Abstract: A machine learning device that learns a control command for a machine by machine learning, including a machine learning unit that performs the machine learning to output the control command; a simulator that performs a simulation of a work operation of the machine based on the control command; and a first determination unit that determines the control command based on an execution result of the simulation by the simulator.

Abstract: In some examples, a system receives first sensor data from respective wind turbines of a plurality of wind turbines. For instance, the first sensor data may include at least a power output and a wind speed per time interval. The system trains at least one respective model for each respective wind turbine based on the first sensor data received from that respective wind turbine. Further, the system receives, for a second time period, respective second sensor data from the respective wind turbines. The system executes, using the respective second sensor data, the respective model trained using the first sensor data received from that respective wind turbine to determine, for each respective wind turbine, a predicted power output for an upcoming period. The predicted power outputs may be aggregated to determine a total predicted power output and at least one action is performed based on the total predicted power output.

Abstract: Techniques are described for implementing automated control systems to control operations of specified physical target systems. In some situations, the described techniques include obtaining and analyzing sensor data about operations of a target system in order to generate an improved model of a current state of the target system, and using the modeled state information as part of determining further current and/or future automated control actions to take for the target system, such as to generate a function and/or other structure that models internal operations of the target system, rather than merely attempting to estimate target system output from input without understanding the internal structure and operations of the target system.

Abstract: Provided is a machining time prediction device including a predicted machining speed table where predicted machining speeds are registered in association with shape groups used for classification based on a shape of a machining path, a machining path generation unit generating machining path data including the machining path based on the program, a shape group determination unit determining which shape groups partial machining paths belong to, a path length addition unit adding and summarizing path lengths of the partial machining paths for the respective shape groups, a predicted machining time calculation unit calculating predicted machining times of the respective shape groups on the basis of a predicted machining speed table and the path lengths of the respective shape groups, a predicted machining time summation unit calculating a predicted machining time of the machining path by adding the predicted machining times of the respective shape groups, and a display unit displaying the predicted machining tim

Abstract: Systems and methods for controlling a generator set are disclosed herein. The method includes determining a state of local modes selectable via a local interface proximate to the generator set. The local modes include a local standby mode and a local remote enabled mode. The method also includes determining a state of a plurality of remote modes using a command from a device remote from the location of the generator set in response to determining the remote enabled mode is active. The method includes, in response to determining the local standby mode is active, the remote enabled mode is active, and one of the remote modes is active, determining whether to activate or stop the generator set based on the active remote mode and disabling the local standby mode from controlling activation of the generator set.

Abstract: Methods, apparatus and systems are disclosed for multi-module process control management. A multi-module view is presented, via a user interface, including a plurality of control modules corresponding to functions of a control process. The multi-module view provides a first set of configuration capabilities associated with the control modules, including the capability to logically connect respective ones of the control modules. In response to the selection of one of the control modules of the multi-module view, a single-module view is presented, via the user interface, including a functional block associated with the selected one of the control modules of the multi-module view. The single-module view provides a second set of configuration capabilities associated with the functional block, including the capability to logically connect the functional block to a respective one of the control modules.

Abstract: A method for optimizing component type allocation in which multiple component types of components are optimally allocated to an automatic feeder device which automatically loads the component storage tape and a manual feeder device which does automatically load when the automatic feeder device and the manual feeder device are installed installation positions on a common pallet, the method including: a workability evaluating step of evaluating a magnitude of labor in a splicing work for replenishing and connecting a new component storage tape in the manual feeder device for each of component types; and an automatic side allocating step of preferentially allocating component type having large labor in the splicing work to the automatic feeder device. Accordingly, the splicing work can be reduced by effectively using the automatic feeder device, and it can contribute to the improvement of the production efficiency of the board.

Abstract: The INTERIOR COMFORT HVAC USER-FEEDBACK CONTROL SYSTEM AND APPARATUS transforms qualitative feedback received from a user/occupant into a “comfort map,” or modifications thereto, a comfort map being defined at least in part by one or more comfort event windows. The comfort map data is used to determine a temperature setpoint sequence that avoids regions of the map corresponding to known and/or predicted regions of user discomfort.

Abstract: An HEMS 700 provided in a consumer having a gas power-generator 220 requiring start-up power for starting power generation and power supply means (PV 100, storage battery 200, PCS 400, distribution board 500) for supplying power to a load 300, and controlling the gas power-generator 220 and the power supply means, detects supply power that can be supplied by the power supply means; and controls the power supply means such that the supply power does not fall below the start-up power of the gas power-generator 220.

Abstract: Provided in some embodiments are systems and methods for emergency shutdown (ESD) systems. Embodiments provide for receiving, from a central logic solver (CLS) of an emergency shutdown (ESD) system for a plant via a first communication channel, a command indicative of a first state for an ESD valve, in response to receiving the command, controlling the ESD valve to operate in the first state, obtaining, from a central status monitor (CSM) of the ESD system via a second communication channel, current status information for the plant, determining a second state for the ESD valve based at least in part on the current status information obtained from the CSM, and controlling the ESD valve to operate in the second state.

Abstract: A method and apparatus for mapping distributed generators (DGs) to corresponding power grid feeder lines. In one embodiment, the method comprises obtaining grid data pertaining to a power grid that comprises a plurality of feeder lines; obtaining, for each distributed generator (DG) of a plurality of DGs coupled to the plurality of feeder lines, DG data pertaining to the DG; and determining, based on the grid data and the DG data, a mapping that identifies to which feeder line of the plurality of feeder lines each of the DGs of the plurality of DGs is coupled.

Abstract: A communication system includes a first remote terminal unit (RTU) outputting first RTU data, a second RTU outputting second RTU data, and a remote control center applying a first RTU weight, which is a weight for the first RTU, to the output first RTU data and a second RTU weight, which is a weight for the second RTU, to the output second RTU data, and generating state estimation information for the first and second RTUs on the basis of the first and second RTU data to which each of the first and second RTU weights are applied.

Abstract: A safety controller module for providing safety control comprises a non-volatile memory configured for storing a safety control program and one or more processing units configured to execute safety control functions associated with the safety control program to provide independent safety control. The safety controller module further comprises a connector configured to communicatively couple the safety controller module with a non-safety controller. The safety controller module is configured to communicate an input and/or an output signal of the safety controller module via the connector to the non-safety controller.

Abstract: Systems, methods, and computer program products for monitoring the tool health of on a critical dimension scanning electron microscope (CDSEM) and recipe quality on a CDSEM. Run-time data from a critical dimension scanning electron microscope is received at a computer. The computer converts the run-time data to time-sequenced data, and analyzes the time-sequenced data to detect an operational abnormality associated with the CDSEM.

Abstract: A system for providing location specific load-modifying demand response (DR) and methods for making and using same. The system advantageously can manage load on individual distribution level power circuits. Information regarding forecasted and real-time loading of individual distribution level power circuits is provided to a DR Locational Application. The DR Locational Application leverages the ability of smart devices containing real-time locational functionality, such as global positioning system, to either indicate to the consumer when it is appropriate to consume power, or automatically control the energy consumption, of the smart device along with any other loads that are verified by the smart device to be in the same location. The DR Locational Application can inform the consumer, the DR Aggregator or Crowd-Source Organization, and the distribution operator of the energy consumption sum of the response for each of its distribution level circuits.

Abstract: An information handling system includes a power supply coupled to a processor that includes a plurality of cores. A power system controller is coupled to the power supply and the processor. The power system controller may set each of the plurality of cores to a performance state that is below a highest performance state. The power system controller may then determine whether the power supplied from the power supply to the processor during operation is sufficient to operate each of the plurality of cores at the highest performance state. In response to the power being insufficient to operate each of the plurality of cores at the highest performance state, the power system controller may control the plurality of cores such that a subset operate at the highest performance state and the remainder operate at a performance state that is lower than the highest performance state.

Abstract: A system for fluid dispensing control includes a fluid dispensing control device, a fluid dispenser, and a fluid flow meter, such that an intelligent parameterization of the dispensing system includes process variables, which characterize system behavior. The parameterization is used in convergence schemes for attaining defined fluid dispensing targets. Further, the parameterization is used to attain a consistent volumetric fluid dispensing by utilizing feedback controls. A fluid dispensing device includes a processor, a non-transitory memory, an input/output, a dispensing controller, a flow monitor, a parameterization manager, and a data bus. Also disclosed is a method for fluid dispensing control, including: a parameter sweep, logging system response data, processing response data, calculating system response function, calculating dispensing parameters, assessing intrinsic variation, determining variation band, controlling fluid dispense process response, and normalizing mass/volume fluid flow.

Abstract: One embodiment of the invention relates to a trainable transceiver. The trainable transceiver includes a transceiver circuit, a user input device, a battery, and a voltage regulator circuit. The transceiver circuit is configured to reproduce and transmit control signals for operating a plurality of remote electronic devices. The user input device is configured to accept user input. The voltage regulator circuit includes a DC-DC converter configured to step up the battery voltage level, a low leakage switch configured to couple the battery and the DC-DC converter, and a temperature-sensitive current source configured to control the low leakage switch. The battery is configured to power the transceiver circuit, the user input device, and the voltage regulator circuit.

Abstract: A method for emulating one or more file system functions is provided. On a first processing device, a request is received. The request comprises a first data indicating a first file that a file system resident on the first processing device does not support. In an emulation library a second data for emulation of the first file is located. A response based upon the first and second data is formed.

Abstract: The present disclosure provides a method and system for semiconductor manufacturing automation. In one example, a method for semiconductor manufacturing automation comprises providing an identification table; defining a scheduled sequence; recording a performed sequence; and issuing a warning, if the scheduled sequence does not match the performed sequence.