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.
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.
