Abstract: An inferential sensor module is incorporated into an engine simulation model. One or more parameters for the inferential sensor module are calibrated using one or more of engine measurement data and the engine simulation model. The calibration is performed such that a difference between an inferred signal predicted by the inferential sensor module and a signal measured on an engine is minimized. The inferential sensor module and the one or more calibrated parameters are loaded into an engine control unit in order to predict inferred variables.

Abstract: A method and system of predictive model control of a controlled system with one or more physical components using a model predictive control (MPC) model, determining an iterative, finite horizon optimization of a system model of the controlled system, in order to generate a manipulated value trajectory as part of a control process. At time t sampling a current state of the controlled system a cost function minimizing manipulated variables trajectories is computed with the MPC model for a relatively short time horizon in the future, wherein the MPC uses a quadratic programming (QP) algorithm to find the optimal solution, and wherein the QP algorithm is solved using an Active Sets solver (AS) class algorithm with simple constraints based on gradient projection and using Newton step projection. A move of the manipulated value trajectory is implemented and the control process is moved forward by continuing to shift the prediction horizon forward.

Abstract: A method includes receiving at least one measurement of a dissolved carbon dioxide concentration of a mixture of fluid containing an autotrophic organism. The method also includes determining an adjustment to one or more manipulated variables using the at least one measurement. The method further includes generating one or more signals to modify the one or more manipulated variables based on the determined adjustment. The one or more manipulated variables could include a carbon dioxide flow rate, an air flow rate, a water temperature, and an agitation level for the mixture. At least one model relates the dissolved carbon dioxide concentration to one or more manipulated variables, and the adjustment could be determined by using the at least one model to drive the dissolved carbon dioxide concentration to at least one target that optimize a goal function. The goal function could be to optimize biomass growth rate, nutrient removal and/or lipid production.

Abstract: An inferential sensor module is incorporated into an engine simulation model. One or more parameters for the inferential sensor module are calibrated using one or more of engine measurement data and the engine simulation model. The calibration is performed such that a difference between an inferred signal predicted by the inferential sensor module and a signal measured on an engine is minimized. The inferential sensor module and the one or more calibrated parameters are loaded into an engine control unit in order to predict inferred variables.

Abstract: A system for controlling fuel to an engine to minimize emissions in an exhaust of the engine. There may be a controller connected to an actuator, for example a fuel control actuator, of the engine and to emissions sensors, such as an NOx and/or PM sensor, proximate to an exhaust output of the engine. The controller, for example a speed controller, may have an input connected to an output of a pedal or desired speed setting mechanism. A speed sensor at a power output of the engine may be connected to an input of the controller.

Abstract: A method includes receiving at least one measurement of a dissolved carbon dioxide concentration of a mixture of fluid containing an autotrophic organism. The method also includes determining an adjustment to one or more manipulated variables using the at least one measurement. The method further includes generating one or more signals to modify the one or more manipulated variables based on the determined adjustment. The one or more manipulated variables could include a carbon dioxide flow rate, an air flow rate, a water temperature, and an agitation level for the mixture. At least one model relates the dissolved carbon dioxide concentration to one or more manipulated variables, and the adjustment could be determined by using the at least one model to drive the dissolved carbon dioxide concentration to at least one target that optimize a goal function. The goal function could be to optimize biomass growth rate, nutrient removal and/or lipid production.

Abstract: A system for controlling fuel to an engine to minimize emissions in an exhaust of the engine. There may be a controller connected to an actuator, for example a fuel control actuator, of the engine and to emissions sensors, such as an NOx and/or PM sensor, proximate to an exhaust output of the engine. The controller, for example a speed controller, may have an input connected to an output of a pedal or desired speed setting mechanism. A speed sensor at a power output of the engine may be connected to an input of the controller.

Abstract: Sensor apparatus includes a housing, a probe mounted to the housing, the probe including an elongate first part and a helical coil second part conductively coupled to each in series with first and second terminals at opposite ends thereof, the probe to be inserted into an exhaust stream in an exhaust corridor; and a circuit coupled to the first and second terminals of the sensor probe, to selectively operate the probe as a temperature sensor in a first mode and as a PM sensor in a second mode.

Abstract: A system for controlling fuel to an engine to minimize emissions in an exhaust of the engine. There may be a controller connected to an actuator, for example a fuel control actuator, of the engine and to emissions sensors, such as an NOx and/or PM sensor, proximate to an exhaust output of the engine. The controller, for example a speed controller, may have an input connected to an output of a pedal or desired speed setting mechanism. A speed sensor at a power output of the engine may be connected to an input of the controller.

Abstract: A method and system of predictive model control of a controlled system with one or more physical components using a model predictive control (MPC) model, determining an iterative, finite horizon optimization of a system model of the controlled system, in order to generate a manipulated value trajectory as part of a control process. At time t sampling a current state of the controlled system a cost function minimizing manipulated variables trajectories is computed with the MPC model for a relatively short time horizon in the future, wherein the MPC uses a quadratic programming (QP) algorithm to find the optimal solution, and wherein the QP algorithm is solved using an Active Sets solver (AS) class algorithm with simple constraints based on gradient projection and using Newton step projection. A move of the manipulated value trajectory is implemented and the control process is moved forward by continuing to shift the prediction horizon forward.

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 method includes receiving a measurement associated with a cloud point of a biofuel being produced in a refining system. The method also includes determining how to adjust the refining system based on a desired cloud point of the biofuel and the measurement associated with the cloud point. The method further includes outputting a control signal to adjust the refining system based on the determination. Determining how to adjust the refining system could include determining how to adjust an inlet temperature of a reactor in the refining system. The reactor could represent an isomerization reactor, and a heater could heat material entering the isomerization reactor. Determining how to adjust the inlet temperature of the reactor could include determining how to adjust operation of the heater. A model predictive control (MPC) technique could be used to determine how to adjust the inlet temperature of the isomerization reactor.

Abstract: The invention concerns turbochargers, or more particularly to multivariable dual stage series turbochargers having two degrees of freedom. A multistage series turbocharger apparatus has a low pressure turbocharger comprising a low pressure compressor and a low pressure turbine; a high pressure turbocharger comprising a high pressure compressor and a high pressure turbine, and a exhaust gas recirculation device. A controller controls the operation of at least two of the low pressure compressor, high pressure compressor, low pressure turbine, high pressure turbine, and exhaust gas recirculation device such that at least one operating parameter is maintained at about a selected value.

Abstract: A system for controlling fuel to an engine to minimize emissions in an exhaust of the engine. There may be a controller connected to an actuator, for example a fuel control actuator, of the engine and to emissions sensors, such as an NOx and/or PM sensor, proximate to an exhaust output of the engine. The controller, for example a speed controller, may have an input connected to an output of a pedal or desired speed setting mechanism. A speed sensor at a power output of the engine may be connected to an input of the controller.

Abstract: A system for controlling fuel to an engine to minimize emissions in an exhaust of the engine. There may be a controller connected to an actuator, for example a fuel control actuator, of the engine and to emissions sensors, such as an NOx and/or PM sensor, proximate to an exhaust output of the engine. The controller, for example a speed controller, may have an input connected to an output of a pedal or desired speed setting mechanism. A speed sensor at a power output of the engine may be connected to an input of the controller.

Abstract: A reverse bump test, for identifying the alignment of a sheetmaking system while the system remains in closed-loop control, includes the following steps: (a) leaving the control system in closed-loop, (b) artificially inserting a step signal on top of the measurement (or setpoint) profile from the scanner, (c) recording the data as the control system moves the actuators to remove the perceived disturbance (or setpoint change), and (d) refining or developing a model from the artificial measurement disturbance (or setpoint change) to the actuator profile. The technique supplies the probing/perturbation signal to the scanner measurement, which is equivalent to supplying the probing/perturbation signal to the setpoint target) rather than inserting bumps via the actuator set points as has been practiced traditionally.

Abstract: A heat transfer system in an engine for transferring heat from the recirculated exhaust gas to an output of an engine exhaust system. The heat transfer may cool the recirculated exhaust for reduced emissions from engine combustion and, at the same time, increase the output exhaust temperature to facilitate regeneration of an exhaust aftertreatment system. There may a heat transfer unit at the output of an exhaust gas recirculating valve connected to a heat transfer unit at the output of the exhaust system.

Abstract: Sensor apparatus includes a housing, a probe mounted to the housing, the probe including an elongate first part and a helical coil second part conductively coupled to each in series with first and second terminals at opposite ends thereof, the probe to be inserted into an exhaust stream in an exhaust corridor; and a circuit coupled to the first and second terminals of the sensor probe, to selectively operate the probe as a temperature sensor in a first mode and as a PM sensor in a second mode.

Abstract: A method includes predicting measurements or states to be used by a controller to control a process. The predicted measurements or states are generated using a model of the process. The method also includes providing the predicted measurements or states to the controller such that the controller uses the predicted measurements or states at a sampling rate of the controller. In addition, the method includes updating at least some of the predicted measurements or states using measurements associated with a characteristic of an item from a sensor. The model may represent a discrete time model, and the method may also include generating the discrete time model using a continuous time model of the process. The measurements could be received from a plurality of sensors, where at least two of the sensors have different sampling times.

Abstract: An automated tuning method of a large-scale multivariable model predictive controller for multiple array papermaking machine cross-directional (CD) processes can significantly improve the performance of the controller over traditional controllers. Paper machine CD processes are large-scale spatially-distributed dynamical systems. Due to these systems' (almost) spatially invariant nature, the closed-loop transfer functions are approximated by transfer matrices with rectangular circulant matrix blocks, whose input and output singular vectors are the Fourier components of dimension equivalent to either number of actuators or number of measurements. This approximation enables the model predictive controller for these systems to be tuned by a numerical search over optimization weights in order to shape the closed-loop transfer functions in the two-dimensional frequency domain for performance and robustness.