Download or read book Nonlinear Model Predictive Control written by Frank Allgöwer and published by Birkhäuser. This book was released on 2012-12-06 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the past decade model predictive control (MPC), also referred to as receding horizon control or moving horizon control, has become the preferred control strategy for quite a number of industrial processes. There have been many significant advances in this area over the past years, one of the most important ones being its extension to nonlinear systems. This book gives an up-to-date assessment of the current state of the art in the new field of nonlinear model predictive control (NMPC). The main topic areas that appear to be of central importance for NMPC are covered, namely receding horizon control theory, modeling for NMPC, computational aspects of on-line optimization and application issues. The book consists of selected papers presented at the International Symposium on Nonlinear Model Predictive Control – Assessment and Future Directions, which took place from June 3 to 5, 1998, in Ascona, Switzerland. The book is geared towards researchers and practitioners in the area of control engineering and control theory. It is also suited for postgraduate students as the book contains several overview articles that give a tutorial introduction into the various aspects of nonlinear model predictive control, including systems theory, computations, modeling and applications.

Download or read book Nonlinear Model Predictive Control of a Quadrotor written by Emilio Melgarejo Hernández and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the most important features of a quadrotor in order to properly work, generally in some sort of path tracking, is to have a suitable control. This thesis will approach the problem of controlling a quadrotor applying the control technique known as Nonlinear Model Predictive Control. First, this control should guarantee stability and feasibility, and then the control parameters are tuned to obtain the better possible performance. Proper simulations will be performed by selecting different situations in terms of path tracking references, as well as in terms of the accuracy level of the control model with respect to the real system represented by a high-fidelity model. Additionally, the requirements for the controller to work in real time will be explored and discussed.

Download or read book Controlling a Quadrotor with a Robotic Arm Using Nonlinear Model Predictive Control written by Sebastián Chávez-Ferrer Marcos and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis designs a method to control a quadrotor equipped with a robotic arm. The arm has been developed in Institut de Rob otica i Inform atica Industrial (CSIC-UPC), namely here IRI. During the project, an algorithm has been made as a rst approximation to control a quadrotor that is working with the robotic arm. In order to compensate the perturbations of the arm's dynamic, a NMPC algorithm has been chosen while others have been discarded as it is discussed in the state of the art (PID, Linear Model Predictive Control or LQR). PID and model predictive control have been discarded because is not possible to handle the nonlinearities of the system studied and reach the desired control objectives. Also there are no possibilites to restrict the system using physical constraints. Finally, three scenarios have been simulated and tested to verify the performances and robustness of the designed method. A takeo maneuver, where the quadrotor reaches a speci c altitude. A hover mode where the system should compensate the dynamics of the arm while it is static or it is in movement. Finally, the quadorotor has to move to a speci c point in the space while the arm it is static or in movement. The goal of the controller is to reject the perturbation due the movement of the arm and stabilize the system. This thesis presents the results obtained after simulating the designed controller with the scenarios considered.

Download or read book Fast Nonlinear Model Predictive Control of Quadrotors written by Hadi Mohammadi Daniali and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Quadrotor (or quadcopter) is a type of Unmanned Aerial Vehicles (UAVs). Due to the quadrotors simple and inexpensive design, they have become popular platforms. This thesis proposes a computationally fast scheme for implementing Nonlinear Model Predictive Control (NMPC) as a high-level controller to solve the path following problem for unmanned quadrotors. After discussing the background and reviewing the literature, it is noted that this problem referred widely in the literature as a necessary step toward the autonomous flight of quadrotor UAVs. The previous studies usually used simplified models which are computationally uncomplicated and straightforward in terms of control developments and stability investigations. Moreover, some articles are presented showing the importance of accurate state observation on the performance of feedback-based control approaches. The NMPC-based controller is designed using a more realistic highly nonlinear control-oriented model which requires heavy computations for practical real-time implementations. To deal with this issue, the Newton generalized minimal residual (Newton/GMRES) method is applied to solve the NMPC's real-time optimizations rapidly during the control process. This technique uses the Hamiltonian method to derive a set of equations with multiple variables. To solve these in a real-time application, the Newton/GMRES method applies forward-difference generalized minimal residual (fdgmres) algorithm. The simulation and experimental result using a commercial drone, called AR.Drone 2.0, in our laboratory instrumented by a Vicon Vantage motion capture system, demonstrate that our feedback-based control method's performance highly depends on the reliability of the state vector feedback signals. As a result, a Kalman filter and Luenberger observer algorithms are used for estimating unknown states. The NMPC-based controller operation is simulated, and the result reveals the similar efficiency of observers. Moreover, the NMPC control approach is compared with a proportional controller which shows great improvements in the response of the quadrotor. The experiment showed that our control method is sufficiently fast for practical implementations, and it can solve the trajectory tracking problem properly even for complex paths. This thesis is concluded by stating a summary of contributions and some potential future works.

Download or read book Non linear Predictive Control written by Basil Kouvaritakis and published by IET. This book was released on 2001-10-26 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: The advantage of model predictive control is that it can take systematic account of constraints, thereby allowing processes to operate at the limits of achievable performance. Engineers in academia, industry, and government from the US and Europe explain how the linear version can be adapted and applied to the nonlinear conditions that characterize the dynamics of most real manufacturing plants. They survey theoretical and practical trends, describe some specific theories and demonstrate their practical application, derive strategies that provide appropriate assurance of closed-loop stability, and discuss practical implementation. Annotation copyrighted by Book News, Inc., Portland, OR

Download or read book Assessment and Future Directions of Nonlinear Model Predictive Control written by Rolf Findeisen and published by Springer. This book was released on 2007-09-08 with total page 644 pages. Available in PDF, EPUB and Kindle. Book excerpt: Thepastthree decadeshaveseenrapiddevelopmentin the areaofmodelpred- tive control with respect to both theoretical and application aspects. Over these 30 years, model predictive control for linear systems has been widely applied, especially in the area of process control. However, today’s applications often require driving the process over a wide region and close to the boundaries of - erability, while satisfying constraints and achieving near-optimal performance. Consequently, the application of linear control methods does not always lead to satisfactory performance, and here nonlinear methods must be employed. This is one of the reasons why nonlinear model predictive control (NMPC) has - joyed signi?cant attention over the past years,with a number of recent advances on both the theoretical and application frontier. Additionally, the widespread availability and steadily increasing power of today’s computers, as well as the development of specially tailored numerical solution methods for NMPC, bring thepracticalapplicabilityofNMPCwithinreachevenforveryfastsystems.This has led to a series of new, exciting developments, along with new challenges in the area of NMPC.

Download or read book Model Based Predictive Control written by J.A. Rossiter and published by CRC Press. This book was released on 2017-07-12 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: Model Predictive Control (MPC) has become a widely used methodology across all engineering disciplines, yet there are few books which study this approach. Until now, no book has addressed in detail all key issues in the field including apriori stability and robust stability results. Engineers and MPC researchers now have a volume that provides a complete overview of the theory and practice of MPC as it relates to process and control engineering. Model-Based Predictive Control, A Practical Approach, analyzes predictive control from its base mathematical foundation, but delivers the subject matter in a readable, intuitive style. The author writes in layman's terms, avoiding jargon and using a style that relies upon personal insight into practical applications. This detailed introduction to predictive control introduces basic MPC concepts and demonstrates how they are applied in the design and control of systems, experiments, and industrial processes. The text outlines how to model, provide robustness, handle constraints, ensure feasibility, and guarantee stability. It also details options in regard to algorithms, models, and complexity vs. performance issues.

Download or read book 2020 2nd Novel Intelligent and Leading Emerging Sciences Conference NILES written by IEEE Staff and published by . This book was released on 2020-10-24 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The conference aims at providing a platform for researchers, engineers, academics and industrial professionals to present their recent research work and to explore future trends in various areas of engineering and technology

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.

Download or read book Economic Model Predictive Control written by Matthew Ellis and published by Springer. This book was released on 2016-07-27 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents general methods for the design of economic model predictive control (EMPC) systems for broad classes of nonlinear systems that address key theoretical and practical considerations including recursive feasibility, closed-loop stability, closed-loop performance, and computational efficiency. Specifically, the book proposes: Lyapunov-based EMPC methods for nonlinear systems; two-tier EMPC architectures that are highly computationally efficient; and EMPC schemes handling explicitly uncertainty, time-varying cost functions, time-delays and multiple-time-scale dynamics. The proposed methods employ a variety of tools ranging from nonlinear systems analysis, through Lyapunov-based control techniques to nonlinear dynamic optimization. The applicability and performance of the proposed methods are demonstrated through a number of chemical process examples. The book presents state-of-the-art methods for the design of economic model predictive control systems for chemical processes.In addition to being mathematically rigorous, these methods accommodate key practical issues, for example, direct optimization of process economics, time-varying economic cost functions and computational efficiency. Numerous comments and remarks providing fundamental understanding of the merging of process economics and feedback control into a single framework are included. A control engineer can easily tailor the many detailed examples of industrial relevance given within the text to a specific application. The authors present a rich collection of new research topics and references to significant recent work making Economic Model Predictive Control an important source of information and inspiration for academics and graduate students researching the area and for process engineers interested in applying its ideas.

Download or read book Explicit Nonlinear Model Predictive Control written by Alexandra Grancharova and published by Springer. This book was released on 2012-03-22 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonlinear Model Predictive Control (NMPC) has become the accepted methodology to solve complex control problems related to process industries. The main motivation behind explicit NMPC is that an explicit state feedback law avoids the need for executing a numerical optimization algorithm in real time. The benefits of an explicit solution, in addition to the efficient on-line computations, include also verifiability of the implementation and the possibility to design embedded control systems with low software and hardware complexity. This book considers the multi-parametric Nonlinear Programming (mp-NLP) approaches to explicit approximate NMPC of constrained nonlinear systems, developed by the authors, as well as their applications to various NMPC problem formulations and several case studies. The following types of nonlinear systems are considered, resulting in different NMPC problem formulations: ؠ Nonlinear systems described by first-principles models and nonlinear systems described by black-box models; - Nonlinear systems with continuous control inputs and nonlinear systems with quantized control inputs; - Nonlinear systems without uncertainty and nonlinear systems with uncertainties (polyhedral description of uncertainty and stochastic description of uncertainty); - Nonlinear systems, consisting of interconnected nonlinear sub-systems. The proposed mp-NLP approaches are illustrated with applications to several case studies, which are taken from diverse areas such as automotive mechatronics, compressor control, combustion plant control, reactor control, pH maintaining system control, cart and spring system control, and diving computers.

Download or read book Model Predictive Control System Design and Implementation Using MATLAB written by Liuping Wang and published by Springer Science & Business Media. This book was released on 2009-02-14 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Airborne Wind Energy written by Roland Schmehl and published by Springer. This book was released on 2018-03-31 with total page 752 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides in-depth coverage of the latest research and development activities concerning innovative wind energy technologies intended to replace fossil fuels on an economical basis. A characteristic feature of the various conversion concepts discussed is the use of tethered flying devices to substantially reduce the material consumption per installed unit and to access wind energy at higher altitudes, where the wind is more consistent. The introductory chapter describes the emergence and economic dimension of airborne wind energy. Focusing on “Fundamentals, Modeling & Simulation”, Part I includes six contributions that describe quasi-steady as well as dynamic models and simulations of airborne wind energy systems or individual components. Shifting the spotlight to “Control, Optimization & Flight State Measurement”, Part II combines one chapter on measurement techniques with five chapters on control of kite and ground stations, and two chapters on optimization. Part III on “Concept Design & Analysis” includes three chapters that present and analyze novel harvesting concepts as well as two chapters on system component design. Part IV, which centers on “Implemented Concepts”, presents five chapters on established system concepts and one chapter about a subsystem for automatic launching and landing of kites. In closing, Part V focuses with four chapters on “Technology Deployment” related to market and financing strategies, as well as on regulation and the environment. The book builds on the success of the first volume “Airborne Wind Energy” (Springer, 2013), and offers a self-contained reference guide for researchers, scientists, professionals and students. The respective chapters were contributed by a broad variety of authors: academics, practicing engineers and inventors, all of whom are experts in their respective fields.

Download or read book Adaptive Dynamic Programming Single and Multiple Controllers written by Ruizhuo Song and published by Springer. This book was released on 2018-12-28 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a class of novel optimal control methods and games schemes based on adaptive dynamic programming techniques. For systems with one control input, the ADP-based optimal control is designed for different objectives, while for systems with multi-players, the optimal control inputs are proposed based on games. In order to verify the effectiveness of the proposed methods, the book analyzes the properties of the adaptive dynamic programming methods, including convergence of the iterative value functions and the stability of the system under the iterative control laws. Further, to substantiate the mathematical analysis, it presents various application examples, which provide reference to real-world practices.

Download or read book Unmanned Aerial Vehicles Breakthroughs in Research and Practice written by Management Association, Information Resources and published by IGI Global. This book was released on 2019-05-03 with total page 558 pages. Available in PDF, EPUB and Kindle. Book excerpt: First used in military applications, unmanned aerial vehicles are becoming an integral aspect of modern society and are expanding into the commercial, scientific, recreational, agricultural, and surveillance sectors. With the increasing use of these drones by government officials, business professionals, and civilians, more research is needed to understand their complexity both in design and function. Unmanned Aerial Vehicles: Breakthroughs in Research and Practice is a critical source of academic knowledge on the design, construction, and maintenance of drones, as well as their applications across all aspects of society. Highlighting a range of pertinent topics such as intelligent systems, artificial intelligence, and situation awareness, this publication is an ideal reference source for military consultants, military personnel, business professionals, operation managers, surveillance companies, agriculturalists, policymakers, government officials, law enforcement, IT professionals, academicians, researchers, and graduate-level students.

Download or read book Predictive Control for Linear and Hybrid Systems written by Francesco Borrelli and published by Cambridge University Press. This book was released on 2017-06-22 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: With a simple approach that includes real-time applications and algorithms, this book covers the theory of model predictive control (MPC).

Download or read book Handbook of Model Predictive Control written by Saša V. Raković and published by Springer. This book was released on 2018-09-01 with total page 693 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent developments in model-predictive control promise remarkable opportunities for designing multi-input, multi-output control systems and improving the control of single-input, single-output systems. This volume provides a definitive survey of the latest model-predictive control methods available to engineers and scientists today. The initial set of chapters present various methods for managing uncertainty in systems, including stochastic model-predictive control. With the advent of affordable and fast computation, control engineers now need to think about using “computationally intensive controls,” so the second part of this book addresses the solution of optimization problems in “real” time for model-predictive control. The theory and applications of control theory often influence each other, so the last section of Handbook of Model Predictive Control rounds out the book with representative applications to automobiles, healthcare, robotics, and finance. The chapters in this volume will be useful to working engineers, scientists, and mathematicians, as well as students and faculty interested in the progression of control theory. Future developments in MPC will no doubt build from concepts demonstrated in this book and anyone with an interest in MPC will find fruitful information and suggestions for additional reading.