
Control and Estimation of Dynamical Nonlinear and Partial Differential Equation Systems
Theory and applications
Institution of Engineering and Technology (Publisher)
Published on 16. August 2022
Book
Hardback
1046 pages
978-1-83953-426-3 (ISBN)
Description
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.
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.
More details
Series
Language
English
Place of publication
Stevenage
United Kingdom
Target group
College/higher education
Professional and scholarly
Product notice
sewn/stitched
Cloth over boards
Dimensions
Height: 231 mm
Width: 163 mm
Thickness: 51 mm
Weight
1814 gr
ISBN-13
978-1-83953-426-3 (9781839534263)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
Gerasimos Rigatos is research director at the Industrial Systems Institute, Greece. He has led research cooperation projects in the areas of nonlinear control, nonlinear filtering and control of distributed parameter systems. His results have appeared in eight research monographs and more than 120 journal articles. He has held visiting professor positions at several academic institutes and is a senior member of the IEEE and a member and CEng of the IET.
Masoud Abbaszadeh is a principal research engineer at GE Research Center, Niskayuna, NY, USA. He has also held an adjunct professor position at Rensselaer Polytechnic Institute, NY, USA. His research interests include estimation and detection theory, robust and nonlinear control, and machine learning with applications in diagnostics, cyber-physical resilience and autonomous systems. He serves as an associate editor of IEEE Transactions on Control Systems Technology, and a member of IEEE CSS Conference Editorial Board.
Pierluigi Siano is a professor and scientific director of the Smart Grids and Smart Cities Laboratory with the Department of Management & Innovation Systems, University of Salerno, Italy. He is also a distinguished visiting professor in the Department of Electrical & Electronic Engineering Science, University of Johannesburg. His research activities are centered on demand response, energy management, the integration of distributed energy resources in smart grids, electricity markets and planning and management of power systems.
Masoud Abbaszadeh is a principal research engineer at GE Research Center, Niskayuna, NY, USA. He has also held an adjunct professor position at Rensselaer Polytechnic Institute, NY, USA. His research interests include estimation and detection theory, robust and nonlinear control, and machine learning with applications in diagnostics, cyber-physical resilience and autonomous systems. He serves as an associate editor of IEEE Transactions on Control Systems Technology, and a member of IEEE CSS Conference Editorial Board.
Pierluigi Siano is a professor and scientific director of the Smart Grids and Smart Cities Laboratory with the Department of Management & Innovation Systems, University of Salerno, Italy. He is also a distinguished visiting professor in the Department of Electrical & Electronic Engineering Science, University of Johannesburg. His research activities are centered on demand response, energy management, the integration of distributed energy resources in smart grids, electricity markets and planning and management of power systems.
Author
Research DirectorIndustrial Systems Institute, Unit of Industrial Automation, Greece
Principal Research EngineerGE Research Center, Niskayuna, NY, USA
ProfessorUniversity of Salerno, Department of Management & Innovation Systems, Smart Grids and Smart Cities Laboratory, Italy
Content
Chapter 1: Principles of non-linear control
Chapter 2: Control based on approximate linearization for robotic systems
Chapter 3: Control based on approximate linearization for autonomous vehicles
Chapter 4: Control based on approximate linearization in energy conversion
Chapter 5: Control based on approximate linearization for mechatronic systems
Chapter 6: Control based on global linearization for industrial and PDE systems
Chapter 2: Control based on approximate linearization for robotic systems
Chapter 3: Control based on approximate linearization for autonomous vehicles
Chapter 4: Control based on approximate linearization in energy conversion
Chapter 5: Control based on approximate linearization for mechatronic systems
Chapter 6: Control based on global linearization for industrial and PDE systems