Download or read book Contributions to Event triggered and Distributed Model Predictive Control written by Felix Berkel and published by Logos Verlag Berlin. This book was released on 2019 with total page 0 pages. 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.
Download or read book Distributed Cooperative Model Predictive Control of Networked Systems written by Yuanyuan Zou and published by Springer Nature. This book was released on 2022-10-03 with total page 159 pages. 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.
Download or read book Distributed Model Predictive Control with Event Based Communication written by Groß, Dominic and published by kassel university press GmbH. This book was released on 2015-02-25 with total page 176 pages. 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.
Download or read book Contributions to Networked and Event Triggered Control of Linear Systems written by María Guinaldo Losada and published by Springer. This book was released on 2016-05-28 with total page 232 pages. 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.
Download or read book A Hybrid Physical and Data drivApproach to Motion Prediction and Control in Human Robot Collaboration written by Min Wu and published by Logos Verlag Berlin GmbH. This book was released on 2022-06-14 with total page 212 pages. 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.
Download or read book New Directions on Model Predictive Control written by Jinfeng Liu and published by MDPI. This book was released on 2019-01-16 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "New Directions on Model Predictive Control" that was published in Mathematics
Download or read book Modelling and Control of an Autonomous Two Wheeled Vehicle written by Alen Turnwald and published by Logos Verlag Berlin GmbH. This book was released on 2020-11-13 with total page 175 pages. Available in PDF, EPUB and Kindle. Book excerpt: With respect to the future urban mobility, modern electrical bicycles, advanced motorcycles and innovative two-wheeled vehicles are arresting enormous amount of attention. Especially, model-based control and optimal trajectory planning for such vehicles are important to the research and development of the future. Therefore, a reliable and yet usable vehicle model as well as a systematic approach to motion control for two-wheeled vehicles are essential, to which this work makes a contribution. Currently available two-wheeled vehicle models are mostly either too complex to be used for a systematic control synthesis, or too simple such that the physical behaviour of the vehicle is no more represented. In this thesis, a unifying approach to modelling and control for autonomous two-wheeled vehicles is presented. The resulting model is generally valid and physically detailed enough to represent the characteristic dynamical behaviour such as the self-stability. At the same time, it is suited to a systematic control synthesis. Furthermore, the systematic extenddability, for instance by a rider, is demonstrated. The model is validated by simulations and by comparison to well-known models from the literature. The proposed vehicle model is derived in the Lagrangian and Hamiltonian framework and used for model-based optimal trajectory planning. Furthermore, a passivity-based trajectory tracking controller is designed based on the resulting port-Hamiltonian system using the so-called generalised canonical transformations. Such a controller is physically interpretable and robust against parameter uncertainties. To this end, existing approaches of passivity-based controller design are extended and adjusted for two-wheeled vehicles. Finally, a prototype two-wheeled vehicle is introduced which is used for experimental validation of the model and to demonstrate motion control algorithms for autonomous two-wheeled vehicles.
Download or read book Distributed Cooperative Control and Communication for Multi agent Systems written by Dong Yue and published by Springer Nature. This book was released on 2021-02-15 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book investigates distributed cooperative control and communication of MASs including linear systems, nonlinear systems and multiple rigid body systems. The model-based and data-driven control method are employed to design the (optimal) cooperative control protocol. The approaches of this book consist of model-based and data-driven control such as predictive control, event-triggered control, optimal control, adaptive dynamic programming, etc. From this book, readers can learn about distributed cooperative control methods, data-driven control, finite-time stability analysis, cooperative attitude control of multiple rigid bodies. Some fundamental knowledge prepared to read this book is finite-time stability theory, event-triggered sampling mechanism, adaptive dynamic programming and optimal control.
Download or read book Economic Model Predictive Control written by Helen Durand and published by Foundations and Trends (R) in Systems and Control. This book was released on 2018-06-19 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt: Economic Model Predictive Control (EMPC) is a control strategy that moves process operation away from the steady-state paradigm toward a potentially time-varying operating strategy to improve process profitability. The EMPC literature is replete with evidence that this new paradigm may enhance process profits when a model of the chemical process provides a sufficiently accurate representation of the process dynamics. Systems using EMPC often neglect the dynamics associated with equipment and are often neglected when modeling a chemical process. Recent studies have shown they can significantly impact the effectiveness of an EMPC system. Concentrating on valve behavior in a chemical process, this monograph develops insights into the manner in which equipment behavior should impact the design process for EMPC and to provide a perspective on a number of open research topics in this direction. Written in tutorial style, this monograph provides the reader with a full literature review of the topic and demonstrates how these techniques can be adopted in a practical system.
Download or read book Distributed Model Predictive Control written by Aswin N. Venkat and published by . This book was released on 2006 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Networked Control Systems written by Alberto Bemporad and published by Springer. This book was released on 2010-10-15 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book nds its origin in the WIDE PhD School on Networked Control Systems, which we organized in July 2009 in Siena, Italy. Having gathered experts on all the aspects of networked control systems, it was a small step to go from the summer school to the book, certainly given the enthusiasm of the lecturers at the school. We felt that a book collecting overviewson the important developmentsand open pr- lems in the eld of networked control systems could stimulate and support future research in this appealing area. Given the tremendouscurrentinterests in distributed control exploiting wired and wireless communication networks, the time seemed to be right for the book that lies now in front of you. The goal of the book is to set out the core techniques and tools that are ava- able for the modeling, analysis and design of networked control systems. Roughly speaking, the book consists of three parts. The rst part presents architectures for distributed control systems and models of wired and wireless communication n- works. In particular, in the rst chapter important technological and architectural aspects on distributed control systems are discussed. The second chapter provides insight in the behavior of communication channels in terms of delays, packet loss and information constraints leading to suitable modeling paradigms for commu- cation networks.
Download or read book Distributed Event triggered Control written by Zhongkui Li and published by Springer Nature. This book was released on 2023-12-11 with total page 155 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on distributed event-triggered control of multi-agent systems, in which the event-triggering mechanism is utilized to reduce the communication frequencies in order to compensate for constrained network bandwidths, an aspect that poses significant challenges for distributed control design. The book summarizes the authors’ original, systematic contributions on scalability and robustness, two core issues in distributed event-triggered control. Specifically, the book presents fully distributed adaptive event-triggered control laws; as they rely on neither continuous communications nor global information on the network, these laws are scalable with regard to network size and topology. Moreover, the book provides novel and robust event-triggered algorithms, which can accommodate various frequency-domain and matching uncertainties. The results presented here are applicable to UAV swarms, automobile systems, aerospace systems, vehicle platooning, and more, and will be of considerable interest to graduate students, researchers, and engineers working on network control systems.
Download or read book Multisensor Fusion Estimation Theory and Application written by Liping Yan and published by Springer Nature. This book was released on 2020-11-11 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the basic theory and methods of multisensor data fusion state estimation and its application. It consists of four parts with 12 chapters. In Part I, the basic framework and methods of multisensor optimal estimation and the basic concepts of Kalman filtering are briefly and systematically introduced. In Part II, the data fusion state estimation algorithms under networked environment are introduced. Part III consists of three chapters, in which the fusion estimation algorithms under event-triggered mechanisms are introduced. Part IV consists of two chapters, in which fusion estimation for systems with non-Gaussian but heavy-tailed noises are introduced. The book is primarily intended for researchers and engineers in the field of data fusion and state estimation. It also benefits for both graduate and undergraduate students who are interested in target tracking, navigation, networked control, etc.
Download or read book An Event triggered Networked Model Predictive Control Approach for Lean Embedded Hardware written by Patrik Simon Berner and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Distributed Model Predictive Control with Industrial Applications written by Magdi S. Mahmoud and published by Elsevier. This book was released on 2024-03-01 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Distributed Model Predictive Control with Industrial Applications provides an overview of the latest advances in Distributed Model Predictive Controllers with special emphasis on Data and Iterative Learning Control (ILC), as well as emerging industrial applications in the security of cyber-physical systems. This book explores the most recent and modern approaches to the control of distributed systems on the framework of model predictive control while focusing on exploiting and controlling physical processes by means of data generated within the system and their interaction with the environments. The book begins with a general introduction of the subject material and subsequent chapters focus on main topics, while highlighting most recent contributions in the subject and open areas and research questions left unanswered. Algorithms related to the subject are explained concisely with some typical examples from literature to reinforce understanding. Provides modern, concise, and precise explanations of theoretical concepts with industrial case studies Highlights the most recent contributions in the area of distributed model predictive controllers Explains algorithms related to the subject typical examples from literature to reinforce understanding
Download or read book Advances in nonlinear systems and networks volume II written by Fei Yu and published by Frontiers Media SA. This book was released on 2024-03-04 with total page 131 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Model Predictive Control in the Process Industry written by Eduardo F. Camacho and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: Model Predictive Control is an important technique used in the process control industries. It has developed considerably in the last few years, because it is the most general way of posing the process control problem in the time domain. The Model Predictive Control formulation integrates optimal control, stochastic control, control of processes with dead time, multivariable control and future references. The finite control horizon makes it possible to handle constraints and non linear processes in general which are frequently found in industry. Focusing on implementation issues for Model Predictive Controllers in industry, it fills the gap between the empirical way practitioners use control algorithms and the sometimes abstractly formulated techniques developed by researchers. The text is firmly based on material from lectures given to senior undergraduate and graduate students and articles written by the authors.
