In order to improve the adaptability of diagnosis of an operating state of a field device, a field device 10 according to the present disclosure has a diagnoser 17 configured to diagnose an operating state of the field device 10 by hierarchically implementing a plurality of diagnostic processes. The diagnoser 17 can select whether to enable or disable a diagnostic result of at least one diagnostic process of a plurality of diagnostic processes in a diagnostic process after the one diagnostic process.

In order to improve the adaptability of diagnosis of an operating state of a field device, a field device 10 according to the present disclosure has a diagnoser 17 configured to diagnose an operating state of the field device 10 by hierarchically implementing a plurality of diagnostic processes. The diagnoser 17 can select whether to enable or disable a diagnostic result of at least one diagnostic process of a plurality of diagnostic processes in a diagnostic process after the one diagnostic process.

The instant disclosure relates to methods, devices, and code for controlling a coating process and, in particular, for controlling a coating process of a substrate. According to various embodiments, the method may include driving a first actuator that supplies the coating process, which is based on monitored process variables that are detected in parallel with one another. The control variables may be considered when driving the first actuator. The method may also include driving a second actuator that supplies the coating process, which is based on the detected monitored process variables. The detected monitored process variables may also be considered when driving the second actuator.

A Multi-Purpose Dynamic Simulation and run-time Control platform includes a virtual process environment coupled to a physical process environment, where components/nodes of the virtual and physical process environments cooperate to dynamically perform run-time process control of an industrial process plant and/or simulations thereof. Virtual components may include virtual run-time nodes and/or simulated nodes. The MPDSC includes an I/O Switch which delivers I/O data between virtual and/or physical nodes, e.g., by using publish/subscribe mechanisms, thereby virtualizing physical I/O process data delivery. Nodes serviced by the I/O Switch may include respective component behavior modules that are unaware as to whether or not they are being utilized on a virtual or physical node. Simulations may be performed in real-time and even in conjunction with run-time operations of the plant, and/or simulations may be manipulated as desired (speed, values, administration, etc.). The platform simultaneously supports simulation and run-time operations and interactions/intersections therebetween.

A hydrocarbon control system includes a base device, a field device, and a mobile device. The base device includes a key generator configured to generate a temporary key. The field device is configured to restrict or allow access based on verification of a received key. The mobile device is configured to communicate with the base device to receive the temporary key when in proximity of the base device, communicate with the field device to provide the temporary key to the field device when in proximity of the field device, and exchange data with the field device in response to the field device verifying the temporary key.

A method for determining conflicts in updates of a hydrocarbon control system includes obtaining a first configuration and a second configuration from different locations in the hydrocarbon control system. The method also includes comparing the first configuration and the second configuration to determine if differences are detected. If differences are detected, the method includes operating a display to notify a user that differences are detected, using conflict resolution techniques to automatically determine a resolved configuration, and updating a configuration of the hydrocarbon control system with the resolved configuration. If no differences are detected, the method includes operating the display to notify the user that no differences are detected and updating the configuration of the hydrocarbon control system with the first configuration or the second configuration.

A grinding and polishing simulation method, a grinding and polishing simulation system and a grinding and polishing process transferring method. The grinding and polishing simulation method includes the following steps. A sensing information of a grinding and polishing apparatus when grinding or polishing a workpiece is obtained. A plurality of model parameters is identified according to the sensing information. At least one quality parameter is calculated according to a machining path, a plurality of process parameters and the plurality of model parameters.

An apparatus for controlling an operation of a system is provided. The apparatus comprises an input interface configured to receive a state trajectory of the system, and a memory configured to store a model of dynamics of the system including a combination of at least one differential equation and a closure model. The apparatus further comprises a processor configured to update the closure model using reinforcement learning (RL) having a value function reducing a difference between a shape of the received state trajectory and a shape of state trajectory estimated using the model with the updated closure model, and determine a control command based on the model with the updated closure model. Further, the apparatus comprises an output interface configured to transmit the control command to an actuator of the system to control the operation of the system.

An apparatus for controlling an operation of a system is provided. The apparatus comprises an input interface configured to receive a state trajectory of the system, and a memory configured to store a model of dynamics of the system including a combination of at least one differential equation and a closure model. The apparatus further comprises a processor configured to update the closure model using reinforcement learning (RL) having a value function reducing a difference between a shape of the received state trajectory and a shape of state trajectory estimated using the model with the updated closure model, and determine a control command based on the model with the updated closure model. Further, the apparatus comprises an output interface configured to transmit the control command to an actuator of the system to control the operation of the system.

An apparatus for controlling an operation of a system is provided. The apparatus comprises an input interface configured to receive a state trajectory of the system, and a memory configured to store a model of dynamics of the system including a combination of at least one differential equation and a closure model. The apparatus further comprises a processor configured to update the closure model using reinforcement learning (RL) having a value function reducing a difference between a shape of the received state trajectory and a shape of state trajectory estimated using the model with the updated closure model, and determine a control command based on the model with the updated closure model. Further, the apparatus comprises an output interface configured to transmit the control command to an actuator of the system to control the operation of the system.