Abstract: A method for generating a data-based function model includes: providing a first data-based partial model ascertained from a first training data record; providing at least one additional training data record; and performing the following steps for the at least one additional training data record: ascertaining a difference training data record having training data which correspond to the differences between the output values of the relevant additional training data record and the function value of the sum of the partial function values (ffirst—partial—model(x) fsecond—partial—model(x)) of the first data-based partial model and previously ascertained data-based partial model(s) at each of the measuring points of the relevant training data record; ascertaining an additional data-based partial model from the difference training data record; and forming a sum (f(x)) from the first and the additional data-based partial models.

Abstract: A method of controlling a dynamic physical system comprising a plurality of variable quantities. A model of the system comprising a plurality of variables representing the variable quantities, and a plurality of respective rate equations that describe the rate of change of the variables, is obtained. A control term in at least one rate equation from the plurality of rate equations is identified. A rate control function is derived from, for at least one of the variables in the rate equation, the proportion of the variable to the growth rate of the rate equation, and the rate control function is applied to the control term to provide a stabilised control term. The dynamic physical system is then controlled by modifying at least one of the quantities represented by the variables in the control term, so that the control term derived from the modified quantities is substantially the same as the stabilised control term.

Abstract: A computer-implemented integrated expert system for the identification of abnormal events in an industrial plant. The expert system integrates a model-based expert system with a rule-based expert system. The model-based expert system receives data on the operating conditions of a process unit in the industrial plant and calculates one or more results that determine whether the process unit is operating abnormally. The rule-based expert system also receives data on the operating conditions of the process unit and applies its rules to the process data. The rule-based expert system also applies its rules to the one or more results generated by the model-based expert system. The integrated system may also suppress any redundant messages generated by the model-based expert system.

Abstract: A system for filtering items to be displayed on a graphical user interface provided to a client and for interaction by a user, the graphical user interface for a building automation system, is provided. The system includes a processor and memory communicably coupled to the processor. The memory includes computer code for allowing the user to create a filter definition via a computer based form. The memory further includes computer code for saving the created filter definition to memory and computer code for applying the saved filter definition to a set of building automation system data items. The memory yet further includes computer code for generating the graphical user interface, the graphical user interface including results of the applied filter definition.

Abstract: A control apparatus capable of improving the control accuracy and stability when controlling a controlled object with a predetermined restraint condition between a plurality of model parameters, or a controlled object having a lag characteristic, using a control target model of a discrete-time system. The control apparatus has an ECU which arranges a control target model including two model parameters such that terms not multiplied by the model parameters and terms multiplied by the same are on different sides of the model, respectively. Assuming the different sides represent a combined signal value and an estimated combined signal value, respectively, the ECU calculates onboard identified values of the model parameters such that an identification error between the signal values is minimized, and calculates an air-fuel ratio correction coefficient using the identified values and a control algorithm derived from the control target model.

Abstract: In the area of storage management, service automation can be realized through the use of “MAPE” loop(s). A Planner (P) interacts with the Monitoring (M), Analysis (A) and Execution (E) components in a closed loop. For each new option or potential planning action the Planner (P) invokes the Analysis (A) component. The correctness, as well as effectiveness, of the planning decision is dependent on the Analysis (A) component. Embodiments can utilize an adaptive Analysis (A) component (i.e., an analysis component that can be retrained) that also associates a value of confidence and a corresponding error in the evaluation along with a predicted impact. The Planner (P) component uses this additional information for quoting the final impact of a particular planning action as part of an adaptive MAPE loop to provide improved resource utilization and resource management.

Abstract: An automation system for creating and adapting a machine or system model, and for checking a control program of an open-loop control based on a virtual machine or a virtual system has a control system, a data recording unit for recording machine or system data, a data preparation unit for analyzing the data recorded in the data recording unit, and the parameters of the machine or system model that were ascertained via the data analysis are storable, in an automated manner, in the virtual machine or the virtual system, in order to simulate a machine or system behavior of a real machine or system.

Abstract: A current controller for controlling plural stator currents of plural stator windings of an electrical machine, in particular a generator, is provided, wherein the plural windings are separately connectable to a converter. The current controller includes a positive-sequence current controller configured to provide a first voltage command, in particular in a rotating dq+ frame, based on the plural stator currents; a negative-sequence current controller configured to provide a second voltage command, in particular in the dq+ frame, based on the plural stator currents. Further, the current controller includes a summation system for adding the first voltage command and the second voltage command to obtain a summed voltage command based on which the converter is controllable.

Abstract: A method for controlling operation of an electro-mechanical transmission configured to transfer torque among an input member, a plurality of torque machines and an output member includes determining an engine pulse torque, calculating a first motor torque pulse command based upon a first transfer function between the engine pulse torque and a torque command for a first torque machine and the engine pulse torque, calculating a second motor torque pulse command based upon a second transfer function between the engine pulse torque and a torque command for a second torque machine and the engine pulse torque, and controlling the first torque machine in response to the first motor torque pulse command and controlling the second torque machine in response to the second motor torque pulse command.

Abstract: A method for model-based control of a gas turbine engine is disclosed. An operating point of the gas turbine engine is generated from measured parameters using a component-level model. The component-level model is analytically linearized by taking the first partial derivative of output parameters of each component with respect to input parameters of each component, and evaluating the result at the operating point. Components of the linearized component-level model are combined to form a combined perturbational model of the gas turbine engine, which is inverted to solve for control commands as a function of target parameters and measured parameters.

Abstract: The embodiments described herein include one embodiment that provides a control method including determining a linear approximation of a pre-determined non-linear model of a process to be controlled, determining a convex approximation of the nonlinear constraint set, determining an initial stabilizing feasible control trajectory for a plurality of sample periods of a control trajectory, executing an optimization-based control algorithm to improve the initial stabilizing feasible control trajectory for a plurality of sample periods of a control trajectory, and controlling the controlled process by application.

Abstract: The embodiments described herein include one embodiment that provides a control method, including determining a first stabilizing feasible control trajectory of a plurality of variables of a controlled process, determining a second stabilizing feasible control trajectory for the plurality of variables for a second time step subsequent to the first time step, determining a first cost of applying the first feasible control trajectory at the second time step, determining a second cost of applying the second feasible control trajectory at the second time step, comparing the first and second costs, selecting the first feasible control trajectory or the second feasible control trajectory based upon the comparison in a predetermined time frame, and controlling the controlled process by application of the selected control trajectory.

Abstract: Systems and methods provided herein. In one embodiment, a system includes an advisory system including a loss computation engine configured to derive a total system loss for an industrial plant based on a first sensor positioned in a first industrial plant component and on a first physical model of the first industrial plant component. The advisory system further includes a cost model configured to use a cost function to derive a cost based on the total system loss, and a control strategy system configured to derive an advisory report, a control correction factor, or a combination thereof, based on the cost, wherein a control system is configured to apply the control correction factor to control a process in the industrial plant.

Abstract: A method for a real-time dynamic simulation of a response of a complex system or process controlled by a plurality of driving factors Pi (i=1 . . . k), each varying in a given range of variation. The range of variation of the driving factor Pi is discretized into NPi values. A prior parametric model of simulation is obtained in the form of a functional equation connecting the response to variations in the plurality of driving factors for any combination of values of the driving factors. Their range of variation is in the form of a sum of N modes that are functions of the factors. Each mode is defined for each of the NPi discretized values. The parametric model is stored in the form of a computer program in an independent device comprising a processor capable of running the program.

Abstract: Example methods and apparatus to execute an auxiliary recipe and a batch recipe execution are disclosed. A disclosed example method involves executing a first recipe, and before completion of execution of the first recipe, receiving an auxiliary recipe. The example method also involves determining whether the first recipe has reached an entry point at which the auxiliary recipe can be executed. The auxiliary recipe is then executed in response to determining that the first recipe has reached the entry point.

Abstract: Systems and methods are described for noninvasively assessing an intracranial pressure of a patient. Some embodiments include providing a simulation model with a measured arterial blood pressure of the patient. Some embodiments further include providing the simulation model with a measured cerebral blood flow velocity of the patient. The simulation model correlates arterial blood pressure values, cerebral blood flow velocity values, and intracranial pressure values. Some embodiments further includes determining an intracranial pressure of the patient based on the simulation model. Some embodiments further includes creating an output data set indicative of the determined intracranial pressure.

Abstract: A method and system are disclosed for tuning a Multivariable Proportional-Integral-Derivative (PID) controller in a process plant. The plant can have at least one PID controller for controlling the processes of the plant. The method can include formulating Model Predictive Control (MPC) for the process model of the plant; obtaining a desired (e.g., optimal control) solution for at least one designated (e.g., critical) region in relation to the MPC; determining PID tuning parameters corresponding to the control solution; and tuning the PID controller with the PID tuning parameters.

Abstract: A control system is described for controlling the operation of a target system, such as a data center. The control system uses a prediction module to predict demand for resources of the target system for future time steps. The control system then uses a transition determination module to determine state transitions within the target system to address the predicted demand. Each state transition describes a number of units to be advanced from a first state, at a first time step, to a second state, at a second time step. The control system then commences those state transitions which begin in the current step, and then repeats the predicting and determining for a next time step. The transition determination module can determine the state transitions by operating on an objective function that includes a demand difference component and a cost component, as subject to a set of conservation equations.

Abstract: An adaptive control device and adaptive control method, and a control device of an injection molding machine, which allow optimal adaptive control to be performed automatically and easily, while preventing a degradation of responsiveness. The adaptive control device is configured to perform feedback control in such a manner that an operation value is output based on a command value and a feedback value which is a sum of a controlled value output from a controlled target and a compensation value output from a parallel feed-forward compensator; wherein the parallel feed-forward compensator includes: an identification section which sequentially estimates a frequency response characteristic of the controlled target and an adjustment section which adjusts the compensation value based on the estimated frequency response characteristic.

Abstract: A method of controlling and managing a process control system having a plurality of control loops includes implementing a plurality of control routines to control operation of the plurality of control loops, respectively, wherein the control routines may include at least one non-adaptive control routine. The method then collects operating condition data in connection with the operation of each control loop, and identifies a respective process model for each control loop from the respective operating condition data collected for each control loop. The identification of the respective process models may be automatic as a result of a detected process change or may be on-demand as a result of an injected parameter change. The process models are then analyzed to measure or determine the operation of the process control loops.

Abstract: A damping apparatus that supports and dampens a stage apparatus that positions and drives a stage to a target position is provided herein. The damping apparatus including a support plate part, a support force generating means, and a first controlling means. The support plate part supports the stage apparatus. The support force generating means exerts a damping action by applying a support force to the support plate part in the vertical directions. The first controlling means uses the acceleration of the stage, which is derived from a target track, to the target position, to control the support force generated by the support force generating means so as to compensate for forces that both occur as a result of the acceleration of the stage and cause the support plate part to tilt. The present invention controls vibration and the tilt of a base plate with high precision.

Abstract: Within a mechanical control system, continuous adaptive digital to analog control may control an analog actuated device by comparing a current value for a process variable to a setpoint value to obtain an error value, wherein the process variable may represent a monitored condition controlled by an analog actuated device. Continuous adaptive digital to analog control may also include converting the error value into a digital pulse time value representing a correction to compensate for the error value. The error value may be converted using a gain factor derived from timing characteristics for the actuated device. An analog value may be output based on a previously output value and the digital pulse time value. Continuous adaptive digital to analog control may repeatedly adjust the actuated device according to the changing values for the process variable.

Abstract: A system, method and computer program product for predicting at least one feature of at least one product being manufactured. The system receives, from at least one sensor installed in equipment performing one or more manufacturing process steps, at least one measurement of the feature of the product being manufactured. The system selects one or more of the received measurement of the feature of the product. The system estimates additional measurements of the feature of the product at a current manufacturing process step. The system creates a computational model for predicting future measurements of the feature of the product, based on the selected measurement and the estimated additional measurements. The system predicts the future measurements of the feature of the product based on the created computational model. The system outputs the predicted future measurements of the feature of the product.

Abstract: A mobile station and methods are disclosed for diagnosing and modeling site specific effluent treatment facility requirements to arrive at a treatment regimen and/or proposed commercial plant model idealized for the particular water/site requirements. The station includes a mobile platform having power intake, effluent intake and fluid outflow facilities and first and second suites of selectably actuatable effluent pre-treatment apparatus. An effluent polishing treatment array is housed at the station and includes at least one of nanofiltration, reverse osmosis and ion-exchange stages. A suite of selectively actuatable post-treatment apparatus is housed at the station. Controls are connected at the station for process control, monitoring and data accumulation. A plurality of improved water treatment technologies is also disclosed.

Abstract: Guidance System for controlling output variables of single-input single-output or multi-input multi-output processes, where the process parameters are known or unknown and time-varying. The guidance system of the present invention generates a desired trajectory for a process output variable, and based on said desired trajectory, computes a set point for the derivative variable of said process output variable. This set point is then applied to a model based advanced controller for said derivative variable and the control action generated by said model based advanced controller is applied to the process and guides the process evolution in such a way that said process output variable converges towards said desired trajectory.

Abstract: A modeling tool for determining the operation of a production facility. A variety of different activities can be modeled, including (a) feed material selection, including quantity and timing, (b) product sales, including quantity and timing, (c) process operations, including process conditions and timing, (d) blending operations, including process conditions and timing, and/or (e) inventory management. The modeling tool may represent time using continuous-time, discrete-time, asynchronous time periods, synchronous time periods, and combinations of these various approaches.

Abstract: A method and apparatus capable of monitoring performance of a process and of the condition of equipment units effecting such process is disclosed. A process model predicated upon mass and energy balancing is developed on the basis of a plurality of generally nonlinear models of the equipment units. At least one or more of such equipment models are characterized by one or more adjustable maintenance parameters. Data relating to mass and energy transfer within the process is collected and is reconciled with the mass and energy characteristics of the process predicted by the model. The condition of the equipment units and process performance may then be inferred by monitoring the values of the maintenance parameters over successive data reconciliation operations.

Abstract: A system, method, and device for generating a signal processing network for deployment on a motion control system are disclosed. The exemplary system may have a module that supplies one or more signal processing units represented in data format using existing compiled and linked code. Another module provides a dedicated interface with the motion control system. The system may also have a module that supplies each signal processing unit with multiple inputs and multiple outputs and a module that routes the inputs and the outputs between the one or more signal processing units.

Abstract: The CV-CAD (computer vision-computer-aided design) model is an enhanced CAD (computer-aided design) model that integrates local and global computer vision data in order to represent an object not only geometrically but also in terms of computer vision. The CV-CAD model provides a scalable solution for intelligent and automatic object recognition, tracking and augmentation based on generic models of objects.

Abstract: The invention relates to linear programming methods and systems. The linear programming model has at least one input streams, at least one intermediate stream, and at least one output stream. The linear programming model is utilized for simulating the effect of withdrawing at least a portion of an intermediate steam on one or more of the model's outputs.

Abstract: There is a method to model large electric power consuming facilities for power system studies. A general facility model, for example a template, is created for different types of industrial or commercial facilities. A template includes all necessary and general electric system information such as the common electric network configuration of a specific type of facilities. The template, stored in a database, is then scaled and adjusted based on the power demand level of the case-specific facility to be modeled based on facility specific parameters acquired for the facility. The result is a full, case-specific model of the facility to be modeled. The case-specific model is simplified into an equivalent model with varying details according to a user's specification. The results are the case-specific facility model of interest to the user. The model is normally included into the power system model of the utility network for power system simulation studies.

Abstract: A control device for controlling an electric machine with ks windings on a stator and kr windings on a rotor, where ks+kr=n and either ks or kr may be zero, includes an input for receiving commands, an output for outputting control commands to a driver, machine modeling means for modeling behavior of the machine, and decision means connected to the input, output, and machine modeling means for determining the driver control commands. The machine modeling means models behavior of the machine through functional mapping suited for correlating sets of values of electrical and mechanical quantities, sets of values of their total or partial derivatives and/or integral functions with one another. The functional mapping includes an algorithm and/or equation based on at least one state function associated with the electromagnetic field inside the machine and/or based on at least one partial derivative of the state function.

Abstract: A system includes host and learning machines in electrical communication with sensors positioned with respect to an item of interest, e.g., a weld, and memory. The host executes instructions from memory to predict a binary quality status of the item. The learning machine receives signals from the sensor(s), identifies candidate features, and extracts features from the candidates that are more predictive of the binary quality status relative to other candidate features. The learning machine maps the extracted features to a dimensional space that includes most of the items from a passing binary class and excludes all or most of the items from a failing binary class. The host also compares the received signals for a subsequent item of interest to the dimensional space to thereby predict, in real time, the binary quality status of the subsequent item of interest.

Abstract: A method for defining XML-based models of logical type hierarchies, business objects and sub-objects, business object operations, enumerations and reusable structures and field-sets. The method defines an optimal, yet extensible, structure of the object models to simplify the modeling process by capturing the most essential elements of the model and inferring any additional information, such as relationship between objects, during the process of generating code, database scripts or other system artifacts from the model. Methods of generating a relational model and a presentation data model from such a business object model.

Abstract: The current application is directed to intelligent controllers that continuously, periodically, or intermittently calculate and display the time remaining until a control task is projected to be completed by the intelligent controller. In general, the intelligent controller employs multiple different models for the time behavior of one or more parameters or characteristics within a region or volume affected by one or more devices, systems, or other entities controlled by the intelligent controller. The intelligent controller collects data, over time, from which the models are constructed and uses the models to predict the time remaining until one or more characteristics or parameters of the region or volume reaches one or more specified values as a result of intelligent controller control of one or more devices, systems, or other entities.

Abstract: Dynamic parameter tuning using particle swarm optimization is disclosed. According to one embodiment, a system for dynamically tuning parameters comprising a control unit; and a system for receiving parameters tuned by the control unit. The control unit receives as input a model selection and definitions, and dynamically tunes a value for each parameter by using a modified particle swarm optimization method. The modified particle swarm optimization method comprises moving particle locations based on a particle's inertia, experience, global knowledge, and a tuning factor. The control unit outputs the dynamically tuned value for each parameter.

Abstract: A method and system for controlling a temperature of an exhaust gas being introduced to a catalyst is provided. Using an adjustable flow controller, an adjustable amount of tempering fluid is provided to the exhaust gas prior to the exhaust gas proceeding to the catalyst. A sensor senses a parameter indicative of a temperature of the exhaust gas being introduced to the catalyst. A computer processor uses a relationship to relate the parameter to an adjustment of the adjustable flow controller that will adjust the amount of tempering fluid provided to the exhaust gas and change the temperature of the exhaust gas being introduced to the catalyst toward a target temperature. Adjustment of the adjustable flow controller is initiated by the computer processor to change the flow of the tempering fluid, and the relationship between the parameter and the adjustment of the adjustable flow controller is updated.

Abstract: Techniques for generating a dynamic treatment control policy for a cyber-physical system having one or more components, including a data collector for collecting data representative of the cyber-physical system, and adaptive stochastic controller including one or more models for generating a predicted value corresponding to available actions based on an objective function, and an approximate dynamic programming element configured to receive actual operation metrics corresponding to the available actions. The approximate dynamic programming element can learn a state-action map and generate a dynamic treatment control policy using the one or more models.

Abstract: Technology for predicting and correcting a trajectory is described. The technology can create a model to predict a position of the reusable launch vehicle at a time in the future; observe a wind condition during ascent of the reusable launch vehicle; store the observed wind condition in a wind map; predict during ascent a position and a terminal lateral velocity of the reusable launch vehicle at a terminal altitude; and correct a flight trajectory of the reusable launch vehicle based on the wind map.

Abstract: A plurality of real control inputs and real process measurements provided by a real automation system controlling an industrial process are continuously stored continuously storing in a historian database. At the same time, a plurality of forecast control inputs and process measurements provided by a virtual automation system based on a simulation model are continuously stored in a futurian database. Both the past operation of the industrial process up to present time based on data from the historian database and the forecast future operation of the industrial process from the present time onwards based on data from the futurian database are displayed on the operator screen.

Abstract: A plant control apparatus includes a plant model and a control input determining device. The plant model estimates a control variable of a plant based on an input including a control parameter to adjust a first control variable of the plant. The control input determining device is configured to correct a temporary value of the control parameter so that a first control variable model value satisfies a predetermined constraint. The control input determining device is configured to determine a control input for the plant based on the temporary value of the control parameter that has been corrected. The first control variable model value is defined as an estimated value of the first control variable calculated by the plant model when the temporary value of the control parameter is input to the plant model.

Abstract: In certain embodiments, a control/optimization system includes an instantiated model object stored in memory on a model server. The model object includes a model of a plant or process being controlled. The model object comprises an interface that precludes the transmission of proprietary information via the interface. The control/optimization system also includes a decision engine software module stored in memory on a decision support server. The decision engine software module is configured to request information from the model object through a communication network via a communication protocol that precludes the transmission of proprietary information, and to receive the requested information from the model object through the communication network via the communication protocol.

Abstract: In one embodiment, the present invention is a method and apparatus for layering agents in a distributed computing system. In one embodiment, a system for monitoring and controlling a distributed computer network including a plurality of components (e.g., devices) includes a plurality of cells, each of the cells being deployed to directly monitor and control one of the components of the network. The system also includes at least one federation, where the federation is made up of cells that cooperate to solve common problems, and at least one supercell, where the supercell provides supplemental decision making capabilities to the cells and federations. In this manner, problems detected by a cell that cannot be resolved by the cell may be forwarded to the cell's associated federations or supercells for resolution.

Abstract: A method of controlling a process control system having a plurality of control loops includes collecting operating condition data in connection with the operation of each control loop of the plurality of control loops, identifying a respective process model for each control loop of the plurality of control loops from the respective operating condition data collected for each control loop of the plurality of control loops and developing a process model history by storing data indicative of the multiple identified process models for each control loop of the plurality of control loops.

Abstract: A computing-device implemented method may include receiving an instruction and dynamically performing tests in a modeling environment in response to the instruction. The dynamically performing tests may include selecting a polymorphic entity, displaying a context menu associated with the polymorphic entity on a display, activating in the context menu a menu item that is linked to one of one or more requirements, generating the test, and performing the test to produce a test result.

Abstract: A method and apparatus for estimating error in a multi-axis controlled machine is applicable to any type of machine configuration in order to estimate and confirm in advance the final position and the posture of the machine, which are produced when geometric errors of the machine are synthesized. The method includes defining the structure of the multi-axis controlled machine subjected to error estimation; and defining parameters, which represent behaviors of drive axes having geometric error and relationships between the drive axes according to the defined structure of the multi-axis controlled machine, adding the defined parameters by applying the parameters to a generalized error synthesis model, and generating an error synthesis model of the multi-axis controlled machine by applying a result of parametric modeling in response to a result of the adding.

Abstract: A method for maintaining a technical plant including several components is provided. The method provides a system for planning the use of an enterprise resources system and a control system, with the enterprise resource system connected to the control system and structures of the technical plant are automatically set up in the enterprise resource system.

Abstract: The present disclosure provides a dynamic view in a modeling of an automation system. A first portion of the model may be described in a first sequence description and a second portion of the model may be described in a second sequence description. The sequence descriptions are linked together. In one embodiment, the links are visually provided.

Abstract: A method and system for updating tuning parameters associated with a controller without repetitive compilation of a controller code. The controller code represents an algorithm associated with the controller and can be compiled separately from a data set representing a solution for an optimization problem and also from a data set representing parameters required for prediction. The algorithm can be implemented in a programming language code suitable for implementation on an embedded platform or other types of computer platforms. The data sets can be represented in a specified data structure and the variables associated with the data structure can be declared in the controller template code. The variables can be updated independently without varying the compiled code associated with the controller algorithm that is referring to the variables. The controller can also be updated while the controller actively performs online.

Abstract: A system includes a process controller and an equation evaluation apparatus. The equation evaluation apparatus includes an equation editor, a model factory, and an equation evaluation engine. The equation editor is adapted to receive equations describing a process to be controlled by the process controller. The equation editor is also adapted to generate model information representing the equations. The model factory is adapted to receive the model information and generate an equation stack representing the equations. The equation evaluation engine is adapted to receive evaluation information from the process controller, evaluate at least one of the equations using the evaluation information and the equation stack, and send a result of the evaluation to the process controller. The model information could include information representing algebraic equations, differential equations, algebraic states, differential states, inputs, parameters, constants, and/or expressions.