Distributed analytics system used to control the operation of at least one monitored system; the system includes an architect subsystem and an edge subsystem, wherein the edge subsystem comprises at least one edge processing device associated with at least one monitored system. The architect subsystem deploys at least one analytic model to an edge processing device based on characteristics of a monitored system associated with the edge processing device, the analytic model to be used by the edge processing device to provide control signals to a monitored system; and, receives information related to the monitored system from the edge processing device, the information utilized by the architect subsystem to modify the analytic model deployed to the at least one edge processing device to improve system performance of the monitored system. An edge processing device receives an analytic model from the architect subsystem; provides control signals to the monitored system according to the analytic model; and, sends information related to the monitored system to the architect subsystem, the information to be used by the architect subsystem to modify the analytic model to improve system performance of the monitored system.

The present invention is a control device which includes a filter unit for performing an attenuation process at a predetermined frequency on a control input based on a predetermined target command, generates the control input through model predictive control executed by a model predictive control unit and causes an output of a predetermined control object to follow the predetermined target command. A prediction model defines a correlation between the control input and predetermined extended state variables including a state variable related to a predetermined control object and a predetermined filter state variable related to the filter unit, and a predetermined evaluation function for model predictive controls configured to calculate a state quantity cost that is a stage cost with respect to state variables except the predetermined filter state variable among the predetermined extended state variables, and a control input cost that is a stage cost related to the control input.

A measurement sensor is integrated with a control object so that a position separated from a processing object by the control object along a target trajectory is a measurement point. A control device includes: a first generator that generates a first command position of the control object on a plane; a first control part that generates a first operation amount using a model predictive control; a second generator that generates a second command position of the control object on an orthogonal axis that is orthogonal to the plane; and a second control part that generates a second operation amount using the model predictive control. The second generator generates the second command position so that the distance between the control object and the surface of an object is constant, based on the measurement result of the measurement sensor and the first command position.

A communication system and method that provides predictive and prescriptive analytics for a system running at an edge. In one embodiment, the communication system includes an architect subsystem configured to build, test and deploy a model based on sensor characteristics of the system. The sensor characteristics are from at least one of an operator input, a historical input, a specification input, and a subject-matter expert input. The communication system also includes an edge subsystem configured to receive said model and perform predictive and prescriptive analytics on sensor data from said system running on said model deployed at said edge.

A system and a method for improving process yield and quality while reducing dependence on operator skill by automatically adjusting I.S. machine timing and motions. Container pixel data information indicative of certain measurements of hot glass containers manufactured by the I.S. machine obtained with a multipoint, multispectral glass container measurement system is mathematically transformed into a reduced dimensional measured signature. Event timing signals to operate the cavities of the section of the I.S. machine in response to the measured signature and a preferred target signature are produced to automatically adjust the event timing of operations in the cavities of the section of the I.S. machine to diminish variations in the measured signature.

Systems and methods for modeling and controlling entities of a building system are provided. An exemplary method includes comparing an input indicating a new entity or connection between entities of a building system to a data model for the building system to determine whether the new entity or connection is represented in the data model, extending the data model to define the new entity or connection in response to determining that the new entity or connection is not represented in the data model, and using the data model with the new entity or connection in a control strategy to generate control decisions for the entities of the building system.

Multiple control parts include a first control part and a second control part other than the first control part, the first control part showing the slowest response speed of a control amount with respect to a target value. A control device includes: a prediction part for predicting a future control amount for a first control target by using a first model indicating dynamic characteristics of the first control target corresponding to the first control part for each control cycle; and a generation part for generating a future target value of a second control target corresponding to the second control part from the future control amount. The second control part determines an operation amount for the second control target based on the future target value.

A measurement sensor is integrated with a control object so that a position separated from a processing object by the control object along a target trajectory is a measurement point. A control device includes: a first generator that generates a first command position of the control object on a plane; a first control part that generates a first operation amount using a model predictive control; a second generator that generates a second command position of the control object on an orthogonal axis that is orthogonal to the plane; and a second control part that generates a second operation amount using the model predictive control. The second generator generates the second command position so that the distance between the control object and the surface of an object is constant, based on the measurement result of the measurement sensor and the first command position.

A method of controlling a matrix converter system is provided. The method includes receiving an operating condition and consulting a trained Q-data structure for reward values associated with respective switching states of the switching matrix for an operating state that corresponds to the operating condition. The Q-data structure is trained using Q-learning to map a reward value predicted for respective switching states to respective discrete operating states. The method further includes sorting the reward values predicted for the respective switching states mapped to the operating state that corresponds to the operating condition, selecting a subset of the set of the mappings as a function of a result of sorting the reward values associated with the switching states of the operating state, evaluating each switching state included in the subset, and selecting an optimal switching state for the operating condition based on a result of evaluating the switching states of the subset.

Systems and methods for modeling and controlling entities of a building system are provided. An exemplary method includes comparing an input indicating a new entity or connection between entities of a building system to a data model for the building system to determine whether the new entity or connection is represented in the data model, extending the data model to define the new entity or connection in response to determining that the new entity or connection is not represented in the data model, and using the data model with the new entity or connection in a control strategy to generate control decisions for the entities of the building system.