A system for managing communication between building management system (BMS) devices includes a memory and a controller. The memory includes instructions stored thereon. The controller is configured to execute the instructions to implement an agent manager, a zone manager, and a channel manager. The agent manager is configured to generate an agent for each of the BMS devices. The zone manager is configured to define at least one zone relating to a physical location zone or a building control zone. The channel manager is configured to generate a communication channel associated with the at least one zone. The channel manager is further configured to manage registration of an agent to the communication channel, wherein an agent is configured to communicate over a communication channel in response to being registered to the communication channel.

A motion control program that causes a computer to function as: a reception unit on a non-real-time OS that receives a control command indicating an operation to be performed by a control target device over a plurality of motion control cycles, and stores control command information indicating a content of the received control command in a control command channel that is reserved in a shared memory referable from the non-real-time OS and a real-time OS; a storage unit that obtains the control command information from the control command channel and stores it in a FIFO queue; a command processing unit that retrieves the control command information from the FIFO queue and passes it to a fixed-cycle processing unit; the fixed-cycle processing unit transmits an interpolation command to the control target device for each motion control cycle, based on the control command information.

A motion control program that causes a computer to function as: a reception unit on a non-real-time OS that receives a control command indicating an operation to be performed by a control target device over a plurality of motion control cycles, and stores control command information indicating a content of the received control command in a control command channel that is reserved in a shared memory referable from the non-real-time OS and a real-time OS; a storage unit that obtains the control command information from the control command channel and stores it in a FIFO queue; a command processing unit that retrieves the control command information from the FIFO queue and passes it to a fixed-cycle processing unit; the fixed-cycle processing unit transmits an interpolation command to the control target device for each motion control cycle, based on the control command information.

A control device includes feature amount generating means for generating a feature amount suitable for detecting an anomaly that occurs in a control target from data that relates to the control target, machine learning means for carrying out machine learning using the feature amount generated by the feature amount generating means, anomaly detecting means for detecting the anomaly, based on the feature amount generated by the feature amount generating means and an anomaly detection parameter determined based on a learning result of the machine learning and used in detection of the anomaly that occurs in the control target, instructing means for instructing the anomaly detecting means to perform detection of the anomaly, and data compressing means for data-compressing the feature amount generated by the feature amount generating means, and providing the data-compressed feature amount to the machine learning means and the anomaly detecting means.

A control device includes feature amount generating means for generating a feature amount suitable for detecting an anomaly that occurs in a control target from data that relates to the control target, machine learning means for carrying out machine learning using the feature amount generated by the feature amount generating means, anomaly detecting means for detecting the anomaly, based on the feature amount generated by the feature amount generating means and an anomaly detection parameter determined based on a learning result of the machine learning and used in detection of the anomaly that occurs in the control target, instructing means for instructing the anomaly detecting means to perform detection of the anomaly, and data compressing means for data-compressing the feature amount generated by the feature amount generating means, and providing the data-compressed feature amount to the machine learning means and the anomaly detecting means.

Systems and methods for operating a motor according to parameters provided by an autotuning component if available are described. A controller can be coupled to a drive which operates a motor for executing a task that can be related to a drilling operation for oil and gas. The controller stores initial parameters and checks for new parameters provided by the autotuning component which are stored on the drive after the autotuning component autotunes the motor. If there are new parameters, they are given priority over the initial parameters.

Systems and methods for operating a motor according to parameters provided by an autotuning component if available are described. A controller can be coupled to a drive which operates a motor for executing a task that can be related to a drilling operation for oil and gas. The controller stores initial parameters and checks for new parameters provided by the autotuning component which are stored on the drive after the autotuning component autotunes the motor. If there are new parameters, they are given priority over the initial parameters.

A control system for causing an output of a control target to follow a command includes: a first processing device which is a processing device having a first processor and a prediction model that defines a correlation between a state variable with respect to the predetermined control target and a control input to the predetermined control target in the form of a state equation, performs model predictive control using the first processor, and outputs a servo command corresponding to the control input at an initial time point of the prediction interval; and a second processing device which is a processing device having a second processor different from the first processor and a feedback system including controllers to which a feedback signal related to an operation of the predetermined control target is input and receiving the servo command from the first processing device, and performs feedback control using the second processor.

A control system for causing an output of a control target to follow a command includes: a first processing device which is a processing device having a first processor and a prediction model that defines a correlation between a state variable with respect to the predetermined control target and a control input to the predetermined control target in the form of a state equation, performs model predictive control using the first processor, and outputs a servo command corresponding to the control input at an initial time point of the prediction interval; and a second processing device which is a processing device having a second processor different from the first processor and a feedback system including controllers to which a feedback signal related to an operation of the predetermined control target is input and receiving the servo command from the first processing device, and performs feedback control using the second processor.

The present disclosure is directed to systems, methods and devices for facilitating object-based cross-domain industrial automation control. An object library comprising a plurality of objects may be maintained. One or more of the objects may represent physical counterparts for use in an industrial automation process. Each object of the plurality of objects in the object library may have at least one property that an automated control device operation can be programmed to act on. Each object of the plurality of objects may also have at least one property that a human machine interface component can utilize in generating display elements corresponding to the objects for display on the human machine interface. When modifications to objects in the object library are received, those modifications may be automatically deployed and incorporated in controller logic and HMI graphics and control.