Abstract: A method of offline code validation and a process control system are provided. The system includes a plurality of sensors each configured to generate a sensor output value representative of a respective sensed parameter in a process plant, at least one process controller configured to receive one or more of the sensor output values and to generate a controller output value using the one or more of the sensor output values and a control algorithm associated with the at least one process controller, a plurality of controlled components configured to receive an associated controller output value, and an offline computing environment including a selectable model controller configurable to represent the at least one process controller, the model controller selectable by a user from code representing the at least one process controller and displayed on a user interface.

Abstract: A system for controlling a machine includes a first model, a second model, a controller, and a comparator. During a first cycle, the first model generates a response signal to the controller while the second model generates a predicted parameter signal. During the first cycle, the comparator transmits a feedback signal to the second model if a predetermined threshold is not met. A method for controlling a machine includes transmitting a response signal from a first model to a controller, generating a control signal to the machine, and generating a predicted parameter value in a second model. The method further includes transmitting a feedback signal to the second model if a predetermined threshold is not met.

Abstract: A method to enable wafer result prediction from a batch processing tool, includes collecting manufacturing data from a batch of wafers processed in batch in the batch processing tool, to form a batch processing result; defining a degree of freedom of the batch processing result based on the manufacturing data; and performing an optimal curve fitting by trial and error for an optimal function model of the batch processing result based on the batch processing result.

Abstract: Methods and systems for modeling turbine operation are disclosed. In one embodiment a method for modeling turbine operation may include: determining current performance parameters of a turbine; providing at least one external factor for current or future operation of the turbine; and modeling, by a predictive model, at least one operating characteristic of the turbine based at least in part on the current performance parameters of the turbine and the at least one external factor.

Abstract: Systems and methods are provided for controlling the simulation of a coupled hybrid dynamic system. A physical test rig configured to drive the physical structure component of the system and to generate a test rig response as a result of applying a test rig drive signal. A processor is configured with a virtual model of the system. The processor receives the test rig response and generates a model response of the system based on the received test rig response and a virtual drive input. The system is driven with a random input. The processor compares the test rig response with the model response, the difference being used to form a system dynamic response model for generating the test drive signal. An inverse of the system dynamic response model is used to iteratively reduce the difference between the model response and the test rig response below a defined threshold.

Abstract: Disclosed are systems and methods for on-line monitoring of operation of a process in connection with process measurements indicative of the operation of the process. In some cases, the operation of the process is simulated to generate model data indicative of a simulated representation of the operation of the process and based on the process measurements. A multivariate statistical analysis of the operation of the process is implemented based on the model data and the process measurements. The output data from the multivariate statistical analysis may then be evaluated during the operation of the process to enable the on-line monitoring of the process involving, for instance, fault detection via classification analysis of the output data.

Abstract: A control system comprises an actuator, a control law and a processor. The actuator positions a control surface and the control law controls the actuator. The processor comprises an open loop module, a corrector, a comparator, and an estimator, and generates an output vector to direct the control law. The open loop module generates the output vector as a function of a state vector and an input vector. The corrector generates a corrector vector as a function of the output vector. The comparator generates an error vector by comparing the corrector vector to the input vector. The estimator generates the state vector as a function of the error vector, such that the error vector is minimized.

Abstract: Process control system for detecting abnormal events in a process having one or more independent variables and one or more dependent variables. The system includes a device for measuring values of the one or more independent and dependent variables, a process controller having a predictive model for calculating predicted values of the one or more dependent variables from the measured values of the one or more independent variables, a calculator for calculating residual values for the one or more dependent variables from the difference between the predicted and measured values of the one or more dependent variables, and an analyzer for performing a principal component analysis on the residual values. The process controller is a multivariable predictive control means and the principal component analysis results in the output of one or more scores values, T2 values and Q values.

Abstract: A first observer gain of an actual damping force estimating observer 21 calculates a dynamic characteristic compensating signal, and a second observer gain of an actual vehicle model state amount estimating observer 23 calculates a vehicle model compensating signal, from an output deviation corresponding to a difference between a sprung speed (observation output) provided from a vehicle 2 and an estimated sprung speed (estimated observation output) provided from a vehicle approximation model of the actual vehicle model state amount estimating observer 23. The dynamic characteristic compensating signal is input into a dynamic characteristic providing unit of the actual vehicle model state amount estimating observer 23, and is used for adjustment of the setting of the dynamic characteristic providing unit. Therefore, it is possible to curb time lag occurrence in a control, and thereby perform a vibration control with improved accuracy.

Abstract: A system and method of modeling, prediction, optimization and controlling an embedded alarm control having a plurality of independently controlled, manipulated variables, at least one controlled variables and one or more disturbance variables. The method includes determining simultaneously a set number of dynamic moves of the manipulated variables along with steady state values of the manipulated and controlled variables with steady state constraints relating to the manipulated and controlled variables as well as dynamic constraints relating to the manipulated and controlled variables including relating to the disturbance variables. Embedding alarm controls in the simultaneous dynamic control and steady state optimization with varying type of alarming situations and aiding operator in recovery actions.

Abstract: A system and method for implementing a control process within a process control system and resolving inconsistencies during execution of the control process includes loading the logical structure of the control process, loading a plurality of instantiation objects or processes when the control process is instantiated, using the instantiation objects to instantiate a procedural element of the control process as the control process calls for the procedural element during execution, executing the procedural element as part of the control process, and deconstructing the procedural element as execution of the procedural element is completed during execution of the control process. Resolution of inconsistencies includes executing a first model of an entity in a controller, executing a second model of the entity in an execution engine, detecting a difference between the models, generating a prompt and receiving an operation instruction to continue the process or abort the process.

Abstract: A device is described for ascertaining state variables and/or parameters of a mathematical energy accumulator model, in particular a battery model, that describes the electrical properties of the energy accumulator on the basis of various state variables and parameters, the mathematical energy accumulator model having correction equations by which the state variables and/or the parameters are corrected and adjusted to the actual operating performance of the energy accumulator. A particularly rapid and accurate compensation of the energy accumulator model may be achieved if the error between a measured battery performance quantity and the battery performance quantity calculated by the energy accumulator model, a differentiated component of the error and an integrated component of the error are calculated, the individual components are each weighted using a weighting factor and the weighted error components are taken into account in correction of a state variable and/or a parameter.

Abstract: A control system comprises a controller for positioning an actuator in a working fluid flow and a model processor for directing the controller as a function of a model feedback. The model processor comprises an output module, a comparator and an estimator. The output module generates the model feedback as a function of a constraint, a model state and a model input describing fluid parameters measured along the working fluid flow. The comparator generates an error by comparing the model feedback to the model input. The estimator generates the constraint and the model state, such that the error is minimized.

Abstract: The present invention discloses a plant diagnostic system for diagnosing a problem with the plant. The plant diagnostic system can include an agent-based plant diagnostic network that has an adaptive global agent located in a central facility, a plant expert agent located at the plant and a plurality of subsystem resident agents. Each of the subsystem resident agents can be assigned to a subsystem of the plant. A diagnosis agent can also be included, the diagnosis agent operable to be instructed by the adaptive global agent, transmitted to the plant expert agent, be received by the plant expert agent, transmitted by the plant expert agent back to the adaptive global agent and be received by the adaptive global agent.

Abstract: The invention relates to the online regulation of a batch process in a bioreactor. According to the invention, spectra of the actual charge in the bioreactor are recorded at successive points during the running batch process. A measuring vector is produced, for each spectrum, in the low-dimensional main constituent region by the main constituent analysis of the high-dimensional spectra. The deviation is calculated between the measuring vector and a corresponding vector of a nominal trajectory consisting of measuring vectors of a reference charge, which are determined in an earlier batch process, and at least one adjustment operation for the batch process is determined and carried out according to said deviation. The direction of the adjustment operation is maintained when the deviation determined from one point to the next decreases, and modified when the deviation determined from one point to the next remains the same or increases.

Abstract: A system for controlling a machine includes a first controller, a second controller, and a comparator. During a first cycle, the first controller generates a control signal to the machine while the second controller generates a predicted parameter signal. During the first cycle, the comparator transmits a feedback signal to the second controller if a predetermined threshold is not met. A method for controlling a machine includes transmitting a control signal from a first controller to the machine and generating a predicted parameter value in a second controller. The method further includes transmitting a feedback signal to the second controller if a predetermined threshold is not met.

Abstract: A method includes generating a model associated with cross-directional fiber orientation of a web, which includes identifying spatial frequency characteristics of a fiber orientation (FO) process. The method also includes providing the model for control of the FO process. Generating the model could include performing a spatial impulse test of the FO process, and long wavelength responses of the FO process can be identified by performing a spatial long wavelength test of the FO process or by retrieving information from a historical database. Actuator edge padding can be applied to the model in order to generate a controller model. A controller can be used to control the process based on the controller model. At least one parameter of the controller model can be dynamically adjusted during operation of the controller. The controller can change average fiber orientation angle profiles and twist profiles by only adjusting slice lip actuators in a headbox.

Abstract: A batch modeling and analysis system uses a simple and computationally inexpensive technique to align data collected from an on-going, currently running or on-line batch process with a batch model formed for the batch process so as to enable the reliable determination of the current operational state of the on-line batch process with respect to the batch model. This data alignment technique enables further statistical processing techniques, such as projection to latent sources (PLS) and principle component analysis (PCA) techniques, to be applied to the on-line batch data to perform analyses on the quality of the currently running batch. These analyses, in turn, provide useful information to a user, such as a batch operator, that enables the user to determine the quality of the batch at the present time, based on the batch model, and the likelihood that the desired batch output quality metrics will be reached at the end of the batch run.

Abstract: Disclosed are an articulated hydraulic machine supporting, control system and control method for same. The articulated hydraulic machine has an end effector for performing useful work. The control system is capable of controlling the end effector for automated movement along a preselected trajectory. The control system has a position error correction system to correct discrepancies between an actual end effector trajectory and a desired end effector trajectory. The correction system can employ one or more absolute position signals provided by one or more acceleration sensors supported by one or more movable machine elements. Good trajectory positioning and repeatability can be obtained. A two-joystick controller system is enabled, which can in some cases facilitate the operator's task and enhance their work quality and productivity.

Abstract: A peritoneal dialysis system includes: an automated peritoneal dialysis (“APD”) machine configured to remove ultrafiltrate (“UF”) from a patient and record how much UF has been removed; and a logic implementer configured to (i) form a first moving average UF removed trend, (ii) determine a trending range around the first moving average UF removed trend, (iii) determine at least one of an upper and lower UF removed limit from the trending range, (iv) form a second moving average UF removed trend, and (v) alert if the second moving average UF removed trend moves outside of the at least one UF removed limit.

Abstract: The present invention provides a processing system, a processing method and a program, which can readily control a gas flow rate. A vertical-type heating apparatus 1 includes a plurality of gas supply pipes 16 to 20 each adapted for supplying a processing gas into a reaction vessel 2 configured to contain therein semiconductor wafers W. For the gas supply pipes 16 to 20, flow rate control units 21 to 25 are provided, respectively, for controlling each flow rate. In a control unit 50, processing conditions including the flow rate of the processing gas and a film thickness-flow rate-relationship model indicative of a relationship between the flow rate of the processing gas and a film thickness, are stored.

Abstract: The present invention provides a method for feedback control and a device using the same, wherein the device comprising a sensing layer for generating a plurality of sensing signals with respect to the at least one kind of characteristics on the sensing layer, and a driving layer for changing the surface status of the sensing layer. The control method is started a step of acquiring the plurality of sensing signals within a first specific time interval and establishing a first prediction model accordingly, then predicting a distribution status with respect to the at least one kind of characteristic on the sending layer at a specific time point according to the first prediction model, and finally, determining whether to change the surface status of the sensing layer according to the distribution status.

Abstract: A method of control for a process control system and an appropriate control system is provided. Model calculations are integrated into the process control system such that the setpoint values calculated using the model calculations are processed further like measured values in the process control system, and control commands are derived from the measured values and/or setpoint values. The model calculations are integrated into the process control system using an adaptation program. The adaptation program includes program code and associated data from the model calculations and, in comparison with the other program components of the process control systems, is designed like a program component of the process control system. Within the adaptation program, the interfaces of the adaptation program match those of the model calculations.

Abstract: A method includes obtaining a nonlinear process model modeling a nonlinear process to be controlled. The method also includes obtaining an objective function defining how the process is controlled. The method further includes obtaining a control model defining a dynamic feasible region associated with a controlled variable, where the controlled variable is associated with the process. In addition, the method includes controlling the nonlinear process by solving a control problem that includes the process model, control model, and objective function. The dynamic feasible region defined by the control model could represent a funnel region. The objective function could include terms for minimizing and optimizing adjustments to one or more manipulated variables associated with the process.

Abstract: A numerical controller controlling a 5-axis machine tool compensates setting error that arises when a workpiece is set on the table. Error in the three linear axes and the two rotation axes are compensated using preset error amounts to keep the calculated tool position and tool direction in a command coordinate system. If a trigonometric function used for error compensation has a plurality of solution sets, the solution set closest to the tool direction in the command coordinate system is selected from the plurality of solution sets and used as the positions of the two rotation axes compensated in the above error compensation.

Abstract: A method for customizing a bearing bore in a housing so that the bearing assembly will transmit load in a desired manner over a predetermined range of operating temperatures.

Abstract: 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.

Abstract: A method and apparatus controls a plant using feedback signals. A procedural description of a feedback control process for the plant is translated into a set of objects, wherein each object is a portion of the procedural description, wherein each object is a strictly-encapsulated and autonomous software module, wherein the objects execute in a platform, and wherein the platform includes a set of nodes embedded in the plant and each node includes a processor. A feedback signals is generated by passing messages between the set of the objects in response to an operation of the plant.

Abstract: A control system comprises an actuator, a control law and a processor. The actuator positions a control surface and the control law controls the actuator. The processor comprises an open loop module, a corrector, a comparator, and an estimator, and generates an output vector to direct the control law. The open loop module generates the output vector as a function of a state vector and an input vector. The corrector generates a corrector vector as a function of the output vector. The comparator generates an error vector by comparing the corrector vector to the input vector. The estimator generates the state vector as a function of the error vector, such that the error vector is minimized.

Abstract: A changepoint detector for modeling data received from at least one sensor in a proces in the hydrocarbon industry. The data is segmented into a plurality of segments and fo each segment a model is assigned and the data corresponding to the segment fit to tha model. A plurality of segmentations are thus provided and these segmentations ar evaluated and assigned weights indicative of the fit of the models of the segmentation t the underlying data. The segmentation models are further used to calculate a result tha may be input to a process control program.

Abstract: A method and system for monitoring a process in a process plant includes collecting data from a process control system within the process plant, where the data is representative of a normal operation of the process when the process is on-line and operating normally, performing a multivariate statistical analysis to represent the normal operation of the process based on a set of collected on-line process data comprising a measure of the normal operation of the process when the process is on-line and operating normally, and representing a real-time on-line operation of the process using monitored on-line process data as an input to the representation of the normal operation of the process, where the monitored on-line process data comprises a measure of a real-time operation to the process when the process is on-line.

Abstract: A diagnostic system includes N dedicated diagnostic modules that each correspond with a respective one of multiple control systems. The N dedicated diagnostic modules each generate status signals indicating results of respective diagnostic tests. A diagnostic error time monitor determines an accumulated error time value between error events for each of the control systems based on the status signals. The diagnostic error time monitor selectively reports a fault to a respective one of the N dedicated diagnostic modules based on the accumulated error time value.

Abstract: The invention relates to a process control system having measuring devices and actuators. All of the measuring devices and actuators process information and exchange data amongst themselves. All measuring devices and actuators are interconnected to enable a bi-directional data exchange. Several, or all of the measuring devices and actuators can exchange data with a service unit that can be connected to the devices and actuators. The invention also relates to a method for operating a process control system of this type.

Abstract: For a plurality of combinations of a plurality of operating states included in an operating range of an engine and for a plurality of combinations of a plurality of objective variables, a system, which calculates design variables, includes a calculating device for obtaining global optimal solutions of the design variables that minimize or maximize a sum of the plurality of objective variables, which respectively correspond to the plurality of combinations of the plurality of operating states; a receiving device for receiving designation of an upper limit or a lower limit of the plurality of objective variables; and a searching device for searching for global optimal solutions that result in the smoothest change in the design variables when changing the operating states in a range of the received upper limit to the received lower limit of the objective variables, with one of the global optimal solutions as an initial value set.

Abstract: A system and method for monitoring and managing utility consumption includes use of (A) one or more sensors arranged to monitor an operating condition and/or utility consumption of at least one segment or appliance of a first facility; (B) a memory including at least one of (i) stored utility consumption information correlated or normalized to at least one designated parameter affecting utility consumption or (ii) hypothetical utility consumption; (C) a processor to compare the monitored information with the stored information, and (D) an output medium to store and/or display the comparison information. Stored consumption information may relate to the first facility or a second facility. Hypothetical utility consumption information may relate to a segment or appliance of the first facility operated according to optimized conditions, or an upgraded segment or appliance.

Abstract: 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.

Abstract: A robot localization system is provided. The robot localization includes a robot, which moves within a predetermined space and performs predetermined tasks, and a docking station corresponding to a home position of the robot. The docking station includes a first transmitting unit, which transmits a sound wave to detect a position of the robot; and a second transmitting unit, which transmits a synchronizing signal right when the sound wave is transmitted.

Abstract: In one aspect of the invention, a method for the improved operation of an electronic device manufacturing system is provided. The method includes providing information to an interface coupled to an electronic device manufacturing system having parameters, processing the information to predict a first parameter, and providing an instruction related to at least a second parameter of the electronic device manufacturing system wherein the instruction is based on the predicted first parameter. Numerous other aspects are provided.

Abstract: A method and system for process control using a model predictive controller. The control system can have one or more control devices operably coupled to a processing system for controlling a process of the processing system; a modeling tool to provide a non-linear model based at least in part on the process and to provide a plurality of linearized models based at least in part on the non-linear model, where the plurality of linearized models are linearized at different linearization rates; and a controller operably coupled to the modeling tool. The controller can select one of the plurality of linearized models based on a comparison of the plurality of linearized models with a reference model. The controller can send one or more control signals to at least one of the one or more control devices. The one or more control signals can be determined using the selected one of the plurality of linearized models.

Abstract: A system for controlling a machine includes a first controller, a second controller, and a comparator. During a first cycle, the first controller generates a control signal to the machine while the second controller generates a predicted parameter signal. During the first cycle, the comparator transmits a feedback signal to the second controller if a predetermined threshold is not met. A method for controlling a machine includes transmitting a control signal from a first controller to the machine and generating a predicted parameter value in a second controller. The method further includes transmitting a feedback signal to the second controller if a predetermined threshold is not met.

Abstract: A method and an apparatus are disclosed for adapting a process instance, which guarantee that process instances are conform to a specific process meta model. Therefore constraint violations are detected and furthermore remedied according to a derived violation meta model. In at least one embodiment, the present invention finds application in process modeling, system process optimization and/or controlling of machines or technical devices.

Abstract: An improved process and corresponding controller provide a model predictive control approach that can be implemented with less computational resources and/or with greater speed than conventional MPC, while at the same time retaining all or a substantial portion of the robustness and advantages of conventional MPC. According to one aspect of the invention, the process provides an improved initial estimate of the MPC model trajectory to reduce the number of iterations to find the optimal one. The improved trajectory is obtained by applying a correction to the computed MPC manipulated value trajectory, and using the corrected manipulated value trajectory as the starting point for the next iteration of MPC manipulated value trajectory computation. As set forth in more detail below, the correction is determined from the LQR feedback control strategy.

Abstract: The present invention provides novel techniques for optimizing and controlling production plants using parametric multifaceted models. In particular, the parametric multifaceted models may be configured to convert a first set of parameters (e.g., control parameters) relating to a production plant into a second set of parameters (e.g., optimization parameters) relating to the production plant. In general, the first set of parameters will be different than the second set of parameters. For example, the first set of parameters may be indicative of low-level, real-time control parameters and the second set of parameters may be indicative of high-level, economic parameters. Utilizing appropriate parameterization may allow the parametric multifaceted models to deliver an appropriate level of detail of the production plant within a reasonable amount of time.

Abstract: In a method for supplying a resource to an entity from a resource actuator, a plurality of physics-based models pertaining to the resource actuator and the entity are developed, a condition detected at the entity is received, feedback control on a resource demand of the entity employed based upon the detected condition, feed forward control on the resource demand of the entity is employed based upon the detected condition and the plurality of physics-based models, a constraint optimization problem having an objective function and at least one constraint using the plurality of physics-based models is formulated, a solution to the constraint optimization problem is determined, in which the solution provides the actuator setting, and the resource actuator is set to the actuator setting to supply the entity with the resource from the resource actuator.

Abstract: A system is disclosed for incorporating a realistic simulated catheter or catheters within a catheter guidance and control system that operate from the same closed-loop position control feedback and geometric mapping data as the real position control system and are able to make contact with real and simulated datasets. These catheters may be operated in a pure simulation mode without interacting with real catheters and position control hardware, or may be used as control cursors to enhance the placement of catheter positioning targets. The catheter tip, which is focus of magnetic control, is realistically guided by the control system parameters, while the remainder of the catheter line is realistically constrained by the mapped chamber geometry and introducer sheath.

Abstract: A two-stage model predictive control (MPC) controller uses a process model and two separate MPC control modules, including a feedforward MPC control module and a feedback MPC control module, to determine a set of control signals for use in controlling a process. The feedforward MPC control module uses the process model to determine a feedforward control component for each of a set of control signals and the feedback MPC control module uses the process model and one or more measured process outputs to determine a feedback control component for each of the set of control signals. The two-stage MPC controller combines the feedforward control components with the feedback control components to form the final control signals used to control the process.

Abstract: A system for compensating and driving a loudspeaker includes an open loop loudspeaker controller that receives and processes an audio input signal and provides an audio output signal. A dynamic model of the loudspeaker receives the audio output signal, and models the behavior of the loudspeaker and provides predictive loudspeaker behavior data indicative thereof. The open loop loudspeaker controller receives the predictive loudspeaker behavior data and the audio input signal, and provides the audio output signal as a function of the audio input signal and the predictive loudspeaker behavior data.

Abstract: A method includes defining a reference model of a system having a plurality of terms for modeling data associated with the system. A reference fit error metric is generated for the reference model. A set of evaluation models each having one term different than the reference model is generated. An evaluation fit error metric for each of the evaluation models is generated. The reference model is replaced with a selected evaluation model responsive to the selected evaluation model having an evaluation fit error metric less than the reference fit error metric. The model evaluation is repeated until no evaluation model has an evaluation fit error metric less than the reference fit error metric. The reference model is trained using the data associated with the system, and the trained reference model is employed to determine at least one characteristic of the system.

Abstract: A control system comprises a controller for positioning an actuator in a working fluid flow and a model processor for directing the controller as a function of a model feedback. The model processor comprises an output module, a comparator and an estimator. The output module generates the model feedback as a function of a constraint, a model state and a model input describing fluid parameters measured along the working fluid flow. The comparator generates an error by comparing the model feedback to the model input. The estimator generates the constraint and the model state, such that the error is minimized.

Abstract: 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.