Distributed Model Predictive Control With Event Based Communication
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Distributed Model Predictive Control with Event-Based Communication
| Author | : Groß, Dominic |
| Publisher | : kassel university press GmbH |
| Total Pages | : 176 |
| Release | : 2015-02-25 |
| Genre | : |
| ISBN | : 386219910X |
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.
Distributed Cooperative Model Predictive Control of Networked Systems
| Author | : Yuanyuan Zou |
| Publisher | : Springer Nature |
| Total Pages | : 159 |
| Release | : 2022-10-03 |
| Genre | : Technology & Engineering |
| ISBN | : 9811960844 |
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.
Contributions to Event-triggered and Distributed Model Predictive Control
| Author | : Felix Berkel |
| Publisher | : Logos Verlag Berlin |
| Total Pages | : 0 |
| Release | : 2019 |
| Genre | : Predictive control |
| ISBN | : 9783832549350 |
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.
New Directions on Model Predictive Control
| Author | : Jinfeng Liu |
| Publisher | : MDPI |
| Total Pages | : 231 |
| Release | : 2019-01-16 |
| Genre | : Engineering (General). Civil engineering (General) |
| ISBN | : 303897420X |
This book is a printed edition of the Special Issue "New Directions on Model Predictive Control" that was published in Mathematics
Optimizing Control of Distributed Cyber-Physical Systems
| Author | : Zonglin Liu |
| Publisher | : BoD – Books on Demand |
| Total Pages | : 178 |
| Release | : 2021-01-01 |
| Genre | : Technology & Engineering |
| ISBN | : 3737609764 |
In this thesis, a set of modeling and control strategies are proposed for Cyberphysical systems (CPS), which aim at ensuring a safe, reliable, and highly performant operation of each local subsystem contained in the CPS. Modeling of CPS is challenging since not only must the tight interconnection of continuous and discrete dynamics of local subsystems be exactly represented, but so must also the interleaving structure between different subsystems. Optimal control of CPS, accordingly, should take into account not only the local mixed dynamics by local controller synthesis, but also the influence from other subsystems around.
Distributed Model Predictive Control Made Easy
| Author | : José M. Maestre |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 601 |
| Release | : 2013-11-10 |
| Genre | : Technology & Engineering |
| ISBN | : 9400770065 |
The rapid evolution of computer science, communication, and information technology has enabled the application of control techniques to systems beyond the possibilities of control theory just a decade ago. Critical infrastructures such as electricity, water, traffic and intermodal transport networks are now in the scope of control engineers. The sheer size of such large-scale systems requires the adoption of advanced distributed control approaches. Distributed model predictive control (MPC) is one of the promising control methodologies for control of such systems. This book provides a state-of-the-art overview of distributed MPC approaches, while at the same time making clear directions of research that deserve more attention. The core and rationale of 35 approaches are carefully explained. Moreover, detailed step-by-step algorithmic descriptions of each approach are provided. These features make the book a comprehensive guide both for those seeking an introduction to distributed MPC as well as for those who want to gain a deeper insight in the wide range of distributed MPC techniques available.
Recent Advances in Model Predictive Control
| Author | : Timm Faulwasser |
| Publisher | : Springer Nature |
| Total Pages | : 250 |
| Release | : 2021-04-17 |
| Genre | : Science |
| ISBN | : 3030632814 |
This book focuses on distributed and economic Model Predictive Control (MPC) with applications in different fields. MPC is one of the most successful advanced control methodologies due to the simplicity of the basic idea (measure the current state, predict and optimize the future behavior of the plant to determine an input signal, and repeat this procedure ad infinitum) and its capability to deal with constrained nonlinear multi-input multi-output systems. While the basic idea is simple, the rigorous analysis of the MPC closed loop can be quite involved. Here, distributed means that either the computation is distributed to meet real-time requirements for (very) large-scale systems or that distributed agents act autonomously while being coupled via the constraints and/or the control objective. In the latter case, communication is necessary to maintain feasibility or to recover system-wide optimal performance. The term economic refers to general control tasks and, thus, goes beyond the typically predominant control objective of set-point stabilization. Here, recently developed concepts like (strict) dissipativity of optimal control problems or turnpike properties play a crucial role. The book collects research and survey articles on recent ideas and it provides perspectives on current trends in nonlinear model predictive control. Indeed, the book is the outcome of a series of six workshops funded by the German Research Foundation (DFG) involving early-stage career scientists from different countries and from leading European industry stakeholders.
Distributed Cooperative Control and Communication for Multi-agent Systems
| Author | : Dong Yue |
| Publisher | : Springer Nature |
| Total Pages | : 196 |
| Release | : 2021-02-15 |
| Genre | : Technology & Engineering |
| ISBN | : 9813367180 |
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.
Distributed Model Predictive Control for Plant-Wide Systems
| Author | : Shaoyuan Li |
| Publisher | : John Wiley & Sons |
| Total Pages | : 421 |
| Release | : 2017-05-02 |
| Genre | : Science |
| ISBN | : 1118921593 |
DISTRIBUTED MODEL PREDICTIVE CONTROL FOR PLANT-WIDE SYSTEMS In this book, experienced researchers gave a thorough explanation of distributed model predictive control (DMPC): its basic concepts, technologies, and implementation in plant-wide systems. Known for its error tolerance, high flexibility, and good dynamic performance, DMPC is a popular topic in the control field and is widely applied in many industries. To efficiently design DMPC systems, readers will be introduced to several categories of coordinated DMPCs, which are suitable for different control requirements, such as network connectivity, error tolerance, performance of entire closed-loop systems, and calculation of speed. Various real-life industrial applications, theoretical results, and algorithms are provided to illustrate key concepts and methods, as well as to provide solutions to optimize the global performance of plant-wide systems. Features system partition methods, coordination strategies, performance analysis, and how to design stabilized DMPC under different coordination strategies. Presents useful theories and technologies that can be used in many different industrial fields, examples include metallurgical processes and high-speed transport. Reflects the authors’ extensive research in the area, providing a wealth of current and contextual information. Distributed Model Predictive Control for Plant-Wide Systems is an excellent resource for researchers in control theory for large-scale industrial processes. Advanced students of DMPC and control engineers will also find this as a comprehensive reference text.
