Applications and Optimizations of Kalman Filter and Their Variants is a comprehensive exploration of Kalman filters’ diverse applications and refined optimizations across various domains. It meticulously examines their role in microgrid management, offering adaptive estimation techniques for effective control strategies. The book then delves into distribution system state estimation, showcasing an innovative stochastic programming model using extended Kalman filters for reliable monitoring and control. In the realm of financial modeling, readers gain insights into how Kalman filters enhance trading strategies like pairs trading and partial co-integration, bridging finance and analytics. Moreover, the book discusses Kalman filter optimization, addressing challenges in object tracking and error reduction with techniques like dynamic stochastic approximation algorithms and M-robust estimates. With practical examples and interdisciplinary approaches, this book serves as a valuable resource for researchers, practitioners, and students looking to harness Kalman filter techniques for enhanced efficiency and accuracy across diverse fields.

Sensor data fusion is the process of combining error-prone, heterogeneous, incomplete, and ambiguous data to gather a higher level of situational awareness. In principle, all living creatures are fusing information from their complementary senses to coordinate their actions and to detect and localize danger. In sensor data fusion, this process is transferred to electronic systems, which rely on some "awareness" of what is happening in certain areas of interest. By means of probability theory and statistics, it is possible to model the relationship between the state space and the sensor data. The number of ingredients of the resulting Kalman filter is limited, but its applications are not.

This book is a printed edition of the Special Issue "Road Vehicles Surroundings Supervision: On-Board Sensors and Communications" that was published in Applied Sciences

This book highlights new developments in the wide and growing field of partial differential equations (PDE)-constrained optimization. Optimization problems where the dynamics evolve according to a system of PDEs arise in science, engineering, and economic applications and they can take the form of inverse problems, optimal control problems or optimal design problems. This book covers new theoretical, computational as well as implementation aspects for PDE-constrained optimization problems under uncertainty, in shape optimization, and in feedback control, and it illustrates the new developments on representative problems from a variety of applications.

Control and Dynamic Systems: Advances in Theory and Applications, Volume 57: Multidisciplinary Engineering Systems: Design and Optimization Techniques and their Application deals with techniques used in the design and optimization of future engineering systems. Comprised of 11 chapters, this book covers techniques for improving product design quality in multidisciplinary systems. These techniques include decomposition techniques for synthesis process; optimization for aircraft systems; actuator and sensor placement; and robust techniques in system design and control process. Students, research workers, and practising engineers will find this book invaluable.

This book presents the selected proceedings of 2nd International Conference on Recent Advances in Manufacturing (RAM 2021). The book provides insights to current research trends and opportunities in modelling and optimization of manufacturing processes and systems. The topics covered include modelling analysis, computing and simulation, traditional and non-traditional optimization techniques, surface coating methods, additive manufacturing processes, CAD/CAM, robotics and automation, welding and joining processes, supply chain management and CAE and reverse engineering. This book will be a good reference for beginners, researchers and professionals interested in modelling and optimization related to manufacturing engineering and related fields.