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Robotic grippers allow industrial robots to interact with the surrounding environment. However, control architectures of the grasping force are still rare in common industrial grippers. In this context, one or more sensors (e.g., force or torque sensors) are necessary. However, the incorporation of such sensors might heavily affect the cost of the gripper, regardless of its type (e.g., pneumatic or electric). An alternative approach could be open-loop force control strategies. Hence, this work proposes an approach for optimizing the open-loop grasping force behavior of a robotic gripper. For this purpose, a specialized robotic gripper was built, as well as its mathematical model. The model was employed to predict the gripper performance during both static and dynamic force characterization, simulating grasping tasks under different experimental conditions. Both simulated and experimental results showed that by managing the mechanical properties of the finger–object contact interface (e.g., stiffness), the steady-state force variability could be greatly reduced, as well as undesired effects such as finger bouncing. Further, the object's size is not required unlike most of the grasping approaches for industrial rigid grippers, which often involve high finger velocities. These results may pave the way toward conceiving cheaper and more reliable open-loop force control techniques for use in robotic grippers. [ABSTRACT FROM AUTHOR]

This article is devoted to improving methods and models for a computer-integrated control system (CICS) that monitors the wear of heat exchange surfaces of pipes in steam boilers at coal-fired thermal power stations (TPP), in particular for coal with unknown abrasive composition. The system uses real-time coal quality data to 1manage the abrasive, optimize coal distribution, and verify coal quality to reduce costs. It is described that the difficulties faced by the global coal industry are related to quality, price and environmental issues, and the transition to sustainable energy is complicated by this diversity. Efficient power generation depends on accurate identification of fuel composition and minimizing damage from abrasive impurities in the fuel of heat exchangers. Despite the existing analytical methods, there is a need for improved diagnostic technology, which involves the integration of automated systems to improve efficiency and sustainability. The paper presents a mathematical model that calculates the effect of different types of coal and impurities on the wear of heat exchange tubes, maximizing service life and minimizing costs. It includes a Cochran sampling rule to improve coal quality control. An automated coal quality management method was also developed to reduce wear from abrasive coal impurities. It includes a stepwise supplier selection and stock utilization method, enhancing wear control using the Cochran stepwise sampling method. In addition, a fuzzy logic-based control device distributes the flow in such a way as to ensure satisfactory coal quality, emphasizing the need for continuous system monitoring. A model-based CICS has been developed that controls coal flow based on real-time impurity identification, resulting in significant cost savings and extended overhaul intervals. Computational experiments confirm that the CICS can more than double the service life of heat exchange tubes by maintaining a satisfactory thickness, thereby postponing repairs and reducing operating costs. Overall, this article presents a comprehensive approach to managing and optimizing heat exchanger tube wear at TPP using modelling, real-time data analysis, and automated control systems to improve efficiency and sustainability. [ABSTRACT FROM AUTHOR]

Robotic grippers allow industrial robots to interact with the surrounding environment. However, control architectures of the grasping force are still rare in common industrial grippers. In this context, one or more sensors (e.g., force or torque sensors) are necessary. However, the incorporation of such sensors might heavily affect the cost of the gripper, regardless of its type (e.g., pneumatic or electric). An alternative approach could be open-loop force control strategies. Hence, this work proposes an approach for optimizing the open-loop grasping force behavior of a robotic gripper. For this purpose, a specialized robotic gripper was built, as well as its mathematical model. The model was employed to predict the gripper performance during both static and dynamic force characterization, simulating grasping tasks under different experimental conditions. Both simulated and experimental results showed that by managing the mechanical properties of the finger–object contact interface (e.g., stiffness), the steady-state force variability could be greatly reduced, as well as undesired effects such as finger bouncing. Further, the object’s size is not required unlike most of the grasping approaches for industrial rigid grippers, which often involve high finger velocities. These results may pave the way toward conceiving cheaper and more reliable open-loop force control techniques for use in robotic grippers.

Model-based systems engineering is widely used in the automotive and avionics domain but less in the railway domain. This paper shows how Matlab / simulink can simulate a toy train system and then control it with the PID control algorithm. To this end, an executable model has been implemented which allows for train movement simulation, this means that the engine first went forward, then backward.

Model-based systems engineering is widely used in the automotive and avionics domain but less in the railway domain. This paper shows that Matlab/Simulink can be used to develop the mathematical model for the train system from first principles and then represented the derived equations. To this end, an executable model has been implemented which allows for train movement simulation, this means that the engine first went forward, then backward.

Model-based systems engineering is widely used in the automotive and avionics domain but less in the railway domain. This paper shows how Matlab / simulink can simulate a toy train system and then control it with the PID control algorithm. To this end, an executable model has been implemented which allows for train movement simulation, this means that the engine first went forward, then backward. [ABSTRACT FROM AUTHOR]

Model-based systems engineering is widely used in the automotive and avionics domain but less in the railway domain. This paper shows that Matlab/Simulink can be used to develop the mathematical model for the train system from first principles and then represented the derived equations. To this end, an executable model has been implemented which allows for train movement simulation, this means that the engine first went forward, then backward. [ABSTRACT FROM AUTHOR]