A control device for a technical process, having at least two devices for detecting a respective input signal and at least one manipulated variable output device. The output device forms a difference between a reference variable and a controlled variable and ascertains a manipulated variable therefrom. The control device additionally has at least one internal signal processing system for influencing the time response and damping behavior of a control loop formed by the control device and technical process. At least two filter devices provide signal processing. A first filter device interacts with the process such that the control loop time response can be influenced by a filter device property change, and at least one amplification element interacts such that the control loop damping behavior can be influenced by an amplification element amplification factor change and such that the second filter device and the I element can be activated individually.

The present invention provides a data sorting device and method and a monitoring and diagnosis device, which are able to create a model conveniently. A data sorting device and a monitoring and diagnosis device of the present invention include an operating data database which stores operating data of the plant equipment in a time-series manner. The devices input the operating data that are highly associated physically and engineeringly among the operating data stored in the operating data database, inputting processing attributes relevant to the operating data that are highly associated physically and engineeringly, creating a model simulating characteristics of the plant equipment, and performing data sorting, monitoring, and diagnosis through use of the model.

A system and method for configuring a boiler combustion model are provided. The system for configuring the boiler combustion model may include a model generator configured to generate the boiler combustion model using, as input/output data, data obtained based on measured data, analysis data, and controller information, a model simulator configured to simulate the generated boiler combustion model and output simulated results, and a model modifier configured to evaluate the boiler combustion model based on the simulated results and generate modification information for modifying the boiler combustion model based on the generated boiler combustion model and corresponding evaluated results.

A method includes obtaining a model associated with a model-based controller in an industrial process having multiple actuator arrays and performing temporal tuning of the controller. The temporal tuning includes adjusting one or more parameters of a multivariable filter used to smooth reference trajectories of actuator profiles of the actuator arrays. The temporal tuning could also include obtaining one or more uncertainty specifications for one or more temporal parameters of the model, obtaining one or more overshoot limits for the actuator profiles, identifying a minimum bound for profile trajectory tuning parameters, and identifying one or more of the profile trajectory tuning parameters that minimize one or more measurement settling times without exceeding the one or more overshoot limits. The controller could be configured to use the adjusted parameter(s) during control of the industrial process such that the adjusting of the parameter(s) alters operation of the controller and the industrial process.

Methods, systems, and media for energy management are provided. In some embodiments, the method comprises: identifying a plurality of devices associated with a building; generating a standardized identifier for each of the plurality of devices, wherein the standardized identifier includes location information, a device type, and an index number; receiving weather data and energy pricing information; receiving, from the plurality of devices, a stream of building data, wherein each piece of building data has a data type and is associated with the standardized identifier for that device; determining whether operation of one or more of the plurality devices is to be modified based on the weather data, the energy pricing information, and the stream of building data; in response to determining that the operation of a device is to be modified based on the weather data, the energy pricing information, and the stream of building data, determining operating instructions based on the device type and the location information from the standardized identifier of the device; and transmitting the operating instructions to the device associated with the building.

A model predictive maintenance system for building equipment that performs operations including obtaining an objective function defining a cost of operating and performing maintenance on the equipment as a function of operating and maintenance decisions for time steps within a time period of a life cycle horizon and including performing a first computation of the objective function under a first scenario where maintenance is performed on the equipment during the period, a result of the first computation indicating a first cost. The operations include performing a second computation under a second scenario in which maintenance is not performed during the period, a result indicating a second cost. The operations include initiating an automated action to perform maintenance on the equipment in accordance with decisions defined by the first scenario if the first cost is less than or equal to the second cost.

A building system of a building including one or more memory devices having instructions thereon, that, when executed by one or more processors, cause the one or more processors to receive a request to access a portion of a building graph of the building from a system, the building graph including a plurality of nodes and a plurality of edges, the plurality of nodes representing entities of the building and the plurality of edges representing relationships between the entities of the building. The instructions cause one or more processors to determine whether the system has access to the portion of the building graph based on a policy indicated by the plurality of nodes and edges of the building graph and provide the portion of the building graph to the system in response to a determination that the system has access to the portion of the building graph.

A method for computer-aided control of an automation system is provided by use of a digital simulation model which simulates the automation system and which is specified by a number parameters comprising a number of configuration parameters) describing the configuration of the automation system and a number of state parameters describing the operational state of the automation system. Simulated operation runs of the automation system based on the simulation model can be performed with the aid of a computer, where a simulation run predicts a number of performance parameters of the automation system.

A temperature control device comprises: an operation amount upper limit setting part that sets an upper limit of an operation amount of a heater; and a temperature change rate comparing part that determines, in every prescribed time period, whether an actual measured change rate of the temperature of a body-to-be-heated with respect to time is outside a prescribed range that includes a target rate of change. The operation amount upper limit setting part sets the upper limit to a preset initial value when operation of the heater is started toward the target temperature, and updates the upper limit, in a period until the temperature of the body-to-be-heated reaches the target temperature, such that the difference between an actual measured temperature and a temperature locus that is represented using the target rate of change becomes smaller when it is determined that the actual measured change rate is outside the prescribed range.

The present disclosure provides a method and a system for determining a maintenance time of a pipe network of natural gas. The method may comprise: obtaining pipe network information of natural gas in at least one area, the pipe network information including a running time of the system and gas leakage information of the pipe network; extracting feature information based on the running time and the gas leakage information; generating a pipe network maintenance value through a maintenance value prediction model based on pipe network maintenance information and pipe network environment information, the pipe network maintenance value reflecting a priority of pipe network maintenance processing; and predicting the maintenance time of the pipe network based on the feature information and the pipe network maintenance value using a maintenance time prediction model, the maintenance time prediction model being a machine learning model.