Gerasimos Rigatos

Autonomous Electric Vehicles explores cutting-edge technologies revolutionizing transportation and city navigation. Novel solutions to the control problem of the complex nonlinear dynamics of robotized electric vehicles are developed and tested. The new control methods are free of shortcomings met in control schemes which are based on diffeomorphisms and global linearization (complicated changes of state variables, forward and backwards state-space transformations, singularities). It is shown that such methods can be used in the steering and traction system of several types of robotized electric vehicles without needing to transform the state-space model of these systems into equivalent linearized forms. It is also shown that the new control methods can be implemented in a computationally simple manner and are also followed by global stability proofs.

Robotics, mechatronics and autonomous systems can exhibit complex nonlinear dynamics which can lead to unsatisfactory transients and deviation from setpoints or even to instability. A standard approach in the control of these systems had been the concept of diffeomorphisms to bring a system into a linear form. However, these methods are not straightforward and result in complicated state-space model transformations. In this monograph, new methods have been investigated which are not constrained by the shortcomings of global linearization-based control schemes. They can be implemented in a computationally simple manner, are followed by global stability proofs, and perform better than previous optimal control approaches for a wider class of nonlinear dynamical systems and applications. In this monograph, the authors present two main proven control methods: the nonlinear optimal (H-infinity) control method, and the flatness-based control approach. These methods have shown to be better suited than previous standard approaches in solving control issues, and can be used in a wide class of dynamical systems. They can have a broad range of applications in mechatronics, industrial robotics, space robotics, robotic cranes and pendulums, autonomous vehicles, aerospace systems and satellites, power electronics, biosystems and financial systems. This very comprehensive monograph is a valuable resource for academic researchers and engineers working on control systems and estimation methods, and university staff and graduate students in the fields of control and automation, robotics and mechatronics, electrical engineering, electric power systems and power electronics, biosystems, computer science, financial systems, and physics. The monograph is also a very useful reference for skilled technical professionals developing real world applications.

Intelligent Control for Electric Power Systems and Electric VehiclesProposes new control methods that treat the control problem of the complex nonlinear dynamics of electric power systems and electric vehicles without the need for complicated state-space model transformations and changes of state variables. The proposed control schemes also foster the optimized exploitation of renewable energy sources and the reliable integration of renewable energy units in the power grid. It focuses on intelligent control techniques applicable to a wide range of electric motor systems and energy conversion units. The manuscript is suitable for teaching nonlinear control, estimation and fault diagnosis topics with emphasis to electric power systems and to electric vehicle traction and propulsion systems both at late undergraduate and postgraduate levels. Fault Diagnosis for Electric Power Systems and Electric VehiclesOffers a detailed and in-depth analysis of the topic of fault diagnosis for electric power systems and electric vehicles. It develops new fault detection and isolation methods which are addressed to a wide class of nonlinear dynamic systems, with emphasis on electric power systems and electric vehicles. Model-free fault detection and isolation methods are analyzed, processing raw data with neural networks and nonlinear regressors to create fault-free models, while statistical tests on the residuals provide objective criteria for failures; these new methods, incorporating statistical procedures for defining fault thresholds, enable early diagnosis and reveal incipient changes in monitored system parameters. Key Features: Offers timely and state-of-the-art insight on nonlinear control, nonlinear estimation and fault diagnosis for electric power systems and for electric traction and propulsion systems. Analyzes new methods of nonlinear control and offers valuable resources for researchers tackling control problems in these domains. Contains fault detection and isolation approaches that have been developed in the new monograph which can be used by researchers carrying out work on condition monitoring and fault diagnosis problems. Equips skilled technical personnel and engineers with advanced control and fault diagnosis methods, enabling them to optimize electric power systems and traction systems while addressing complex challenges in power electronics and propulsion systems.

Robotic and mechatronic systems, autonomous vehicles, electric power systems and smart grids, as well as manufacturing and industrial production systems can exhibit complex nonlinear dynamics or spatio-temporal dynamics which need to be controlled to ensure good functioning and performance. In this comprehensive reference, the authors present new and innovative control and estimation methods and techniques based on dynamical nonlinear and partial differential equation systems. Such results can be classified in five main domains for the control of complex nonlinear dynamical systems using respectively methods of approximate (local) linearization, methods of exact (global) linearization, Lyapunov stability approaches, control and estimation of distributed parameter systems and stochastic estimation and fault diagnosis methods. Control and Estimation of Dynamical Nonlinear and Partial Differential Equation Systems: Theory and applications will be of interest to electrical engineering, physics, computer science, robotics and mechatronics researchers and professionals working on control problems, condition monitoring, estimation and fault diagnosis and isolation problems. It will also be useful to skilled technical personnel working on applications in robotics, energy conversion, transportation and manufacturing.

This volume discusses advances in applied nonlinear optimal control, comprising both theoretical analysis of the developed control methods and case studies about their use in robotics, mechatronics, electric power generation, power electronics, micro-electronics, biological systems, biomedical systems, financial systems and industrial production processes. The advantages of the nonlinear optimal control approaches which are developed here are that, by applying approximate linearization of the controlled systems' state-space description, one can avoid the elaborated state variables transformations (diffeomorphisms) which are required by global linearization-based control methods. The book also applies the control input directly to the power unit of the controlled systems and not on an equivalent linearized description, thus avoiding the inverse transformations met in global linearization-based control methods and the potential appearance of singularity problems. The method adopted here also retains the known advantages of optimal control, that is, the best trade-off between accurate tracking of reference setpoints and moderate variations of the control inputs. The book's findings on nonlinear optimal control are a substantial contribution to the areas of nonlinear control and complex dynamical systems, and will find use in several research and engineering disciplines and in practical applications.

This monograph addresses problems of:• nonlinear control, estimation and filtering for robotic manipulators (multi-degree-of freedom rigid-link robots, flexible-link robots, underactuated, redundant and cooperating manipulators and closed-chain robotic mechanisms); and• nonlinear control, estimation and filtering for autonomous robotic vehicles operating on the ground, in the air, and on and under water, independently and in cooperating groups. The book is a thorough treatment of the entire range of applications of robotic manipulators and autonomous vehicles. The nonlinear control and estimation methods it develops can be used generically, being suitable for a wide range of robotic systems. Such methods can improve robustness, precision and fault-tolerance in robotic manipulators and vehicles at the same time as enabling the reliable functioning of these systems under variable conditions, model uncertainty and external perturbations.

Focused on renewable energy systems and the development of information and communication technologies (ICTs) for their integration in smart grids, this book presents recent advances and methods that help to ensure that power generation from renewable sources remains stable, that power losses are minimized, and that the reliable functioning of these power generation units is maintained. The book highlights key topics and technologies for renewable energy systems including the intelligent control of power generators, power electronics that connect renewable power generation units to the grid, and fault diagnosis for power generators and power electronics. In particular, the following topics are addressed:• Modeling and control of power generators (PMSGs, DFIGs);• Modeling and control of power electronics (converters, inverters); • Modeling and fault diagnosis of the transmission and distribution Grid; and• Modelling and control of distributed power generation units (interconnected synchronous generators or photovoltaic units). Because of the above coverage, members of the wider engineering community will find that the nonlinear control and estimation methods presented provide essential insights into the functioning of renewable energy power systems, while the academic community will find the book a valuable textbook for undergraduate or graduate courses on renewable energy systems.

This monograph addresses problems of:• nonlinear control, estimation and filtering for robotic manipulators (multi-degree-of freedom rigid-link robots, flexible-link robots, underactuated, redundant and cooperating manipulators and closed-chain robotic mechanisms); and• nonlinear control, estimation and filtering for autonomous robotic vehicles operating on the ground, in the air, and on and under water, independently and in cooperating groups. The book is a thorough treatment of the entire range of applications of robotic manipulators and autonomous vehicles. The nonlinear control and estimation methods it develops can be used generically, being suitable for a wide range of robotic systems. Such methods can improve robustness, precision and fault-tolerance in robotic manipulators and vehicles at the same time as enabling the reliable functioning of these systems under variable conditions, model uncertainty and external perturbations.

Focused on renewable energy systems and the development of information and communication technologies (ICTs) for their integration in smart grids, this book presents recent advances and methods that help to ensure that power generation from renewable sources remains stable, that power losses are minimized, and that the reliable functioning of these power generation units is maintained. The book highlights key topics and technologies for renewable energy systems including the intelligent control of power generators, power electronics that connect renewable power generation units to the grid, and fault diagnosis for power generators and power electronics. In particular, the following topics are addressed:• Modeling and control of power generators (PMSGs, DFIGs);• Modeling and control of power electronics (converters, inverters); • Modeling and fault diagnosis of the transmission and distribution Grid; and• Modelling and control of distributed power generation units (interconnected synchronous generators or photovoltaic units). Because of the above coverage, members of the wider engineering community will find that the nonlinear control and estimation methods presented provide essential insights into the functioning of renewable energy power systems, while the academic community will find the book a valuable textbook for undergraduate or graduate courses on renewable energy systems.

Incorporating intelligence in industrial systems can help to increase productivity, cut-off production costs, and to improve working conditions and safety in industrial environments. This need has resulted in the rapid development of modeling and control methods for industrial systems and robots, of fault detection and isolation methods for the prevention of critical situations in industrial work-cells and production plants, of optimization methods aiming at a more profitable functioning of industrial installations and robotic devices and of machine intelligence methods aiming at reducing human intervention in industrial systems operation. To this end, the book analyzes and extends some main directions of research in modeling and control for industrial systems. These are: (i) industrial robots, (ii) mobile robots and autonomous vehicles, (iii) adaptive and robust control of electromechanical systems, (iv) filtering and stochastic estimation for multisensor fusion and sensorless control of industrial systems (iv) fault detection and isolation in robotic and industrial systems, (v) optimization in industrial automation and robotic systems design, and (vi) machine intelligence for robots autonomy. The book will be a useful companion to engineers and researchers since it covers a wide spectrum of problems in the area of industrial systems. Moreover, the book is addressed to undergraduate and post-graduate students, as an upper-level course supplement of automatic control and robotics courses.