Industrial smart data tags conforming to structured data types serve as the basis for creating a digital twin of an industrial asset. The digital twin can comprise an automation model and a mechanical model or other type of non-automation model, both of which reference the smart tags in connection with digitally modeling the industrial asset. The structured data topology offered by the smart tags allows the digital twin to be readily interfaced with artificial intelligence (AI) systems. AI analysis can leverage the smart tags to discover new relationships between key performance indicators and other variables of the asset and encode these relationships in the smart tags themselves. These enhanced smart tags can also be leveraged to perform AI-based validation the digital twin. Additional contextualization provided by the enhanced smart tags can simplify AI analysis and assist in quickly converging on desired analytic results.

An inspection-plan based inspection method includes receiving data characterizing an inspection plan associated with inspection of one or more nodes in an inspection site by an inspection device. A first step of the inspection plan includes a first set of operating parameters of the inspection device associated with the inspection of a first node of the one or more nodes and a first set of constraints associated with one or more inspection criteria at the first node by the inspection device. The method also includes generating a first control signal configured to instruct the inspection device to inspect the first node of the one or more nodes. The first control signal is based on one or more of the first set of operating parameters and a user input. The method further includes receiving data characterizing the inspection measurement of the first node by the inspection device.

A compressed air provision device (4) for carrying out a closed-loop control, in particular a closed-loop position control and/or a closed-loop pressure control, on the basis of controller parameters (RP), wherein the compressed air provision device (4) has a machine-learning model (55) and is designed to provide, using the machine-learning model (55), the controller parameters (RP) on the basis of entered system parameters (SP) which describe physical properties of a system (100) in which the compressed air provision device (4) is to be used, and to carry out the closed-loop control on the basis of the provided controller parameters (RP).

A method of additive manufacturing machine (AMM) build process control includes obtaining AMM machine and process parameter settings, accessing sensor data for monitored physical conditions in the AMM, calculating a difference between expected AMM physical conditions and elements of the monitored conditions, providing the machine and process parameter settings, monitored conditions, and differences to one or more material property prediction models, computing a predicted value or range for the monitored conditions, comparing the predicted value or range to a predetermined target range, based on a determination that predicted value(s) are within the predetermined range, maintaining the machine and process parameter settings, or based on a determination that one or more of the predicted value(s) is outside the predetermined range, generating commands to compensate the machine and process parameter settings, and repeating the closed feedback loop at intervals of time during the build process. A system and a non-transitory medium are also disclosed.

The present invention reduces the probability of malfunction occurrence when performing predictive control of a device being controlled. In this control device of one aspect of the present invention, a prediction model for a control variable is used to calculate a prediction value from a measured value of the control variable, and a desired command value of the control variable is determined by correcting a desired basic value in accordance with the calculated prediction value. The degree of correction is determined on the basis of weight. The control device controls the operation of the device being controlled according to the determined desired command value. The control device assesses whether the device being controlled is operated appropriately on the basis of monitoring data relating to the operation result of the device being controlled, and optimizes the weight of the correction to make appropriate control possible based on the assessment result.

A method to identify physical parameters of a mechanical load with integrated reliability indication includes: applying a first control signal to a mechanical device in a control circuit; measuring a first return signal; and using a power density spectrum of the first return signal to stipulate an excitation signal for the mechanical device.

A setting method according to the present invention determines a desired time response in an optimum servo control structure corresponding to a servo control structure of a control target, calculates a predetermined gain corresponding to the desired time response, and calculates a first weighting coefficient Qf, a second weighting coefficient Q, and a third weighting coefficient R of a predetermined Riccati equation according to the Riccati equation on the basis of the predetermined gain. The first weighting coefficient Qf, the second weighting coefficient Q, and the third weighting coefficient R are set as a weighting coefficient corresponding to a terminal cost, a weighting coefficient corresponding to a state quantity cost, and a weighting coefficient corresponding to a control input cost, respectively, in a predetermined evaluation function for model prediction control.

The present invention is notably directed to a computerized method for providing real-time feedback to a user from states of a model physical system, or MPS, via a computerized system comprising one or more processors and a user interface system, or UIS. The method comprises the following steps, each performed via the one or more processors. Configuration inputs are repeatedly received, to modify a configuration of the MPS, said inputs including user inputs received via said UIS. While receiving said configuration inputs: configurations of the MPS are updated based on the configuration inputs received; and a state of the MPS is repeatedly computed, whereby each computed state corresponds to a latest updated configuration that was available before starting to compute said each computed state. While repeatedly computing a state of the MPS: a surrogate function is obtained, upon completion of each computation, which surrogate function approximates a function of said each computed state; and at least one type of feedback is repeatedly provided via the UIS in respect to said user inputs received. Said at least one type of feedback is provided by sampling the configurations being updated and by evaluating a last surrogate function obtained, and/or a function derived from it, according to the sampled configurations, at a frequency compatible with real-time user-interactivity. The present invention is further directed to related computerized systems and computer program products.

The present invention is suitable for easily properly setting control parameters in short time. The simulation device of the present invention comprises: a frequency response function computing part (53) computing a frequency response function according to a first command value and a measured value of a mechanical system; an impulse response computing part (41) computing an impulse response by performing inverse Fourier transform on the frequency response function obtained according to the frequency response function and the control parameters; and a time response outputting part (44) executing time response simulation of the mechanical system (7) according to a second command value and the impulse response.

The present invention easily displays a frequency response and a time response to a user. The simulation device of the present invention comprises: a frequency response function computing part (53) computing a frequency response function according to a measured value of a response of a mechanical system (7), a time response outputting part (44) executing time response simulation, a frequency response outputting part (45) outputting a frequency response characteristic and a display control part (26) displaying the time response simulation and frequency response characteristic simultaneously or selectively.