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An all-in-one resource for designing and implementing embedded control in mobile roboticsIn Embedded Control for Mobile Robotic Applications, a distinguished trio of researchers delivers an authoritative and fulsome resource for understanding embedded control and robotics. The book includes coverage of a variety of embedded platforms, their use in controller implementation, stability analyses of designed controllers, and two new approaches for designing embedded controllers.The authors offer a full chapter on Field-Programmable-Gate-Array (FPGA) architecture development for controller design that is perfect for both practitioners and students taking robotics courses and provide a companion website that includes MATLAB codes for simulation and embedded platform-specific code for mobile robotic applications (in Embedded C and Verilog).The two approaches discussed by the authors--the top-down methodology and the bottom-up methodology--are of immediate practical utility to both practicing professionals in the field and students studying control applications and mobile robotics. The book also offers:* A thorough introduction to embedded control, including processor, IC, and design technology, as well as a discussion of limitations in embedded control design* Comprehensive explorations of the bottom-up and top-down methods, including computations using CORDIC, interval arithmetic, sliding surface design, and switched nonlinear systems* Practical discussions of generic FPGA architecture design, including Verilog, PID controllers, DC motors and Encoder, and a systematic approach for designing architecture using FSMD* In-depth examinations of discrete-time controller design, including the approximation to discrete-time transfer function and embedded implementation stabilityPerfect for practitioners working in embedded control design and control applications in robotics, Embedded Control for Mobile Robotic Applications will also earn a place in the libraries of academicians, researchers, senior undergraduate students, and graduate students in these fields.

Dynamic System Modeling & Analysis with MATLAB & PythonA robust introduction to the advanced programming techniques and skills needed for control engineeringIn Dynamic System Modeling & Analysis with MATLAB & Python: For Control Engineers, accomplished control engineer Dr. Jongrae Kim delivers an insightful and concise introduction to the advanced programming skills required by control engineers. The book discusses dynamic systems used by satellites, aircraft, autonomous robots, and biomolecular networks. Throughout the text, MATLAB and Python are used to consider various dynamic modeling theories and examples.The author covers a range of control topics, including attitude dynamics, attitude kinematics, autonomous vehicles, systems biology, optimal estimation, robustness analysis, and stochastic system. An accompanying website includes a solutions manual as well as MATLAB and Python example code.Dynamic System Modeling & Analysis with MATLAB & Python: For Control Engineers provides readers with a sound starting point to learning programming in the engineering or biology domains. It also offers:* A thorough introduction to attitude estimation and control, including attitude kinematics and sensors and extended Kalman filters for attitude estimation* Practical discussions of autonomous vehicles mission planning, including unmanned aerial vehicle path planning and moving target tracking* Comprehensive explorations of biological network modeling, including bio-molecular networks and stochastic modeling* In-depth examinations of control algorithms using biomolecular networks, including implementationDynamic System Modeling & Analysis with MATLAB & Python: For Control Engineers is an indispensable resource for advanced undergraduate and graduate students seeking practical programming instruction for dynamic system modeling and analysis using control theory.

Merging Optimization and Control in Power SystemsA novel exploration of distributed control in power systems with insightful discussions of physical and cyber restrictionsIn Merging Optimization and Control in Power Systems an accomplished team of engineers deliver a comprehensive introduction to distributed optimal control in power systems. The book re-imagines control design within the framework of cyber-physical systems with restrictions in both the physical and cyber spaces, addressing operational constraints, non-smooth objective functions, rapid power fluctuations caused by renewable generations, partial control coverage, communication delays, and non-identical sampling rates.This book bridges the gap between optimization and control in two ways. First, optimization-based feedback control is explored. The authors describe feedback controllers which automatically drive system states asymptotically to specific, desired optimal working points. Second, the book discusses feedback-based optimization. Leveraging the philosophy of feedback control, the authors envision the online solving of complicated optimization and control problems of power systems to adapt to time-varying environments.Readers will also find:* A thorough argument against the traditional and centralized hierarchy of power system control in favor of the merged approach described in the book* Comprehensive explorations of the fundamental changes gripping the power system today, including the increasing penetration of renewable and distributed generation, the proliferation of electric vehicles, and increases in load demand* Data, tables, illustrations, and case studies covering realistic power systems and experiments* In-depth examinations of physical and cyber restrictions, as well as the robustness and adaptability of the proposed modelPerfect for postgraduate students and researchers with the prerequisite knowledge of power system analysis, operation, and dynamics, convex optimization theory, and control theory, Merging Optimization and Control in Power Systems is an advanced and timely treatment of distributed optimal controller design.

Unique resource presenting advanced nonlinear control methods for power converters, plus simulation, controller design, analyses, and case studies Advanced Control of Power Converters equips readers with the latest knowledge of three control methods developed for power converters: nonlinear control methods such as sliding mode control, Lyapunov-function-based control, and model predictive control. Readers will learn about the design of each control method, and simulation case studies and results will be presented and discussed to point out the behavior of each control method in different applications. In this way, readers wishing to learn these control methods can gain insight on how to design and simulate each control method easily. The book is organized into three clear sections: introduction of classical and advanced control methods, design of advanced control methods, and case studies. Each control method is supported by simulation examples along with Simulink models which are provided on a separate website. Contributed to by five highly qualified authors, Advanced Control of Power Converters covers sample topics such as: Mathematical modeling of single- and three-phase grid-connected inverter with LCL filter, three-phase dynamic voltage restorer, design of sliding mode control and switching frequency computation under single- and double-band hysteresis modulations Modeling of single-phase UPS inverter and three-phase rectifier and their Lyapunov-function-based control design for global stability assurance Design of model predictive control for single-phase T-type rectifier, three-phase shunt active power filter, three-phase quasi-Z-source inverter, three-phase rectifier, distributed generation inverters in islanded ac microgrids How to realize the Simulink models in sliding mode control, Lyapunov-function-based control and model predictive control How to build and run a real-time model as well as rapid prototyping of power converter by using OPAL-RT simulator Advanced Control of Power Converters is an ideal resource on the subject for researchers, engineering professionals, and undergraduate/graduate students in electrical engineering and mechatronics; as an advanced level book, and it is expected that readers will have prior knowledge of power converters and control systems.

Disturbance Observer for Advanced Motion Control with MATLAB/SimulinkA fulsome and robust presentation of disturbance observers complete with MATLAB sample programs and simulation resultsIn Disturbance Observer for Advanced Motion Control with MATLAB/Simulink, distinguished electronics engineer Dr. Akira Shimada delivers a comprehensive exploration of the suppression of actual and unknown disturbances. In the book, you'll find a systematic discussion of the basic theory and design methods of disturbance observers accompanied by instructive MATLAB and Simulink simulation examples.Included appendices cover the mathematical background of classical, modern, and digital control and ground the reader's understanding of the more advanced sections. The included material is ideal for students enrolled in courses in advanced motion control, mechatronics system control, electrical drives, motion control, robotics, and aeronautics.In addition to topics like model predictive control, vibration systems, acceleration control, adaptive observers, and multi-rate sampling, readers will find:* A thorough introduction to the various types of disturbance observers and the fundamentals of disturbance observers, including disturbance estimation and disturbance rejection* Comprehensive explorations of stabilized control and coprime factorization, including the derivation of stabilizing controllers* Practical discussions of disturbance observers in state space, including identity input disturbance observers and identity reaction force observers* Fulsome treatments of the mathematical foundations of control theory, methods??for measuring and estimating velocities, and the disturbance estimation Kalman filterPerfect for undergraduate and graduate students with existing knowledge of the fundamentals of control engineering who wish to learn how to design disturbance observers, Disturbance Observer for Advanced Motion Control with MATLAB/Simulink will also benefit professional engineers and researchers studying alternative control theories.