Robotic and Autonomous Systems (RAS): Dynamic Modeling of Cyber-physical Environments

Abstract

Dynamic modeling of nonlinear systems in cyber-physical contexts is necessary for understanding and predicting complex behavior. Enabling accurate representation of intricate interactions between cyber and physical components is crucial for enhancing control systems, predicting maintenance requirements, and enhancing resilience. This article presents industrial automation and robotics, taking into account the circumstances in developing economies. The importance of studying and using industrial automation and robotics can be attributed to the complexity of today's industrial setup and the pressing demand for increased production quantity and quality. Finding current initiatives and chances for more research was the aim of the examination. When it reaches innovation maturity, there is a dearth of study on the application and adoption of automation technologies and even less on technology innovation or prototyping. A more recent development has been an increase in the amount of research being done on industrial production technologies, especially additive manufacturing. Research on non-robotic cyber-physical systems, such as IoT connection, drone technologies, and actuator and actuator technologies specifically geared towards the construction industry, is minuscule. This research significantly advances dynamic modeling methodologies by creating a comprehensive and adaptable strategy tailored to the complexities of cyber-physical systems.