Class / Patent application number | Description | Number of patent applications / Date published |
700047000 | Trainable system (e.g., self-learning, self-organizing) | 31 |
20100082125 | ANALYTICAL GENERATOR OF KEY PERFORMANCE INDICATORS FOR PIVOTING ON METRICS FOR COMPREHENSIVE VISUALIZATIONS - A guidance system of an industrial process captures process parameter data that is correlated with a human-machine interface (HMI) in order to learn how an experienced operator selects visualizations of key performance indicators (KPI) in order to take a corrective action to address an abnormal or non-optimal performance condition. Such solution learning can be invoked to recognize onset of another similar occurrence and responding by suggesting visualizations utilized by the experienced operator to diagnose the problem. Analytics can further determine which visualizations provided useful information relative to the problem. In addition, the corrective action can be suggested or automatically implemented. | 04-01-2010 |
20100249956 | ELECTRONIC OPERATOR INTERFACE BASED CONTROLLER AND DEVICE AUTOMATIC DOWNLOADS - The invention relates to systems and/or methodologies for electronic operator interface based controller and device automatic downloads. More particularly, an electronic operator interface can determine if control logic or content used by an industrial controller has been updated, changed, or otherwise modified. If the content has been modified, then the electronic operator interface can automatically obtain the content and store a back-up copy in memory. Additionally or alternatively, the electronic operator interface can periodically update a backup copy of the content. Furthermore, the electronic operator interface can determine if the controller has lost its content, and restore the content from the most recent version saved in memory. | 09-30-2010 |
20100280632 | DEVICE FOR CONTROLLING THE FLOW OF A LIQUID AND METHOD USING SAID DEVICE - The invention relates to a device and a method for controlling the flow of a liquid. In a learning phase, the flow rate of a liquid is measured for a given time period (t), the start and the end of this time period being indicated by a user. The value of the volume of liquid (V) dispensed during this time period is calculated from the duration (t) of the time period and from the flow rate measured during the time period, and this measured liquid volume value is stored as a reference value (V | 11-04-2010 |
20100324702 | LEARNING DEVICE - A learning device learns a control parameter (e.g., injection start response delay), which is used for deciding a control content of an injector (controlled object), in relation to a criterion variable (e.g., fuel pressure). The learning device has a storing section for storing a learning vector consisting of the control parameter and the criterion variable. The learning device has a measurement vector obtaining section for obtaining a measurement vector consisting of a measurement value of the control parameter and a measurement value of the criterion variable. The learning device has a correcting section for correcting the learning vector based on the measurement vector and for performing storing and updating of the learning vector in the storing section. | 12-23-2010 |
20110118857 | METHOD AND APPARATUS FOR AUTOMATION OF A PROGRAMMABLE DEVICE - A method and apparatus for a computer-implemented adaptive automation module comprising an event recorder to store one or more events for a predetermined period, and a timeline pattern generator logic to create a timeline for the predetermined period. The module further comprising marker creator logic to generate a marker to abstract the timeline data from the event data for controlling a device. | 05-19-2011 |
20110313548 | Event Prediction Using Hierarchical Event Features - Event prediction using hierarchical event features is described. In an embodiment a search engine monitors search results presented to users and whether users click on those search results. For example, features describing the search result events are universal resource locator prefix levels which are inherently hierarchically related. In an embodiment a graphical data structure is created and stored and used to represent the hierarchical relationships between features. An online training process is used in examples which enables knowledge to be propagated through the graphical data structure according to the hierarchical relations between features. In an example, the graphical data structure is used to predict whether a user will click on a search result and those predictions are used by the search engine to rank search results for future searches. In another example the events are advertisement impressions and the predictions are used by an online advertisement system. | 12-22-2011 |
20120041574 | TEMPORARY EXPANDING INTEGRATED MONITORING NETWORK - A system for monitoring an industrial process and taking action based on the results of process monitoring. Actions taken may include process control, paging, voicemail, and input for e-enterprise systems. The system includes an input module for receiving a plurality of parameters from a process for manufacture of a substance or object. The system also includes a library module. The library module includes a plurality of computer aided processes. Any one of the computer aided processes is capable of using each of the plurality of parameters to compare at least two of the plurality of parameters against a training set of parameters. The training set of parameters is generally predetermined. The computer aided process is also capable of determining if the at least two of the plurality of parameters are within a predetermined range of the training set of parameters. Additionally, the system includes an output module for outputting a result based upon the training set and the plurality of parameters. | 02-16-2012 |
20120150325 | METHOD FOR MOVING A MACHINE ELEMENT OF AN AUTOMATION MACHINE AND A CONTROL DEVICE - The invention relates to a method and a control device for moving a machine element of an automation machine by dividing an overall movement of the machine element into separately controlled first and a second movement sections extending in a common direction. Desired values for the first and second movement sections are monitored for compliance with a predefined movement constraint. If the first and/or second desired values fail to comply with the predefined movement constraint, the first movement component and/or the second movement component are changed in an iterative process until the changed first and/or second desired values are in compliance with the predefined movement constraint. The changed first and/or second desired values are stored as new first and/or second desired values for moving the machine element. The method and control device prevent overloading of the drive shafts of an automation machine having redundant kinematics. | 06-14-2012 |
20130178952 | METHOD FOR CLOSED-LOOP CONTROLLING A LASER PROCESSING OPERATION AND LASER MATERIAL PROCESSING HEAD USING THE SAME - The present invention relates to a method for closed-loop controlling a processing operation of a workpiece, comprising the steps of: (a) recording a pixel image at an initial time point of an interaction zone by means of a camera, wherein the workpiece is processed using an actuator having an initial actuator value; (b) converting the pixel image into a pixel vector; (c) representing the pixel vector by a sum of predetermined pixel mappings each multiplied by a corresponding feature value; (d) classifying the set of feature values on the basis of learned feature values into at least two classes of a group of classes comprising a first class of a too high actuator value, a second class of a sufficient actuator value and a third class of a too low actuator value at the initial time point; (e) performing a control step for adapting the actuator value by minimizing the error e | 07-11-2013 |
20130190900 | PROCESS CONTROL SYSTEMS AND METHODS HAVING LEARNING FEATURES - A system for operating a process includes a processing circuit that uses a self-optimizing control strategy to learn a steady-state relationship between an input and an output. The processing circuit is configured to switch from using the self-optimizing control strategy to using a different control strategy that operates based on the learned steady-state relationship. | 07-25-2013 |
20140074258 | ADAPTIVE AND AUTOMATIC DETERMINATION OF SYSTEM PARAMETERS - A method of automatically determining process parameters for processing equipment includes processing at least one first substrate in the processing equipment at a first time; and processing at least one second substrate in the processing equipment at a second time. The method includes collecting data on process monitors for the at least one first substrate; and the at least one second substrate. The method includes receiving the data by a multiple-input-multiple-output (MIMO) optimization system. The method includes revising a sensitivity matrix, by a MIMO optimizer, using the data and an adaptive-learning algorithm, wherein the adaptive-learning algorithm revises the sensitivity matrix based on a learning parameter which is related to a rate of change of the processing equipment over time. The method includes determining a set of process parameters for the processing equipment by the MIMO optimizer, wherein the MIMO optimizer uses the revised sensitivity matrix to determine the process parameters. | 03-13-2014 |
20140081426 | CONTROL SYSTEM AUTO-TUNING - A control system includes a controller. The controller repeatedly excites a control loop characterized by parameters having randomly selected values for each excitation and scores a response of the control loop to each excitation relative to a target signal until the scores no longer achieve a value less than a minimum of the scores for a predefined number of excitations occurring after the excitation yielding the minimum of the scores to auto-tune the control system. | 03-20-2014 |
20140114442 | REAL TIME CONTROL SYSTEM MANAGEMENT - Systems and methods for real time control system management in networked environments are disclosed. In one embodiment, a computer-based system for real time embedded control system behavior monitoring and anomaly detection comprises a processor and logic instructions stored in a tangible computer-readable medium coupled to the processor which, when executed by the processor, configure the processor to generate a behavior training set for the embedded control system, wherein the behavior training set correlates inputs to the embedded control system with outputs from the embedded control system during a training process to define behavior fingerprints for the embedded control system monitor inputs to the embedded control system and outputs from the embedded control system in real time during operation of the embedded control system, and generate an alert when one or more of the inputs into the embedded control system or the outputs collected from the embedded control system in real time operation represent an anomaly. | 04-24-2014 |
20140142726 | METHOD AND SYSTEM OF PROGRAMMING AT LEAST ONE APPLIANCE TO CHANGE STATE UPON THE OCCURRENCE OF A TRIGGER EVENT - An automation system for programming appliances having programmable controllers, programmable devices and trigger devices that communicate over a communication link. The user programs the programmable devices by placing the programmable controller in its training mode, activating the trigger device to generate a trigger signed and places select programmable devices in their programmed state. After all of the desired programmable devices have been put in then programmed states, the user takes the programmable controller out of its training mode. When the programmable controller is out of its training mode, it monitors the communication link for the trigger event. Upon detecting the trigger event, the programmable controller sends messages to the selected programmable devices instructing them to go to their programmed state. | 05-22-2014 |
20140277604 | DISTRIBUTED BIG DATA IN A PROCESS CONTROL SYSTEM - A distributed big data device in a process plant includes an embedded big data appliance configured to locally stream and store, as big data, data that is generated, received, or observed by the device, and to perform one or more learning analyses on at least a portion of the stored data. The embedded big data appliance generates or creates learned knowledge based on a result of the learning analysis, which the device may use to modify its operation to control a process in real-time in the process plant, and/or which the device may transmit to other devices in the process plant. The distributed big data device may be a field device, a controller, an input/output device, or other process plant device, and may utilize learned knowledge created by other devices when performing its learning analysis. | 09-18-2014 |
20150018982 | AUTOMATION OF A PROGRAMMABLE DEVICE - A method and apparatus for a computer-implemented adaptive automation module comprising an event recorder to store one or more events for a predetermined period, and a timeline pattern generator logic to create a timeline for the predetermined period. The module further comprising marker creator logic to generate a marker to abstract the timeline data from the event data for controlling a device. | 01-15-2015 |
20150094828 | SYSTEM FOR LEARNING EQUIPMENT SCHEDULES - Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for learning equipment schedules based on user occupancy patterns and equipment usage patterns. | 04-02-2015 |
20150112455 | CONTROL DEVICE WITH AUTOMATIC ADJUSTMENT - A control device with automatic adjustment includes: a GPS module, for receiving a GPS satellite information; and a microcontroller unit, coupled to the GPS module. The microcontroller unit updates a control setting value based on the GPS satellite information from the GPS module, and the microcontroller unit controls a controlled device based on the control setting value. | 04-23-2015 |
20150120007 | Adaptive Fall and Collision Detection and Injury Mitigation System and Method - A safety device assembly is disclosed. The assembly includes a brain signal sensor adapted to receive a first electrical signal and to transmit a first electronic signal based on the first electrical signal, a muscular signal sensor adapted to receive a second electrical signal and to transmit a second electronic signal based on the second electrical signal, and a movement sensor adapted to sense movement and to transmit a third electronic signal based on the movement. A processor is electronically coupled to the brain signal sensor, the muscular signal sensor, and the movement sensor. The processor is configured to process the first electronic signal, the second electronic signal, and the third electronic signal and generate a result. A safety device is electronically coupled to the processor such that, when the result meets a predetermined threshold, the safety device is activated. | 04-30-2015 |
20160075016 | APPARATUS AND METHODS FOR CONTEXT DETERMINATION USING REAL TIME SENSOR DATA - Computerized appliances may be operated by users remotely. In one exemplary implementation, a learning controller apparatus may be operated to determine association between a user indication and an action by the appliance. The user indications, e.g., gestures, posture changes, audio signals may trigger an event associated with the controller. The event may be linked to a plurality of instructions configured to communicate a command to the appliance. The learning apparatus may receive sensory input conveying information about robot's state and environment (context). The sensory input may be used to determine the user indications. During operation, upon determine the indication using sensory input, the controller may cause execution of the respective instructions in order to trigger action by the appliance. Device animation methodology may enable users to operate computerized appliances using gestures, voice commands, posture changes, and/or other customized control elements. | 03-17-2016 |
20160098021 | REGIONAL BIG DATA IN PROCESS CONTROL SYSTEMS - A regional big data node oversees or services, during real-time operations of a process plant or process control system, a respective region of a plurality of regions of the plant/system, where at least some of the regions each includes one or more process control devices that operate to control a process executed in the plant/system. The regional big data node is configured to receive and store, as big data, streamed data and learned knowledge that is generated, received, or observed by its respective region, and to perform one or more learning analyses on at least some of the stored data. As a result of the learning analyses, the regional big data node creates new learned knowledge which the regional big data node may use to modify operations in its respective region, and/or which the regional big data node may transmit to other big data nodes of the plant/system. | 04-07-2016 |
20160098647 | AUTOMATIC SIGNAL PROCESSING-BASED LEARNING IN A PROCESS PLANT - Techniques for automatically or autonomously performing signal processing-based learning in a process plant are disclosed. Generally, said techniques automatically or autonomously perform signal processing on a real-time signal that is generated based on the process plant controlling a process. Typically, the signal corresponds to a parameter value that varies over time, and the signal is processed as it is generated in real-time during on-line plant operations. Results of the signal processing may indicate characteristics of the signal, and one or more analytics functions may determine the sources of the characteristics, which may include a process element or device, a piece of equipment, and/or an asset of the process plant that is upstream, within the process, of the source of the signal. An autonomous signal processor may be integrated with or included in a process control device and/or a big data node of the process plant. | 04-07-2016 |
20160179083 | NUMERICAL CONTROLLER | 06-23-2016 |
700048000 | Neural network | 8 |
20080208372 | SCHEDULING WITH NEURAL NETWORKS AND STATE MACHINES - Software for controlling processes in a heterogeneous semiconductor manufacturing environment may include a wafer-centric database, a real-time scheduler using a neural network, and a graphical user interface displaying simulated operation of the system. These features may be employed alone or in combination to offer improved usability and computational efficiency for real time control and monitoring of a semiconductor manufacturing process. More generally, these techniques may be usefully employed in a variety of real time control systems, particularly systems requiring complex scheduling decisions or heterogeneous systems constructed of hardware from numerous independent vendors. | 08-28-2008 |
20090043407 | Method for Controlling an Industrial Automation Device or Process - A method for controlling an industrial automation device or process including a control unit, at least one actuator, and at least one device arranged for wireless communication with the control unit. The method determines characteristics of the wireless transmissions used to communicate sensor and/or actuator data to the control unit. The method, a system and a graphic interface enable a user to select a control strategy dependent on a value or values of the characteristics of the wireless communications. | 02-12-2009 |
20100082126 | CONTROL DEVICE, CONTROL PROGRAM, AND CONTROL METHOD - According to one embodiment, a control device that controls operation of a system includes a first selecting module, a second selecting module, a control error measuring module, a determining module, and a control module. The first selecting module selects a first neural network from neural networks different in network configuration from each other. The second selecting module selects a second neural network different from the first neural network from the neural networks. The control error measuring module measures first control error in control by the first neural network and second control error in control by the second neural network. The determining module compares the first control error and the second control error measured by the control error measuring module, and determines a neural network with less control error. The control module controls the operation of the system by the neural network with less control error determined by the determining module. | 04-01-2010 |
20100179671 | SYSTEM AND METHOD FOR EMBEDDING EMOTION IN LOGIC SYSTEMS - A system, method, and computer readable-media for creating a stable synthetic neural system. The method includes training an intellectual choice-driven synthetic neural system (SNS), training an emotional rule-driven SNS by generating emotions from rules, incorporating the rule-driven SNS into the choice-driven SNS through an evolvable interface, and balancing the emotional SNS and the intellectual SNS to achieve stability in a nontrivial autonomous environment with a Stability Algorithm for Neural Entities (SANE). Generating emotions from rules can include coding the rules into the rule-driven SNS in a self-consistent way. Training the emotional rule-driven SNS can occur during a training stage in parallel with training the choice-driven SNS. The training stage can include a self assessment loop which measures performance characteristics of the rule-driven SNS against core genetic code. The method uses a stability threshold to measure stability of the incorporated rule-driven SNS and choice-driven SNS using SANE. | 07-15-2010 |
20120065746 | CONTROL SYSTEM - A control system ( | 03-15-2012 |
20130178953 | METHOD FOR CONTROLLING A LASER PROCESSING OPERATION BY MEANS OF A REINFORCEMENT LEARNING AGENT AND LASER MATERIAL PROCESSING HEAD USING THE SAME - The present invention relates to a method for controlling a processing operation of a workpiece by means of a Reinforcement Learning (RL) agent unit, comprising the steps of: (a) observing an interaction zone in the workpiece by means of at least one radiation sensor to generate at least one sensor signal s | 07-11-2013 |
20150370227 | Controlling a Target System - For controlling a target system, such as a gas or wind turbine or another technical system, a pool of control policies is used. The pool of control policies including a plurality of control policies and weights for weighting each control policy of the plurality of control policies are received. The plurality of control policies is weighted by the weights to provide a weighted aggregated control policy. The target system is controlled using the weighted aggregated control policy, and performance data relating to a performance of the controlled target system is received. The weights are adjusted based on the received performance data to improve the performance of the controlled target system. The plurality of control policies is reweighted by the adjusted weights to adjust the weighted aggregated control policy. | 12-24-2015 |
20180024510 | MACHINE LEARNING MODEL CONSTRUCTION DEVICE, NUMERICAL CONTROL, MACHINE LEARNING MODEL CONSTRUCTION METHOD, AND NON-TRANSITORY COMPUTER READABLE MEDIUM ENCODED WITH A MACHINE LEARNING MODEL CONSTRUCTION PROGRAM | 01-25-2018 |