El-Kébir Boukas

This book deals with the analysis, the design and the implementation of the mechatronic systems. Classical and modern tools are developed for the analysis and the design for such systems. Robust control, H-Infinity and guaranteed cost control theory are also used for analysis and design of mechatronic systems. Different controller such as state feedback, static output feedback and dynamic output feedback controllers are used to stabilize mechatronic systems. Heuristic algorithms are provided to solve the design of the classical controller such as PID, phase lead, phase lag and phase lead-lag controllers while linear matrix inequalities (LMI) algorithms are provided for finding solutions to the state feedback, static output feedback and dynamic output feedback controllers. The theory presented in the different chapters of the volume is applied to numerical examples to show the usefulness of the theoretical results. Some case studies are also provided to show how the developed concepts apply for real system. Emphasis is also put on the implementation in real-time for some real systems that we have developed in our mechatronic laboratory and all the detail is provided to give an idea to the reader how to implement its own mechatronic system. Mechatronics Systems: Analysis, Design and Implementation is an excellent textbook for undergraduate and graduate students in mechatronic system and control theory and as a reference for academic researchers in control or mathematics with interest in control theory. The reader should have completed first-year graduate courses in control theory, linear algebra, and linear systems. It will also be of great value to engineers practising in fields where the systems can be modeled by linear time invariant systems.

Most practical processes such as chemical reactor, industrial furnace, heat exchanger, etc., are nonlinear stochastic systems, which makes their con­ trol in general a hard problem. Currently, there is no successful design method for this class of systems in the literature. One common alterna­ tive consists of linearizing the nonlinear dynamical stochastic system in the neighborhood of an operating point and then using the techniques for linear systems to design the controller. The resulting model is in general an approximation of the real behavior of a dynamical system. The inclusion of the uncertainties in the model is therefore necessary and will certainly improve the performance of the dynamical system we want to control. The control of uncertain systems has attracted a lot of researchers from the control community. This topic has in fact dominated the research effort of the control community during the last two decades, and many contributions have been reported in the literature. Some practical dynamical systems have time delay in their dynamics, which makes their control a complicated task even in the deterministic case. Recently, the class ofuncertain dynamical deterministic systems with time delay has attracted some researchers, and some interesting results have been reported in both deterministic and stochastic cases. But wecan't claim that the control problem ofthis class ofsystems is completely solved; more work must be done for this class of systems.

This book deals with the analysis, the design and the implementation of the mechatronic systems. Classical and modern tools are developed for the analysis and the design for such systems. Robust control, H-Infinity and guaranteed cost control theory are also used for analysis and design of mechatronic systems. Different controller such as state feedback, static output feedback and dynamic output feedback controllers are used to stabilize mechatronic systems. Heuristic algorithms are provided to solve the design of the classical controller such as PID, phase lead, phase lag and phase lead-lag controllers while linear matrix inequalities (LMI) algorithms are provided for finding solutions to the state feedback, static output feedback and dynamic output feedback controllers. The theory presented in the different chapters of the volume is applied to numerical examples to show the usefulness of the theoretical results. Some case studies are also provided to show how the developed concepts apply for real system. Emphasis is also put on the implementation in real-time for some real systems that we have developed in our mechatronic laboratory and all the detail is provided to give an idea to the reader how to implement its own mechatronic system. Mechatronics Systems: Analysis, Design and Implementation is an excellent textbook for undergraduate and graduate students in mechatronic system and control theory and as a reference for academic researchers in control or mathematics with interest in control theory. The reader should have completed first-year graduate courses in control theory, linear algebra, and linear systems. It will also be of great value to engineers practising in fields where the systems can be modeled by linear time invariant systems.

This book deals with the class of singular systems with random abrupt changes also known as singular Markovian jump systems. Various problems and their robustness are tackled. The book examines both the theoretical and practical aspects of the control problems from the angle of the structural properties of linear systems. It can be used as a textbook as well as a reference for researchers in control or mathematics with interest in control theory.

This book deals with the class of singular systems with random abrupt changes also known as singular Markovian jump systems. Various problems and their robustness are tackled. The book examines both the theoretical and practical aspects of the control problems from the angle of the structural properties of linear systems. It can be used as a textbook as well as a reference for researchers in control or mathematics with interest in control theory.

Stochastic switching systems represent an interesting class of systems that can be used to model a variety of systems having abrupt random changes in their dynamics. Such systems may be found in the fields of manufacturing, communications, aerospace, power, and economics. This work presents stochastic switching systems and provides up-to-date methods and techniques for the analysis and design of various control systems with or without uncertainties. An introductory chapter highlights basic concepts and practical models, which are then used to solve more advanced problems throughout the book. Included are many numerical examples as well as LMI analysis methods and design approaches to supplement the developed results. Stochastic Switching Systems may be used as a supplementary textbook for graduate-level engineering courses, or as a reference for control engineers, graduate students, and researchers in systems and control. Prerequisites include elementary courses in matrix theory, probability, optimization techniques, and control systems theory.

Most practical processes such as chemical reactor, industrial furnace, heat exchanger, etc., are nonlinear stochastic systems, which makes their con­ trol in general a hard problem. Currently, there is no successful design method for this class of systems in the literature. One common alterna­ tive consists of linearizing the nonlinear dynamical stochastic system in the neighborhood of an operating point and then using the techniques for linear systems to design the controller. The resulting model is in general an approximation of the real behavior of a dynamical system. The inclusion of the uncertainties in the model is therefore necessary and will certainly improve the performance of the dynamical system we want to control. The control of uncertain systems has attracted a lot of researchers from the control community. This topic has in fact dominated the research effort of the control community during the last two decades, and many contributions have been reported in the literature. Some practical dynamical systems have time delay in their dynamics, which makes their control a complicated task even in the deterministic case. Recently, the class ofuncertain dynamical deterministic systems with time delay has attracted some researchers, and some interesting results have been reported in both deterministic and stochastic cases. But wecan't claim that the control problem ofthis class ofsystems is completely solved; more work must be done for this class of systems.