedance control scheme with human reference estimation is presented. Reinforcement learning is used to find optimal control parameters to minimize a task-orient cost function without fully knowing the system dynamic. The proposed framework is experimentally validated through two benchmark applications for human-robot collaboration: object handover and cooperative object handling. Results show that the robot can provide reliable online human motion prediction, react early to human motion variation, make proactive contributions to physical collaborations, and behave compliantly in response to human forces.

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