State Feedback Control and Kalman Filtering with MATLAB/Simulink Tutorials


Book Description

STATE FEEDBACK CONTROL AND KALMAN FILTERING WITH MATLAB/SIMULINK TUTORIALS Discover the control engineering skills for state space control system design, simulation, and implementation State space control system design is one of the core courses covered in engineering programs around the world. Applications of control engineering include things like autonomous vehicles, renewable energy, unmanned aerial vehicles, electrical machine control, and robotics, and as a result the field may be considered cutting-edge. The majority of textbooks on the subject, however, lack the key link between the theory and the applications of design methodology. State Feedback Control and Kalman Filtering with MATLAB/Simulink Tutorials provides a unique perspective by linking state space control systems to engineering applications. The book comprehensively delivers introductory topics in state space control systems through to advanced topics like sensor fusion and repetitive control systems. More, it explores beyond traditional approaches in state space control by having a heavy focus on important issues associated with control systems like disturbance rejection, reference tracking, control signal constraint, sensor fusion and more. The text sequentially presents continuous-time and discrete-time state space control systems, Kalman filter and its applications in sensor fusion. State Feedback Control and Kalman Filtering with MATLAB/Simulink Tutorials readers will also find: MATLAB and Simulink tutorials in a step-by-step manner that enable the reader to master the control engineering skills for state space control system design and Kalman filter, simulation, and implementation An accompanying website that includes MATLAB code High-end illustrations and tables throughout the text to illustrate important points Written by experts in the field of process control and state space control systems State Feedback Control and Kalman Filtering with MATLAB/Simulink Tutorials is an ideal resource for students from advanced undergraduate students to postgraduates, as well as industrial researchers and engineers in electrical, mechanical, chemical, and aerospace engineering.




State Feedback Control and Kalman Filtering with MATLAB/Simulink Tutorials


Book Description

STATE FEEDBACK CONTROL AND KALMAN FILTERING WITH MATLAB/SIMULINK TUTORIALS Discover the control engineering skills for state space control system design, simulation, and implementation State space control system design is one of the core courses covered in engineering programs around the world. Applications of control engineering include things like autonomous vehicles, renewable energy, unmanned aerial vehicles, electrical machine control, and robotics, and as a result the field may be considered cutting-edge. The majority of textbooks on the subject, however, lack the key link between the theory and the applications of design methodology. State Feedback Control and Kalman Filtering with MATLAB/Simulink Tutorials provides a unique perspective by linking state space control systems to engineering applications. The book comprehensively delivers introductory topics in state space control systems through to advanced topics like sensor fusion and repetitive control systems. More, it explores beyond traditional approaches in state space control by having a heavy focus on important issues associated with control systems like disturbance rejection, reference tracking, control signal constraint, sensor fusion and more. The text sequentially presents continuous-time and discrete-time state space control systems, Kalman filter and its applications in sensor fusion. State Feedback Control and Kalman Filtering with MATLAB/Simulink Tutorials readers will also find: MATLAB and Simulink tutorials in a step-by-step manner that enable the reader to master the control engineering skills for state space control system design and Kalman filter, simulation, and implementation An accompanying website that includes MATLAB code High-end illustrations and tables throughout the text to illustrate important points Written by experts in the field of process control and state space control systems State Feedback Control and Kalman Filtering with MATLAB/Simulink Tutorials is an ideal resource for students from advanced undergraduate students to postgraduates, as well as industrial researchers and engineers in electrical, mechanical, chemical, and aerospace engineering.




Kalman Filtering


Book Description

The definitive textbook and professional reference on Kalman Filtering – fully updated, revised, and expanded This book contains the latest developments in the implementation and application of Kalman filtering. Authors Grewal and Andrews draw upon their decades of experience to offer an in-depth examination of the subtleties, common pitfalls, and limitations of estimation theory as it applies to real-world situations. They present many illustrative examples including adaptations for nonlinear filtering, global navigation satellite systems, the error modeling of gyros and accelerometers, inertial navigation systems, and freeway traffic control. Kalman Filtering: Theory and Practice Using MATLAB, Fourth Edition is an ideal textbook in advanced undergraduate and beginning graduate courses in stochastic processes and Kalman filtering. It is also appropriate for self-instruction or review by practicing engineers and scientists who want to learn more about this important topic.




Linear Feedback Control


Book Description

This book discusses analysis and design techniques for linear feedback control systems using MATLAB® software. By reducing the mathematics, increasing MATLAB working examples, and inserting short scripts and plots within the text, the authors have created a resource suitable for almost any type of user. The book begins with a summary of the properties of linear systems and addresses modeling and model reduction issues. In the subsequent chapters on analysis, the authors introduce time domain, complex plane, and frequency domain techniques. Their coverage of design includes discussions on model-based controller designs, PID controllers, and robust control designs. A unique aspect of the book is its inclusion of a chapter on fractional-order controllers, which are useful in control engineering practice.




Control Engineering


Book Description

This book offers fundamental information on the analysis and synthesis of continuous and sampled data control systems. It includes all the required preliminary materials (from mathematics, signals and systems) that are needed in order to understand control theory, so readers do not have to turn to other textbooks. Sampled data systems have recently gained increasing importance, as they provide the basis for the analysis and design of computer-controlled systems. Though the book mainly focuses on linear systems, input/output approaches and state space descriptions are also provided. Control structures such as feedback, feed forward, internal model control, state feedback control, and the Youla parameterization approach are discussed, while a closing section outlines advanced areas of control theory. Though the book also contains selected examples, a related exercise book provides Matlab/Simulink exercises for all topics discussed in the textbook, helping readers to understand the theory and apply it in order to solve control problems. Thanks to this combination, readers will gain a basic grasp of systems and control, and be able to analyze and design continuous and discrete control systems.




Model Predictive Control System Design and Implementation Using MATLAB®


Book Description

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


Book Description

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







Adaptive Control Tutorial


Book Description

Designed to meet the needs of a wide audience without sacrificing mathematical depth and rigor, Adaptive Control Tutorial presents the design, analysis, and application of a wide variety of algorithms that can be used to manage dynamical systems with unknown parameters. Its tutorial-style presentation of the fundamental techniques and algorithms in adaptive control make it suitable as a textbook. Adaptive Control Tutorial is designed to serve the needs of three distinct groups of readers: engineers and students interested in learning how to design, simulate, and implement parameter estimators and adaptive control schemes without having to fully understand the analytical and technical proofs; graduate students who, in addition to attaining the aforementioned objectives, also want to understand the analysis of simple schemes and get an idea of the steps involved in more complex proofs; and advanced students and researchers who want to study and understand the details of long and technical proofs with an eye toward pursuing research in adaptive control or related topics. The authors achieve these multiple objectives by enriching the book with examples demonstrating the design procedures and basic analysis steps and by detailing their proofs in both an appendix and electronically available supplementary material; online examples are also available. A solution manual for instructors can be obtained by contacting SIAM or the authors. Preface; Acknowledgements; List of Acronyms; Chapter 1: Introduction; Chapter 2: Parametric Models; Chapter 3: Parameter Identification: Continuous Time; Chapter 4: Parameter Identification: Discrete Time; Chapter 5: Continuous-Time Model Reference Adaptive Control; Chapter 6: Continuous-Time Adaptive Pole Placement Control; Chapter 7: Adaptive Control for Discrete-Time Systems; Chapter 8: Adaptive Control of Nonlinear Systems; Appendix; Bibliography; Index




Optimal State Estimation


Book Description

A bottom-up approach that enables readers to master and apply the latest techniques in state estimation This book offers the best mathematical approaches to estimating the state of a general system. The author presents state estimation theory clearly and rigorously, providing the right amount of advanced material, recent research results, and references to enable the reader to apply state estimation techniques confidently across a variety of fields in science and engineering. While there are other textbooks that treat state estimation, this one offers special features and a unique perspective and pedagogical approach that speed learning: * Straightforward, bottom-up approach begins with basic concepts and then builds step by step to more advanced topics for a clear understanding of state estimation * Simple examples and problems that require only paper and pen to solve lead to an intuitive understanding of how theory works in practice * MATLAB(r)-based source code that corresponds to examples in the book, available on the author's Web site, enables readers to recreate results and experiment with other simulation setups and parameters Armed with a solid foundation in the basics, readers are presented with a careful treatment of advanced topics, including unscented filtering, high order nonlinear filtering, particle filtering, constrained state estimation, reduced order filtering, robust Kalman filtering, and mixed Kalman/H? filtering. Problems at the end of each chapter include both written exercises and computer exercises. Written exercises focus on improving the reader's understanding of theory and key concepts, whereas computer exercises help readers apply theory to problems similar to ones they are likely to encounter in industry. With its expert blend of theory and practice, coupled with its presentation of recent research results, Optimal State Estimation is strongly recommended for undergraduate and graduate-level courses in optimal control and state estimation theory. It also serves as a reference for engineers and science professionals across a wide array of industries.