In recent years, there has been growing interest in industrial systems, especially in robotic manipulators and mobile robot systems. As the cost of robots goes down and become more compact, the number of industrial applications of robotic systems increases. Moreover, there is need to design industrial systems with intelligence, autonomous decision making capabilities, and self-diagnosing properties. Intelligent Industrial Systems: Modeling, Automation and Adaptive Behavior analyzes current trends in industrial systems design, such as intelligent, industrial, and mobile robotics, complex electromechanical systems, fault diagnosis and avoidance of critical conditions, optimization, and adaptive behavior. This book discusses examples from major areas of research for engineers and researchers, providing an extensive background on robotics and industrial systems with intelligence, autonomy, and adaptive behavior giving emphasis to industrial systems design.The estimator fuses observations from multiple sensors with predictions from a nonlinear dynamic state-space model of the ... in the EKF case (Julier et al., 2000 ), (Julier aamp; Uhlmann, 2004), (van der Merwe et al., 2004), (Sarka, 2007), ( Kandepu et al., 2008). ... The concept of particle filtering comes from Monte-Carlo methods.
|Title||:||Intelligent Industrial Systems: Modeling, Automation and Adaptive Behavior|
|Publisher||:||IGI Global - 2010-06-30|