Model Predictive Vibration Control

Model Predictive Vibration Control
Author: Gergely Takács
Publisher: Springer Science & Business Media
Total Pages: 535
Release: 2012-03-14
Genre: Technology & Engineering
ISBN: 1447123328

Real-time model predictive controller (MPC) implementation in active vibration control (AVC) is often rendered difficult by fast sampling speeds and extensive actuator-deformation asymmetry. If the control of lightly damped mechanical structures is assumed, the region of attraction containing the set of allowable initial conditions requires a large prediction horizon, making the already computationally demanding on-line process even more complex. Model Predictive Vibration Control provides insight into the predictive control of lightly damped vibrating structures by exploring computationally efficient algorithms which are capable of low frequency vibration control with guaranteed stability and constraint feasibility. In addition to a theoretical primer on active vibration damping and model predictive control, Model Predictive Vibration Control provides a guide through the necessary steps in understanding the founding ideas of predictive control applied in AVC such as: · the implementation of computationally efficient algorithms · control strategies in simulation and experiment and · typical hardware requirements for piezoceramics actuated smart structures. The use of a simple laboratory model and inclusion of over 170 illustrations provides readers with clear and methodical explanations, making Model Predictive Vibration Control the ideal support material for graduates, researchers and industrial practitioners with an interest in efficient predictive control to be utilized in active vibration attenuation.

Model Predictive Vibration Control

Model Predictive Vibration Control
Author: Gergely Takács
Publisher: Springer Science & Business Media
Total Pages: 535
Release: 2012-03-05
Genre: Technology & Engineering
ISBN: 1447123336

Real-time model predictive controller (MPC) implementation in active vibration control (AVC) is often rendered difficult by fast sampling speeds and extensive actuator-deformation asymmetry. If the control of lightly damped mechanical structures is assumed, the region of attraction containing the set of allowable initial conditions requires a large prediction horizon, making the already computationally demanding on-line process even more complex. Model Predictive Vibration Control provides insight into the predictive control of lightly damped vibrating structures by exploring computationally efficient algorithms which are capable of low frequency vibration control with guaranteed stability and constraint feasibility. In addition to a theoretical primer on active vibration damping and model predictive control, Model Predictive Vibration Control provides a guide through the necessary steps in understanding the founding ideas of predictive control applied in AVC such as: · the implementation of computationally efficient algorithms · control strategies in simulation and experiment and · typical hardware requirements for piezoceramics actuated smart structures. The use of a simple laboratory model and inclusion of over 170 illustrations provides readers with clear and methodical explanations, making Model Predictive Vibration Control the ideal support material for graduates, researchers and industrial practitioners with an interest in efficient predictive control to be utilized in active vibration attenuation.

Distributed Model Predictive Control Made Easy

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.

Dynamic Modeling, Predictive Control and Performance Monitoring

Dynamic Modeling, Predictive Control and Performance Monitoring
Author: Biao Huang
Publisher: Springer
Total Pages: 249
Release: 2008-03-02
Genre: Technology & Engineering
ISBN: 1848002335

A typical design procedure for model predictive control or control performance monitoring consists of: 1. identification of a parametric or nonparametric model; 2. derivation of the output predictor from the model; 3. design of the control law or calculation of performance indices according to the predictor. Both design problems need an explicit model form and both require this three-step design procedure. Can this design procedure be simplified? Can an explicit model be avoided? With these questions in mind, the authors eliminate the first and second step of the above design procedure, a “data-driven” approach in the sense that no traditional parametric models are used; hence, the intermediate subspace matrices, which are obtained from the process data and otherwise identified as a first step in the subspace identification methods, are used directly for the designs. Without using an explicit model, the design procedure is simplified and the modelling error caused by parameterization is eliminated.

Model Predictive Control System Design and Implementation Using MATLAB®

Model Predictive Control System Design and Implementation Using MATLAB®
Author: Liuping Wang
Publisher: Springer Science & Business Media
Total Pages: 398
Release: 2009-02-14
Genre: Technology & Engineering
ISBN: 1848823312

Model Predictive Control System Design and Implementation Using MATLAB® proposes methods for design and implementation of MPC systems using basis functions that confer the following advantages: - continuous- and discrete-time MPC problems solved in similar design frameworks; - a parsimonious parametric representation of the control trajectory gives rise to computationally efficient algorithms and better on-line performance; and - a more general discrete-time representation of MPC design that becomes identical to the traditional approach for an appropriate choice of parameters. After the theoretical presentation, coverage is given to three industrial applications. The subject of quadratic programming, often associated with the core optimization algorithms of MPC is also introduced and explained. The technical contents of this book is mainly based on advances in MPC using state-space models and basis functions. This volume includes numerous analytical examples and problems and MATLAB® programs and exercises.

Practical Design and Application of Model Predictive Control

Practical Design and Application of Model Predictive Control
Author: Nassim Khaled
Publisher: Butterworth-Heinemann
Total Pages: 264
Release: 2018-05-04
Genre: Technology & Engineering
ISBN: 0128139196

Practical Design and Application of Model Predictive Control is a self-learning resource on how to design, tune and deploy an MPC using MATLAB® and Simulink®. This reference is one of the most detailed publications on how to design and tune MPC controllers. Examples presented range from double-Mass spring system, ship heading and speed control, robustness analysis through Monte-Carlo simulations, photovoltaic optimal control, and energy management of power-split and air-handling control. Readers will also learn how to embed the designed MPC controller in a real-time platform such as Arduino®. The selected problems are nonlinear and challenging, and thus serve as an excellent experimental, dynamic system to show the reader the capability of MPC. The step-by-step solutions of the problems are thoroughly documented to allow the reader to easily replicate the results. Furthermore, the MATLAB® and Simulink® codes for the solutions are available for free download. Readers can connect with the authors through the dedicated website which includes additional free resources at www.practicalmpc.com. - Illustrates how to design, tune and deploy MPC for projects in a quick manner - Demonstrates a variety of applications that are solved using MATLAB® and Simulink® - Bridges the gap in providing a number of realistic problems with very hands-on training - Provides MATLAB® and Simulink® code solutions. This includes nonlinear plant models that the reader can use for other projects and research work - Presents application problems with solutions to help reinforce the information learned

Model Predictive Control of Microgrids

Model Predictive Control of Microgrids
Author: Carlos Bordons
Publisher: Springer Nature
Total Pages: 280
Release: 2019-09-12
Genre: Technology & Engineering
ISBN: 3030245705

The book shows how the operation of renewable-energy microgrids can be facilitated by the use of model predictive control (MPC). It gives readers a wide overview of control methods for microgrid operation at all levels, ranging from quality of service, to integration in the electricity market. MPC-based solutions are provided for the main control issues related to energy management and optimal operation of microgrids. The authors present MPC techniques for case studies that include different renewable sources – mainly photovoltaic and wind – as well as hybrid storage using batteries, hydrogen and supercapacitors. Experimental results for a pilot-scale microgrid are also presented, as well as simulations of scheduling in the electricity market and integration of electric and hybrid vehicles into the microgrid. in order to replicate the examples provided in the book and to develop and validate control algorithms on existing or projected microgrids. Model Predictive Control of Microgrids will interest researchers and practitioners, enabling them to keep abreast of a rapidly developing field. The text will also help to guide graduate students through processes from the conception and initial design of a microgrid through its implementation to the optimization of microgrid management. Advances in Industrial Control reports and encourages the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.

Virtual Inertia Synthesis and Control

Virtual Inertia Synthesis and Control
Author: Thongchart Kerdphol
Publisher: Springer Nature
Total Pages: 259
Release: 2020-11-28
Genre: Technology & Engineering
ISBN: 3030579611

This book provides a thorough understanding of the basic principles, synthesis, analysis, and control of virtual inertia systems. It uses the latest technical tools to mitigate power system stability and control problems under the presence of high distributed generators (DGs) and renewable energy sources (RESs) penetration. This book uses a simple virtual inertia control structure based on the frequency response model, complemented with various control methods and algorithms to achieve an adaptive virtual inertia control respect to the frequency stability and control issues. The chapters capture the important aspects in virtual inertia synthesis and control with the objective of solving the stability and control problems regarding the changes of system inertia caused by the integration of DGs/RESs. Different topics on the synthesis and application of virtual inertia are thoroughly covered with the description and analysis of numerous conventional and modern control methods for enhancing the full spectrum of power system stability and control. Filled with illustrative examples, this book gives the necessary fundamentals and insight into practical aspects. This book stimulates further research and offers practical solutions to real-world power system stability and control problems with respect to the system inertia variation triggered by the integration of RESs/DGs. It will be of use to engineers, academic researchers, and university students interested in power systems dynamics, analysis, stability and control.

Predictive Control for Linear and Hybrid Systems

Predictive Control for Linear and Hybrid Systems
Author: Francesco Borrelli
Publisher: Cambridge University Press
Total Pages: 447
Release: 2017-06-22
Genre: Mathematics
ISBN: 1107016886

With a simple approach that includes real-time applications and algorithms, this book covers the theory of model predictive control (MPC).