Abstract: A heater energization control apparatus. When an engine is stopped, a microcomputer of a GCU enters a power save mode. When the microcomputer returns to a normal mode in response to an interruption signal periodically generated from an interruption timer, the microcomputer supplies electricity to a heating resistor for a short time and obtains its resistance (S19). When the resistance is greater than a first reference value, the microcomputer determines that a glow plug is removed from the engine; that is, the glow plug is being exchanged (S29). The microcomputer sets an exchange flag to “1” (S30), and performs calibration for the heating resistor of a new glow plug after the engine is operated next time (S35). When the current resistance becomes smaller than the past resistance, the microcomputer determines that the glow plug has been exchanged.

Abstract: A system and method of detecting clutch engagement of a manual transmission of a motor vehicle is disclosed. The system and method include a clutch switch for detecting clutch engagement and a backup method for detecting clutch engagement. The backup method includes varying a target speed of an engine drive shaft of the motor vehicle and comparing the speed of the engine drive shaft with the speed of a mainshaft of the motor vehicle.

Abstract: The present disclosure provides a method. The method includes gathering advanced process control (APC) data from a subset of available wafers and a subset of available processing chambers. The method includes establishing a matrix that contains a plurality of cells. The cells each correspond to one of the available wafers and one of the available processing chambers. The matrix is partially filled by populating cells for which the APC data has been gathered. The method includes determining a plurality of chamber-coverage-rate (CCR) parameters associated with the matrix. The method includes optimizing the CCR parameters through an iteration process to obtain optimized CCR parameters. The method includes predicting an APC data value for a designated cell of the matrix based on the optimized CCR parameters. The designated cell is an empty cell before the predicting and is populated by the predicting.

Abstract: A critical dimension controlling method in a semiconductor production process includes determining whether a model is to undergo a discontinuous production process when a run is inserted in a semiconductor manufacturing line, applying an offset for said model or a common offset for a model group including said model according to the determination, executing a production process in dependence upon a process variation along with the offset for the model or the common offset for the model group, and measuring an actual critical dimension in the production process. The offset for the model is calculated based on a previously measured actual critical dimension, and the calculated offset for the model is applied to the calculation of the common offset for the model group.

Abstract: A method and a device for robust rejection of the periodic disturbances in a motor-position control structure of the RST type, wherein the assembly including the motor, the position sensor, the element for computing the functions 1/So(z?1) and Ro(z?1), in a loop, is called central controller. Within the framework of the invention, to the central controller are added two additional computing elements, the first one being an estimator block E(z?1) and the second one a modifier block Q(z?1), as well as an additional loop, the estimator block E(z?1) allowing a load disturbance estimation signal {circumflex over (v)}(t) to be computed, the modifier block Q(z?1) receiving the load disturbance estimation signal {circumflex over (v)}(t) as an input, to produce a modified signal, which is applied to a negative input of an additional adder arranged upstream from the element for computing the function 1/So(z?1) and then forming the additional loop, the modifier block having a variable transfer function.

Abstract: A power model that relates the settings of resource actuators to power consumption levels of the resource actuators and a condition model that relates the settings of the resource actuators to an environmental condition at the location of the at least one entity and a power consumption level of the at least one entity are developed. A constraint optimization problem having an objective function and at least one constraint is formulated, where the objective function computes at least a proportional quantity of a total power consumption level of the resource actuators and the at least one constraint comprises a setpoint environmental condition at a location of the at least entity. A solution to the constraint optimization problem is determined, where the solution provides optimal values for the resource actuator settings.

Abstract: A method and system for estimating context offsets for run-to-run control in a semiconductor fabrication facility is described. In one embodiment, contexts associated with a process are identified. The process has one or more threads, and each thread involves one or more contexts. A set of input-output equations describing the process is defined. Each input-output equation corresponds to a thread and includes a thread offset expressed as a summation of individual context offsets. A state-space model is created that describes an evolution of the process using the set of input-output equations. The state-space model allows to estimate individual context offsets.

Abstract: The identification of Hammerstein models relates to a computerized method for identifying Hammerstein models in which the linear dynamic part is modeled by a space-state model and the static nonlinear part is modeled using a radial basis function neural network (RBFNN), and in which a particle swarm optimization (PSO) algorithm is used to estimate the neural network parameters and a numerical algorithm for subspace state-space system identification (N4SID) is used for estimation of parameters of the linear part.

Abstract: The method for Hammerstein modeling of a steam generator plant includes modeling of the linear dynamic part of a Hammerstein model with a state-space model, and modeling the nonlinear part of the Hammerstein model with a radial basis function neural network (RBFNN). Particle swarm optimization (PSO), typically known for its heuristic search capabilities, is used for estimating the parameters of the RBFNN. Parameters of the linear part are estimated using a numerical algorithm for subspace state-space system identification (N4SID).

Abstract: The method for the identifying of multiple input, multiple output (MIMO) Hammerstein models that includes modeling of the linear dynamic part of a Hammerstein model with a state-space model, and modeling the nonlinear part of the Hammerstein model with a radial basis function neural network (RBFNN).

Abstract: A control system is disclosed. The control system may have a physical sensor configured to measure physical parameter values of a machine. The control system may also have a virtual sensor network system configured to receive the physical parameter values measured by the physical sensor as input parameter values, and generate output parameter values based on the input parameter values. Further, the control system may have an electronic control module configured to store an output parameter value default rate of change and an output parameter value threshold rate of change, compare a rate of change of the output parameter values generated by the virtual sensor network system to the output parameter value threshold rate of change, and control the machine based on the output parameter value default rate of change if the rate of change of the output parameter values exceeds the output parameter value threshold rate of change.

Abstract: Real-time condition-based analysis is performed on a machine for providing diagnostic and prognostic outputs indicative of machine status includes a signal processor for receiving signals from sensors adapted for measuring machine performance parameters. The signal processor conditions and shapes at least some of the received signals into an input form for a neural network. A fuzzy adaptive resonance theory neural network receives at least some of the conditioned and shaped signals, and detects and classifies a state of the machine based upon the received conditioned and shaped signals, and upon a predetermined ontology of machine states, diagnostics, and prognostics. The neural network can also determine from the machine state a health status thereof, which can comprise an anomaly, and output a signal representative of the determined health status. A Bayesian intelligence network receives the machine state from the neural network and determines a fault probability at a future time.

Abstract: An embedded nonlinear cooperative pulse-controller (ENCPC), is characterized in that its control algorithm module comprises: a comparison module, an identification control unit, a dynamic control unit, a steady-state control unit and a cooperative control unit; wherein, the comparison module plays the major role of generating the control errors; the identification control unit mainly through the step response identifies the model parameters such as the amplification gain, the time constant and the delay time; the dynamic control unit plays the major role rapidly reducing the control errors in the dynamic change process, improving the rise time of the control system and decreasing the overshoot of the control system by rapidly outputting a regulation pulse, which can make the process variable rapidly approach the desired steady-state value; the steady-state control unit plays the major role of further eliminating the control errors in a steady change process and improving the control precision, according to a

Abstract: A thermal manager has a digital filter whose input is to receive raw temperature values from a sensor and whose output is to provide processed or filtered temperature values according to a filter function that correlates temperature at the sensor with temperature at another location in the device. The thermal manager has a look-up table that further correlates temperature at the sensor with temperature at the other location. The look-up table contains a list of processed temperature sensor values, and/or a list of temperatures representing the temperature at the other location, and their respective power consumption change commands. The thermal manager accesses the look-up table using selected, filtered temperature values, to identify their respective power consumption change commands. The latter are then evaluated and may be applied, to mitigate a thermal at the other location. Other embodiments are also described and claimed.

Abstract: One method includes obtaining a preliminary model associated with a system to be controlled and constructing a weighted model using one or more weighting factors. The method also includes identifying a final model of the system using the preliminary and weighted models, where the final model has a stability margin that is greater than an uncertainty associated with the final model. The method further includes controlling the system using a controller designed based on the final model. Another method includes identifying a first model associated with a system to be controlled, performing model order reduction to identify a second model, and controlling the system using a controller designed based on the second model. Performing the model order reduction includes reducing a weighted coprime factor model uncertainty between the first and second models.

Abstract: A sensor system for use with a machine is disclosed. The sensor system may have a sensor associated with the machine and configured to generate a signal indicative of an actual value for a parameter of the machine, and a controller in communication with the sensor. The controller may be configured to model behavior of the machine under particular conditions and responsively generate a first predicted value for the parameter, determine a time lag coefficient for the sensor based on the signal, model behavior of the sensor based on the time lag coefficient and the first predicted value, and responsively generate a second predicted value for the parameter. The controller may also be configured to determine an error value based on the actual value and the second predicted value, and determine a compensated value for the parameter based on the first predicted value and the error value.

Abstract: An in-plane compressive strength evaluation device (10) provided with a memory unit (21) into which, when an in-plane compressive strength evaluation is actually performed using a test piece, an evaluation result is stored as first information; a first analysis unit (22) that obtains second information that is an evaluation result related to the load and a displacement of the structural model; an adjustment unit (23) that adjusts an elemental factor of the structural model that influences the in-plane compressive strength such that the second information approaches the first information; and a second analysis unit (24) that, in a state where the elemental factor used when the second information approaches the first information most closely expands the structural model into the structural form of the actual tube support plate, and that performs the in-plane compressive strength evaluation using the expanded structural model.

Abstract: The invention develops models of functional proteomics. Simulation scenarios of protein pathway vectors and protein-protein interactions are modeled from limited information in protein databases. The system focuses on three integrated subsystems, including (1) a system to model protein-protein interactions using an evolvable Global Proteomic Model (GPM) of functional proteomics to ascertain healthy pathway operations, (2) a system to identify haplotypes customized for specific pathology using dysfunctional protein pathway simulations of the function of combinations of single nucleotide polymorphisms (SNPs) so as to ascertain pathology mutation sources and (3) a pharmacoproteomic modeling system to develop, test and refine proposed drug solutions based on the molecular structure and topology of mutant protein(s) in order to manage individual pathologies. The system focuses on simulating the degenerative genetic disease categories of cancer, neurodegenerative diseases, immunodegenerative diseases and aging.

Abstract: Embodiments of the invention can provide systems and methods for using a combustion dynamics tuning algorithm with a multi-can combustor. According to one embodiment of the invention, a method for controlling a gas turbine engine with an engine model can be implemented for an engine comprising multiple cans. The method can include obtaining operating frequency information associated with multiple cans of the engine. In addition, the method can include determining variation between operating frequency information of at least two cans. Furthermore, the method can include determining a median value based at least in part on the variation. Moreover, the method can include determining whether the median value exceeds at least one operating threshold. The method can also include implementing at least one engine control action to modify at least one of the operating frequencies if at least one operating threshold is exceeded.

Abstract: A method and computer program for the control of the heat treatment of batches of metal workpieces for increasing the degree of automation of industrial furnace plants presumes an identical batch layout, an identical treatment program, and an identical article geometry of metal workpieces and relates it to a model batch, which has been run using batch thermoelements. The model batch becomes the foundation for a new batch. Through the assumption of program parameters of the actually run process of the model batch into the program of the new batch to be run, new batch thermoelements are not required for the new batch to be run.

Abstract: In a field device for process automation, a reprogammable logic device is used, in order to achieve a high flexibility as regards hardware components.

Abstract: Methods for modeling the secondary path of an ANC system to improve convergence and tracking during noise control operation, and their associated uses are provided. In one aspect, for example, a method for modeling a secondary path for an active noise control system is provided. Such a method may include receiving a reference signal, filtering the reference signal with an initial secondary path model to obtain a filtered reference signal, calculating an autocorrelation matrix from the filtered reference signal, and calculating a plurality of eigenvalues from the autocorrelation matrix. The method may further include calculating a maximum difference between the plurality of eigenvalues and iterating a test model to determine an optimized secondary path model having a plurality of optimized eigenvalues that have a minimized difference that is less than the maximum difference of the plurality of eigenvalues, such that the optimized secondary path model may be utilized in the active noise control system.

Abstract: Systems and techniques for processing signals representative of sound for conveyance to the auditory system of a subject based on the identity of an input device. In one implementation, a method includes identifying an input element to an audiological system that conveys sound information directly to a subject's auditory system, automatically setting parameters for processing the signal based on the identity of the input element, and processing the signal in accordance with the processing parameters. The input element is configured to generate a signal representative of sound.

Abstract: In tuning a PID controller for a process in a feedback control system, a method is provided for bringing the system into symmetric self-excited oscillations for measuring the frequency and the amplitude of the oscillations, and tuning the controller in dependence on the measurements obtained. A control algorithm referred to as the modified relay feedback test is introduced into a system in series with a process to generate self-excited oscillations. Tuning includes the steps of selecting a desired gain margin or phase margin, generating oscillations with the algorithm parameter corresponding to a selected gain or phase margin, measurements of the amplitude and the frequency of these oscillations, and computing PID controller tuning parameters. Data and formulas are given for the computation of the specific parameter of the modified relay feedback test and for tuning the parameters of the PID controller. An apparatus for performing the method is disclosed.

Abstract: Power consumption of a group of computer systems is managed based on a maximum power consumption for the group. A power budget is determined from the power consumption of each computer system and the maximum power consumption for the group. The power budget identifies a power cap for each computer system in the group. The power caps in the power budget are distributed to the computer systems in the group.

Abstract: The systems and methods described herein allow for automatic identification experiments in a closed loop, where the old control strategy, already tuned and tested, is utilized. The strategy is modified to inject additional signal optimized for identification. The experimenting time may be reduced by performing only those system manipulations which explore model uncertainties important to potential degradation of controller performance by discrepancy between the system and the model. The disruptions are reduced by keeping the control loop closed, which eliminates waiting for steady state before applying steps to the inputs and reduces the risk of process limits crossing. The energy of additional signal can be set to meet the maximum allowable disruption requirements. The energy of additional signal is in a direct relation to the speed of identification related information gathering. It can be varied in time to follow the needs of system operators.

Abstract: A microprocessor may include a logic circuit for executing instructions of a data processing application. The microprocessor may have a timer system which includes a clock counter connected to a clock input for receiving a clock signal and counting a number of cycles of the clock signal. A clock comparator may be connected the clock counter and to a timer register in which a timer reference value can be stored. The clock comparator may compare a number of cycles of the clock signal with the timer reference value and generate a timer signal based on the comparison. The timer system may have a timer output for outputting timer signal. The timer system may include a control input for receiving a digital value representing a measured value of a sensed parameter of a device and a control register in which a control reference value can be stored. A control comparator may be connected the control input.

Abstract: A recommendation engine coupled to a server computer in communication with a plurality of hosts is described. The recommendation engine includes computer readable intrusion-protection instructions stored in a memory device, which cause a processor of said server computer to determine a current host-protection configuration for a target host; detect discrepancy between said current host-protection configuration and a prior host-protection configuration; install said current host-protection configuration in said target host upon detecting said discrepancy; record successive host-reconfiguration periods, a host reconfiguration period being a difference between successive instants of time at which a current host-protection configuration differs from a prior host-protection configuration; determine a monitoring period according to a value of at least one of said successive host-reconfiguration periods; and a scheduler for activating said intrusion-protection instructions according to said monitoring period.

Abstract: The plant control system has a measurement signal data database, a model to estimate the value of measurement signal data used at a time when an operation signal is given to the plant, and an operation signal learning unit to learn a method of generating a model input, which is equivalent to an operation signal, so that a model output, which is equivalent to the measurement signal data, attains a target value. The plant control system also has an evaluation function calculating unit to calculate an evaluation function value from the model output obtained as a result of an operation carried out by the operation signal learning unit for the model, and an evaluation function adjusting unit to adjust evaluation function parameters used in calculation of an evaluation function.

Abstract: A system and method for radio network planning comprises a grid generator and a Monte Carlo analysis module. The Monte Carlo analysis module comprises a snapshot generation module which draws, for each snapshot and for each pixel, a statistical realization from a distribution function relating to slow fading, and a snapshot evaluation module which establishes radio network parameters. The Monte Carlo analysis module further comprises a sub-snapshot generation module which generates at least one sub-snapshot for each evaluated snapshot result, and a sub-snapshot evaluation module (14) for evaluating HSDPA performance parameters based on the sub-snapshot. The sub-snapshot evaluation module (14) comprises a scheduler module (16) which is arranged for scheduling a HSDPA user according to a scheduling scheme.

Abstract: Methods and systems for assessing transmitter electronics in an industrial process control system comprise generating a process condition reference equation signal, a process condition approximation equation signal, and an accuracy output signal. The process condition reference equation signal is generated using a process condition reference equation and process control inputs. The process condition approximation equation signal is generated using a process condition approximation equation that approximates the reference equation using the process control inputs, and approximation equation coefficients based on the approximation equation and the process control inputs. The approximation equation signal is compared to the reference equation signal at a control room workstation such that the industrial process control system can be adjusted. In one embodiment, the approximation equation coefficients are adjusted and transmitted to process transmitter electronics over a control network.

Abstract: An apparatus, system, and storage medium that in an embodiment collect a performance metric of a first partition in a logically-partitioned computer. If the difference between the performance metric and an expected performance metric exceeds a threshold, then a job or another partition is shut down or suspended. The expected performance metric is calculated based on the performance that is expected if the first partition is the only partition.

Abstract: An extremum seeking control method optimizes a control process for a plant such as an air handling unit. The method compensates for abrupt changes in the operation of the plant by resetting the extremum seeking control strategy in response to a detection of the abrupt change.

Abstract: A braking control method that includes: (1) regularly updating a grip model representative of a relationship between a coefficient of friction and a wheel slip rate; (2) determining, with an iterative calculation process including a plurality of calculation cycles a variation of a braking setpoint in a given prediction horizon, the variation of the braking setpoint in the given prediction horizon being established using the regularly updated grip model and its characteristic shape and so that the variation of the braking setpoint in the given prediction horizon complies with the braking order and complies with a given calculation constraint which is function of the wheel slip rate; and (3) retaining as the generated braking setpoint a value of the braking setpoint in the given prediction horizon which corresponds to a first calculation cycle of the plurality of calculation cycles of the iterative calculation process.

Abstract: The method for generating an integrated guidance law for aerodynamic missiles uses a strength Pareto evolutionary algorithm (SPEA)-based approach for generating an integrated fuzzy guidance law, which includes three separate fuzzy controllers. Each of these fuzzy controllers is activated in a unique region of missile interception. The distribution of membership functions and the associated rules are obtained by solving a nonlinear constrained multi-objective optimization problem in which final time, energy consumption, and miss distance are treated as competing objectives. A Tabu search is utilized to build a library of initial feasible solutions for the multi-objective optimization algorithm. Additionally, a hierarchical clustering technique is utilized to provide the decision maker with a representative and manageable Pareto-optimal set without destroying the characteristics of the trade-off front. A fuzzy-based system is employed to extract the best compromise solution over the trade-off curve.

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 model output to direct the control law. The open loop module generates the model output as a function of a model state and a model input. The corrector generates a corrector output as a function of the model output. The comparator generates an error by comparing the corrector output to the model input. The estimator generates the model state as a function of the error, such that the error is minimized as a function of single-input, single-output gain matrix.

Abstract: A method and a system for adjusting a measuring device. The measuring device, determines the physical or chemical process variable based on measurement data; an analytical tool, ascertains the analytical data from the measurement data; a database, in which data sets with analytical data for different process conditions and associated parameter sets for adjusting the measuring device are stored, or in which a plurality of models with associated calculational specifications are stored, which produce the analytical data; and a calculation/control unit, which compares the ascertained analytical data with the stored analytical data, ascertains that data set of the stored analytical data, which has maximum agreement with the ascertained analytical data and adjusts the measuring device corresponding to the associated parameter set.

Abstract: A control apparatus which is capable of ensuring both high-level stability and accuracy of control, even when controlling a controlled object having extremal characteristics or a controlled object a controlled object model of which cannot be represented. The control apparatus 1 includes a cooperative controller 30, an onboard model analyzer 40, and a model corrector 60. The model corrector 60 calculates the model correction parameter matrix ?, so as to correct the controlled object model defining the relationship between the intake opening angle ?lin and the exhaust reopening angle ?rbl and the indicated mean effective pressure Pmi. The onboard model analyzer 40 calculates first and second response indices RI1 and RI2 representative of correlations between ?lin, ?rbl, and Pmi, based on the controlled object model corrected using ?.

Abstract: Methods and systems for controlling drilling operations include using a statistical model to identify at least one controllable drilling parameter having significant correlation to an objective function incorporating two or more drilling performance measurements. The methods and systems further generate operational recommendations for at least one controllable drilling parameter based at least in part on the statistical model. The operational recommendations are selected to optimize the objective function.

Abstract: Embodiments described herein comprise a system and method for corroborative vehicle diagnostic. The corroborative vehicle diagnostic system allows a vehicle to detect a fault indicator experienced by a vehicle subsystem. The corroborative vehicle diagnostic system allows the vehicle to compare the fault indicator with similar and/or dissimilar conditions experienced by one or more additional vehicle located within a geographic region. A corroborative diagnostic controller compares the fault indicator with the conditions of the additional vehicle. Based on the comparison of the fault indicator with the condition, an error status of the fault indicator is determined. The error status may be that the vehicle subsystem has failed, that the vehicle subsystem has not failed and/or that the results are inconclusive. The corroborative diagnostic controller may communicate directly with a control system of the vehicle.

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: A method for ascertaining process values for a process control is provided. The method includes detecting a measured value, providing a model that simulates the process, and, on the basis of the model, calculating a calculated real value and a calculated measured value. The method also includes comparing the calculated real value with the calculated measured value to obtain a delay compensation value, and adding the delay compensation value to the measured value to obtain an accelerated value indicative of the process value to be ascertained.

Abstract: This invention provides a process control simulator configured to efficiently debug a plant control system. A computer stores simulated data generated by a model executing part to a time-series memory area. A programmable controller stops input from the input-device interface when there is a virtual input/output request received. A virtual input/output processor sets simulated data from a time-series memory area of the computer to a time-series memory area of the programmable controller. A program executing part sets simulated data from the time-series memory area to a memory area at the same resolution as an arithmetic operation period of program execution and executes the program. Control output as a result of the execution is fed back to the model executing part of the computer, and the computer calculates simulated data as process value at this timing, and stores the data to its time-series memory area.

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 method of determining complete sensor requirements for autonomous mobility of an autonomous system includes computing a time variation of each behavior of a set of behaviors of the autonomous system, determining mobility sensitivity to each behavior of the autonomous system, and computing a change in mobility based upon the mobility sensitivity to each behavior and the time variation of each behavior. The method further includes determining the complete sensor requirements of the autonomous system through analysis of the relative magnitude of the change in mobility, the mobility sensitivity to each behavior, and the time variation of each behavior, wherein the relative magnitude of the change in mobility, the mobility sensitivity to each behavior, and the time variation of each behavior are characteristic of the stability of the autonomous system.

Abstract: A multivariable model predictive controller (MPC) for controlling a coalbed methane (CBM) production process. The MPC includes input ports for receiving a plurality of measurement signals including measured process parameters from CBM wells in a well field. A control loop includes a mathematical model that controls the CBM gas production. The model includes individual production characteristics for each CBM well that predicts its behavior for controlled variables (CVs) with respect to changes in manipulated variables (MVs) and disturbance variables (DVs). The control loop calculates future set points for the MVs based on the model and the measured process parameters for CBM production to achieve at least one control objective for the well field. A plurality of output ports provide control signals for implementing the future set points which when coupled to physical process equipment at the plurality of CBM wells control the physical equipment to reach the future set points.

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.