Class / Patent application number | Description | Number of patent applications / Date published |
700031000 | Having adjustment of model (e.g., update) | 48 |
20080215166 | Process For Producing Sandwich Structures With Particulate Material Pattern - The present invention is concerned with a process for forming a very well defined pattern of particulate material in a composite material comprising a web material and particulate absorbent material. The present invention relates also to a method for determining the equipment design and process parameter for such a process. In a particular application, the present invention provides a process for preparing liquid absorbent structures, such as may be useful for disposable absorbent articles. | 09-04-2008 |
20080275575 | Determining States of a Physical System by an Observer - Determining estimations of states of a physical system ( | 11-06-2008 |
20080288091 | Control parameters for searching - An optimum control parameter in control of an internal combustion engine and the like is searched. In a plurality of search cycles, a control parameter that maximizes an output of an object to be controlled which shows an output realized by a given control parameter is searched using control parameters. The control parameters are provided at each search cycle by a predetermined algorithm. A periodic function of a predetermined period and a correction value obtained in a previous search cycle are added to the control parameters to obtain an input parameters to the object. An output obtained from the object with the input parameters is multiplied by the periodic function to obtain a correction value for correcting the control parameters such that the search converges. | 11-20-2008 |
20090037002 | METHOD AND DEVICE FOR CONTROLLING EQUIPMENT BASED ON MULTIPLE-INPUT/ONE-OUTPUT CONTROL - Combined control patterns corresponding to the actual control coordinates point (px) are formed by morphing a shape of the model control patterns PA, PB, PC having J pieces and corresponding to each morphing coordinates (pa, pb, pc), in the control pattern space CPS extended by the second type of input variable β and the output variable α. The morphing is performed according to weight between the morphing coordinates (pa, pb, pc) in the M-dimensional input space MPS and the actual control coordinates point (px). Combined control patterns Px are formed, and output variable value a corresponding to the input value (px) based on the combined control pattern Px is calculated. | 02-05-2009 |
20090105853 | PROCESS-PARAMETER PROGNOSTIC SYSTEM FOR PREDICTING SHAPE OF SEMICONDUCTOR STRUCTURE, SEMICONDUCTOR FABRICATION APPARATUS HAVING THE SYSTEM, AND METHOD OF USING THE APPARATUS - Provided are a process-parameter prognostic system for predicting the shape of a semiconductor structure, a semiconductor fabrication apparatus having the process-parameter prognostic system, and a method of using the same. The process-parameter prognostic system may have a process prediction unit and a process-change point corresponding unit. The process prediction unit and the process-change point corresponding unit may obtain predicted parameters using measured parameters of semiconductor structures and sensor parameters of plasmas corresponding to the semiconductor structures. | 04-23-2009 |
20090143873 | BATCH PROCESS MONITORING USING LOCAL MULTIVARIATE TRAJECTORIES - A system and method include determining a state of a batch process. Historical segments are retrieved from a historical database of trajectories of the batch process as a function of the state of the batch process. A model is created as a function of the retrieved historical segments. The model is used to provide state information about the batch process and may then be discarded. | 06-04-2009 |
20090143874 | System And Method For Optimizing Optical And Digital System Designs - A software product includes instructions stored on computer-readable media, that when executed by a computer, perform steps for optimizing an optical system design and a digital system design. The instructions are for simulating an optical model of the optical system design, simulating a digital model of the digital system design, analyzing simulated output of the optical model and simulated output of the digital model, to produce a score, modifying the optical model and the digital model, based upon the score, controlling re-execution of the instructions for simulating the optical model, the instructions for simulating the digital model, the instructions for analyzing and the instructions for modifying to produce an optimized optical model and an optimized digital model, and outputting predicted performance of the optimized optical and digital models. | 06-04-2009 |
20090216347 | Neuro-Fuzzy Systems - A systematic method of generating a neuro-fuzzy structure a system comprises: recording data relating sample system outputs to sample system inputs, granulating the data to identify rules relating the inputs to the outputs, measuring information loss during the granulation process to enable identification of an optimum number of rules, and constructing the network so that it has a plurality of processing elements corresponding to the rules. | 08-27-2009 |
20090216348 | Dynamically updated predictive model - Data of at least one of past values and present values of a system is consolidated from a plurality of sources. Virtual data of future values of the system is generated by applying the acquired data to a predictive model. Additional acquired data is received. The virtual data is dynamically updated by applying the additional acquired data to the predictive model. | 08-27-2009 |
20100042231 | RELIABILITY TOOLS FOR COMPLEX SYSTEMS - Tools for the maintenance of complex plants or systems are provided. A master equipment list of components included in a complex plant are organized according to systems. Those components that are critical to the function of the associated system are identified. A template modeling aspects of each critical component is prepared. Information included in applied templates can be reused in association with common or similar components. Particular information included in applied templates may include information related to critical parts within the component, and information regarding maintenance requirements and procedures associated with the component or parts included in the component. | 02-18-2010 |
20100049339 | METHOD FOR THE COMPUTER-ASSISTED CONTROL AND/OR REGULATION OF A TECHNICAL SYSTEM - A method for the computer-assisted control and/or regulation of a technical system is provided. The method is used to efficiently reduce a high-dimensional state space describing the technical system to a smaller dimension. The reduction of the state space is performed using an artificial recurrent neuronal network. In addition, the reduction of the state space enables conventional learning methods, which are only designed for small dimensions of state spaces, to be applied to complex technical systems with an initially large state space, wherein the conventional learning methods are performed in the reduced state space. The method can be used with any technical system, especially gas turbines. | 02-25-2010 |
20100049340 | Inferential Sensors Developed Using Three-Dimensional Pareto-Front Genetic Programming - A predictive algorithm for predictive at least one output variable based on a plurality of input variables is developed using a genetic programming technique that evolves a population of candidate algorithms through multiple generations. Within each generation, the candidate algorithms are evaluated based on three fitness criteria: (i) an accuracy criterion that evaluates each candidate algorithm's ability to predict historical measurements of the at least one output variable based on corresponding historical measurements of the input variables; (ii) a complexity criterion that evaluates each candidate algorithm's complexity; and (iii) a smoothness criterion that evaluates each candidate algorithm's nonlinearity. The predictive algorithm may be implemented in an inferential sensor that is used to monitor a physical, chemical, or biological process, such as an industrial process in an industrial plant. | 02-25-2010 |
20100057222 | COMPUTER METHOD AND APPARATUS FOR CONSTRAINING A NON-LINEAR APPROXIMATOR OF AN EMPIRICAL PROCESS - A constrained non-linear approximator for empirical process control is disclosed. The approximator constrains the behavior of the derivative of a subject empirical model without adversely affecting the ability of the model to represent generic non-linear relationships. There are three stages to developing the constrained non-linear approximator. The first stage is the specification of the general shape of the gain trajectory or base non-linear function which is specified graphically, algebraically or generically and is used as the basis for transfer functions used in the second stage. The second stage of the invention is the interconnection of the transfer functions to allow non-linear approximation. The final stage of the invention is the constrained optimization of the model coefficients such that the general shape of the input/output mappings (and their corresponding derivatives) are conserved. | 03-04-2010 |
20100125347 | MODEL-BASED SYSTEM CALIBRATION FOR CONTROL SYSTEMS - A system and method for model-based control of a the physical system, based on a computer simulation model approximating operating characteristics of at least a portion of the plurality of components and having one or more model parameters for adjusting a modeled operating characteristic of at least one of the plurality of components is provided. In the system and method at least one active input parameter for the physical system is generated based on current values for the model parameters and the computer simulation model and at least one measured system parameter value and at least one modeled system parameter value are obtained for measuring the performance of physical system responding to the active input parameter. The system and method also evaluate a difference between the measured system parameter value and the modeled system parameter value and update the current values for the model parameters to minimize the difference. | 05-20-2010 |
20100168876 | INFORMATION CONTROL SYSTEM AND INFORMATION CONTROL METHOD - An information control system capable of precisely defining and executing a condition for stipulating a state of an apparatus to be controlled. A storage unit stores an object definition table storing data items of a structure and a state of an object constituting a controlled system, and an actor definition table storing a monitor condition of an object state, an object monitor item and a setting value, as an actor as a control element for monitoring and controlling the object. A processing unit receives an object state from the controlled system, and when the state changes, transmits changed state value to the actor. The actor then refers to the actor definition table to judge whether the monitor condition is satisfied, and if satisfied, changes the setting value of the monitor condition and transmits a control command for setting value change to the object corresponding to the monitor item. | 07-01-2010 |
20100241251 | METHODS AND SYSTEMS FOR FAULT DIAGNOSIS IN OBSERVATION RICH SYSTEMS - Diagnostic systems and methods are presented for determining the current condition of a production plant and the resources thereof, in which successively more complex diagnostic abstractions are used to determine the plant condition, with a more complex abstraction being selected when the most recently selected diagnostic abstraction is logically inconsistent with the current fault status indications. | 09-23-2010 |
20100274367 | PROCESS SIMULATION UTILIZING COMPONENT-SPECIFIC CONSUMPTION DATA - Methods and apparatuses are provided for simulating components and processes using discrete, variable-granularity, component-specific data relating to energy consumption or other sustainability factors. Simulations can be analyzed and optimized to facilitate forecasting of sustainability factors and determine advantageous modifications to the components or processes. | 10-28-2010 |
20110130850 | APPARATUS AND METHOD FOR MODEL QUALITY ESTIMATION AND MODEL ADAPTATION IN MULTIVARIABLE PROCESS CONTROL - Apparatuses and methods for model quality estimation and model adaptation in multivariable process control are disclosed. A method for updating a multiple input multiple output (MIMO) dynamical model of a process includes perturbing the process, auditing the controller model, identifying poor performing submodels and re-testing the relevant process variables, re-identifying submodels and adapting the model online while the process continues to operate within normal operating parameters. An apparatus comprises an online multivariable controller, a tester, a database to store data corresponding to manipulated variables and controlled variables, and a performance diagnosis module configured to identify problematic submodels and adapt a model used by the controller. | 06-02-2011 |
20110218654 | Method For Optimizing A Control Program For Actuators - Method for optimizing a control program for actuators, wherein by means of the control program, at least one first function comprising the allocated program lines is executed to control a first actuator, the control program being in the form of an executable model in a first step, and, based on the model, an instrumented program code being generated by a code generator for a test control program, and a first parameter being allocated to the first function, and wherein by means of a test unit, the test control program is processed repeatedly with predefined input values and, based on the result of this processing, a value is allocated to the first parameter, and the value allocated to the first parameter is stored in a memory area allocated to the model, and in a second step, the optimized control program is generated by the code generator, the value allocated to the first parameter being read out of the allocated memory area by an optimization unit of the code generator and compared with a predefined threshold value, and then a decision is made by the optimization unit on the basis of the result of the comparison as to whether the allocated program lines are to be tied directly into the control program or tied in by means of a subprogram retrieval. | 09-08-2011 |
20120035748 | INTERACTIVE SYSTEM FOR CONTROLLING MULTIPLE INPUT MULTIPLE OUTPUT CONTROL (MIMO) STRUCTURES - Exemplary embodiments allow users to interactively formulate and solve multivariable feedback control problems. For example, users can solve problems where a plurality of control elements are distributed over one or more feedback loops and need to be jointly tuned to optimize overall performance and robustness of a control system. Embodiments allow users to specify design requirements and objectives in formats familiar to the user. Embodiments can operate on tunable parameters to solve the control problem in a manner that satisfies the design requirements and/or objectives provided by the user. | 02-09-2012 |
20120116546 | Model Predictive Control System and Method for Reduction of Steady State Error - A technique is disclosed for reducing an error in a controlled variable via model predictive control. A predicted error in the controlled variable is determined for a forward-looking control horizon based upon measured or computed variables. The integral of the predicted error is computed. If the error or the integral exceed a tolerance for a determined time period, the model predictive control algorithm is modified to drive the error or the integral to within a tolerance. The modifications to the control algorithm may include changes to coefficients for terms based upon the error and/or the integral of the error. | 05-10-2012 |
20120136462 | METHOD, ARTICLE OF MANUFACTURE, AND SYSTEM FOR CONFIGURING CONTROLLER IN SLIDING-MODE CONTROL SCHEME - Method, article of manufacture and system using minimum data to determine whether a sliding-mode control should be applied in a plant. First measure the plant in an open-loop control fashion, and using the measured data, describe a state equation of the plant by system identification and order determination methods. Then design a switching hyperplane for sliding-mode control. Next, calculate higher order statistics on the difference between an output of a linear model on the hyperplane and an output of the sliding-mode control model in the measured data; When any of the higher order moments is larger than a predetermined threshold, configure a controller as a sum of the linear control input term and the nonlinear control input term. If both higher-order moments are smaller than the threshold, then configure the controller using only a linear control input term. | 05-31-2012 |
20120150324 | Method for Solving Control Problems - A method solves a quadratic programming (QP) problem in real-time implementations of model predictive control for automation applications. The method can be implemented for fine-grained parallel solutions. Due to the extreme simplicity of the method, even serial implementations offer considerable speed advantages. The method solves the problem by formulating, over a predetermined time interval, an optimization problem with a quadratic cost function, and linear state and control constraints as a quadratic program for the application. Then, the quadratic program is solved by applying a parallel quadratic programming update law starting from a positive initial estimate to obtain control actions for the application. | 06-14-2012 |
20120221124 | USING AUTOCORRELATION TO DETECT MODEL MISMATCH IN A PROCESS CONTROLLER - A process controller adaptation and tuning technique uses a closed loop adaptation cycle that performs an autocorrelation analysis on the prediction error or the control error of a process control system to determine if significant process model mismatch exists or to determine an increase or a decrease in process model mismatch over time. The adaptation and tuning technique may perform a controller tuning cycle when the determined model mismatch raises above a predetermined level. | 08-30-2012 |
20120303142 | AUTOMATED MODEL BUILDING AND MODEL UPDATING - A system and computer-implemented method for creating a new model or updating a previously-created model based on a template are described. A template is generated from a previously-created model. The previously-created model specifies a set of parameters associated with a manufacturing process, a process tool or chamber. Variables associated with the manufacturing process are acquired, monitored, and analyzed. A statistical analysis (or multivariate statistical analysis) is employed to analyze the monitored variables and the set of parameters. When any of the monitored variables satisfy a threshold condition, a new model is created or the parameters of the previously-created model are updated, adjusted, or modified based on the template and the monitored variables. A user interface facilitating communication between a user and the systems and display of information is also described. | 11-29-2012 |
20120310376 | OCCUPANCY PREDICTION USING HISTORICAL OCCUPANCY PATTERNS - Methods and systems for occupancy prediction using historical occupancy patterns are described. In an embodiment, an occupancy probability is computed by comparing a recent occupancy pattern to historic occupancy patterns. Sensor data for a room, or other space, is used to generate a table of past occupancy which comprises these historic occupancy patterns. The comparison which is performed identifies a number of similar historic occupancy patterns and data from these similar historic occupancy patterns is combined to generate an occupancy probability for a time in the future. In an example, time may be divided into discrete slots and binary values may be used to indicate occupancy or non-occupancy in each slot. An occupancy probability for a defined future time slot then comprises a combination of the binary values for corresponding time slots from each of the identified similar occupancy patterns. | 12-06-2012 |
20130184838 | RESOURCE OPTIMIZATION USING ENVIRONMENTAL AND CONDITION-BASED MONITORING - In a method for dynamically optimizing resource utilization in a system over time according to one or more objectives, data including information indicative of current environmental conditions, upcoming environmental conditions, a current state of a system configuration, and current system operating conditions is dynamically updated. Automatic analysis of the data using a probabilistic model based on conditional relationships is performed periodically. For each periodically generated set of possible system control actions, a probabilistic model is used to automatically analyze each possible system control action and an optimal system control action is selected based on a set of current utility functions. For each periodically generated set of possible system control actions, control of the system according to the optimal system control action selected from the possible system control actions. Resource optimization couples condition-based and environmental monitoring with automated reasoning and decision making technologies, to develop real time optimal control and decision strategies. | 07-18-2013 |
20130304236 | Model-Based Learning Control - A method controls an operation of a system. The system is operated by a controller. The controller is model-based controller determined according to a model of the system. The method updates the model, during the operation, based on an extremum seeking, and updates the controller based on the updated model. | 11-14-2013 |
20130317629 | METHOD OF LARGE SCALE PROCESS OPTIMIZATION AND OPTIMAL PLANNING BASED ON REAL TIME DYNAMIC SIMULATION - This invention provides a system and method of Advanced Process Control for optimal operation of multi-unit plants in large scale processing and power generation industries. The invention framework includes the following components: continuous real time dynamic process simulation, automatic coefficient adjustment of dynamic and static process models, automatic construction of transfer functions, determination of globally optimal operating point specific to current conditions, provision of additional optimal operating scenarios through a variety of unit combinations, and calculation of operational forecasts in accordance with planned production. | 11-28-2013 |
20130325148 | EFFICIENT QUADRATIC PROGRAMMING (QP) SOLVER FOR PROCESS CONTROL AND OPTIMIZATION - A method includes identifying an initial solution to a quadratic programming (QP) problem associated with a process. The method also includes performing an iterative procedure having one or more iterations. Each iteration includes determining whether any constraint associated with the process is violated in the solution. Each iteration also includes selecting a violated constraint, determining a step direction and a step length associated with the selected violated constraint, and updating the solution based on the step direction and the step length. Determining the step direction and the step length includes using a Schur complement based on an active set of constraints associated with the solution. The Schur complement is nonsingular during all iterations of the iterative procedure except when the active set is empty. | 12-05-2013 |
20140067088 | TUNING MODEL STRUCTURES OF DYNAMIC SYSTEMS - Tuning model structures of dynamic systems are described herein. One method for tuning model structures of a dynamic system includes predicting a variable for each of a number of models associated with a number of model structures of a dynamic system, calculating a rate of error of the predicted variable for each of the number of models compared to an observed variable, determining a best model structure among the number of model structures based on the calculated rate of error, and creating a revised model structure using the best model structure to tune the number of model structures of the dynamic system. | 03-06-2014 |
20140309756 | System, Method and Apparatus for Determining Properties of Product or Process Streams - Systems, methods, and apparatuses are provided for determining properties of process streams, in particular, hydrocarbon processing streams. The systems, methods, and apparatuses frequently, for example, substantially in real-time, determine measurements for the properties of the process stream. The systems, methods, and apparatuses provide features that allow such properties of process streams to be accurately measured even as process conditions and other parameters that affect process operations change. More specifically, an analyzer having a measurement device configured to detect one or more independent variables of a process stream, a model configured to determine one or more analyzer measurements from the one or more independent variables, and a procedure to adjust the model using a corresponding primary measurement is disclosed. | 10-16-2014 |
20140330402 | Computer Apparatus And Method using Model Structure Information of Model Predictive Control - A system and method of model predictive control executes a model predictive control (MPC) controller of a subject dynamic process (e.g., processing plant) in a configuration mode, identification mode and model adaptation mode. Users input and specify model structure information in the configuration mode, including constraints. Using the specified model structure information in the identification mode, the MCP controller generates linear dynamic models of the subject process. The generated linear dynamic models collectively form a working master model. In model adaptation mode, the MPC controller uses the specified model structure information in a manner that forces control actions based on the formed working master model to closely match real-world behavior of the subject dynamic process. The MPC controller coordinates execution in identification mode and in model adaptation mode to provide adaptive modeling and preserve structural information of the model during a model update. | 11-06-2014 |
20140336789 | CONTROLLING DYNAMICAL SYSTEMS WITH BOUNDED PROBABILITY OF FAILURE - A computer-based method controls a dynamical system in an uncertain environment within a bounded probability of failure. The dynamical system has a state space and a control space. The method includes diffusing a risk constraint corresponding to the bounded probability of failure into a martingale that represents a level of risk tolerance associated with the dynamical system over time. The state space and the control space of the dynamical system are augmented with the martingale to create an augmented model with an augmented state space and an augmented control space. The method may include iteratively constructing one or more Markov Decision Processes (MDPs), with each iterative MDP represents an incrementally refined model of the dynamical system. The method further includes computing a first solution based on the augmented model or, if additional time was available, based on one of the MDP iterations. | 11-13-2014 |
20140343695 | MPC Controller Using Parallel Quadratic Programming - A method controls an operation of a machine using a model predictive control (MPC). The method determine, in response to receiving a state of the operation of the machine, a dual solution of a dual parametric problem of a parametric form of the MPC using a parallel quadratic programming (PQP) rescaling iteratively a candidate dual solution of the dual parametric problem. The coefficients of the dual parametric problem include data representing dynamics of the machine and constraints on the operation of the machine. A parameter of the dual parametric problem includes the state of the operation of the machine. The method determines a primal solution of a primal problem of the MPC using the dual solution of the dual parametric problem. | 11-20-2014 |
20150018981 | SYSTEM AND METHOD FOR FEEDBACK ERROR LEARNING IN NON-LINEAR SYSTEMS - A method for operating an actuator is disclosed. The actuator may be a linear or non-linear actuator. In one example, a pseudo-inverse piecewise bilinear model is adapted in response to output of a feedback controller to improve feed forward control. | 01-15-2015 |
20150100138 | METHODS AND SYSTEMS FOR DYNAMIC WORKFLOW PRIORITIZATION AND TASKING - A computer-implemented system includes a plurality of metrological interface devices. Each metrological interface device is in communication with a metrological sensing device configured to detect metrological data from a physical asset. The computer-implemented system also includes a portable computing device. The portable computing device is configured to a) receive a metrological data set, the metrological data set substantially representing data associated with the physical asset at a point in time, b) process the metrological data set and an asset data model into a processed metrological data set, c) upon determining, based on the processed metrological data set, a metrological variance, recalibrating the asset data model and returning to step (a), and d) upon determining no metrological variance, reporting the metrological data set and the asset data model to at least one report recipient. | 04-09-2015 |
20150148919 | METHOD AND APPARATUS FOR ARTIFICIALLY INTELLIGENT MODEL-BASED CONTROL OF DYNAMIC PROCESSES USING PROBABILISTIC AGENTS - A system and method for controlling a process such as an oil production process is disclosed. The system comprises multiple intelligent agents for processing data received from a plurality sensors deployed in a job site of an oil well, and applies a probabilistic model for evaluating risk and recommending appropriate control action to the process. | 05-28-2015 |
20150300674 | CONTROLLER AND LOOP PERFORMANCE MONITORING IN A HEATING, VENTILATING, AND AIR CONDITIONING SYSTEM - A controller and loop performance monitoring system is coupled to a controller, detects loop performance degradation in time, and diagnoses a cause of the loop performance degradation. If the cause of loop performance degradation is poor controller tuning, a re-tuning mechanism is triggered. If the cause of loop performance degradation is external to the controller (a disturbance acting on the loop, hardware malfunction etc.), an action defined in control strategy is taken, or the user is informed via alarm, user interface, or upper layer software that collects the performance measures. The monitoring itself is designed to be recursive and with low memory demands, so it can be implemented directly in the controller, without need for data transfer and storage. The monitoring is modular, consisting of oscillation detection and diagnosis part, performance indices part, internal logic part, and triggering part, easily extensible by other performance indices or parts (e.g. for overshoot monitoring). The oscillation detection and diagnosis part includes controller output oscillation monitoring, the performance indices part includes predictability index and offset index. The outputs of the controller and loop performance monitoring are overall loop performance together with loop diagnosis information, and overall controller performance together with controller diagnosis. The outputs of the controller and loop performance monitoring are used as parts of controller and loop performance monitoring user interface. | 10-22-2015 |
20150316916 | REDUCING PILOT RUNS OF RUN-TO-RUN CONTROL IN A MANUFACTURING FACILITY - A system and method for reducing pilot runs of run-to-run control in a manufacturing facility calculates an unbiased estimation of an independent model intercept based on a state space model associated with the manufacturing facility. A determination is made as to whether to perform a pilot run in the manufacturing facility. Upon determining that the run is to be performed, an indication that the pilot run is to be performed is generated. Pilot run data is received in response to the pilot run being performed, and the state space model is updated based on the received data. | 11-05-2015 |
20150338834 | SIMULATION SYSTEM - A simulation system includes a control device for controlling a control object; and an information processing device configured to exchange data with the control device. The control device includes a computation unit configured to execute sequence control and motion control of the control object; and an output unit configured to output a fixed interval of data related to the sequence control and the motion control of the object. The information processing device includes a storage module configured to store design data representing at least a portion of the configuration of the control object; and a visualization module configured to present a visual representation of the behavior of the control object around a period in time that satisfies a predetermined criteria using the fixed interval of data output from the control device, and the design data, where the fixed interval of data from the control device the visualization module uses is the fixed interval of data over a predetermined period that includes the period in time. | 11-26-2015 |
20150370228 | DETERMINING CONTROL ACTIONS OF DECISION MODULES - Techniques are described for implementing automated control systems that manipulate operations of specified target systems, such as by modifying or otherwise manipulating inputs or other control elements of the target system that affect its operation (e.g., affect output of the target system). An automated control system may have one or more decision modules that each controls at least some of a target system, with each decision module's control actions being automatically determined to reflect near-optimal solutions with respect to or one more goals and in light of a target system model having multiple inter-related constraints, such as based on a partially optimized solution that is within a threshold amount of a fully optimized solution. Such determination of one or more control actions to perform may occur for a particular time and particular decision module, as well as be repeated over multiple times for ongoing control. | 12-24-2015 |
20160041536 | Model Predictive Control with Uncertainties - A method controls a system for a multiple control steps according to the reference trajectory of a task of the operation to produce an actual trajectory of the system completing the task of the operation. For each control step, a control input to the system is determined using a model predictive control (MPC) having at least one parameter of uncertainty. The method determines a value of a learning cost function of a distance between the reference trajectory and the actual trajectory and determines, using a model free optimization, a value of the parameter of uncertainty reducing the value of the learning cost function. Next, the method determines a set of control inputs for completing the task according to the reference trajectory using the MPC with the updated parameter of uncertainty. | 02-11-2016 |
20160048113 | SYSTEM AND METHOD FOR ADVANCED PROCESS CONTROL - A system and method for performing management and diagnostic functions in an advanced process control (APC) system. An APC management computer retrieves operating process data from an APC control computer and performs an iterative step test on the APC system. The iterative step test modifies at least one test parameter of the operating process data and identifies changes to a set of remaining parameters of the operating process data resulting from modification of the test parameter. The APC management computer determines at least one process variable from the iterative step test and generates at least one process model based on the process variable. The APC management computer transmits the process model to the APC control computer. | 02-18-2016 |
20160062353 | METHOD AND SYSTEM OF ADAPTIVE MODEL-BASED CONTROL FOR MULTIPLE-INPUT MULTIPLE-OUTPUT PLANTS - A method and system for controlling a plant having a plurality of actuators, a plurality of inputs corresponding to the operational state of the actuators and plurality of outputs corresponding to an operating condition of the plant according to a model-based control and a plant model. The plant model is on-line reconfigured and the model-based control is built such that the model-based control adapts to the reconfigured plant model. | 03-03-2016 |
20160195857 | APPARATUS AND METHOD FOR MODEL ADAPTATION | 07-07-2016 |
20170235284 | METHOD AND APPARATUS FOR ARTIFICALLY INTELLIGENT MODEL-BASED CONTROL OF DYNAMIC PROCESSES USING PROBABILISTIC AGENTS | 08-17-2017 |
20180024512 | SYSTEM MODELING, CONTROL AND OPTIMIZATION | 01-25-2018 |