Abstract: The disclosure describes a system that includes a closed-loop reference module, an adaptation module, and a control module. The closed-loop reference module is configured to execute a reference model that represents operation of an engine and determine a reference control signal and a reference state trajectory signal. The adaptation module is configured to determine an adaptation signal based on a difference between the reference state trajectory signal and an engine state trajectory signal representative of actual operation of the engine. The control module is configured to receive the reference control signal from the closed-loop reference module, the adaptation signal from the adaptation module, and the engine state trajectory signal. The control module is further configured to determine a demand signal based on the engine state trajectory signal, the adaptation signal, and the reference control signal, and output the demand signal to control operation of at least one engine component.

Abstract: A micro grid power control system may control a plurality of different sources of electrical energy, such as generators, renewable energy sources, and stored energy sources. The micro grid power control system may include hierarchical levels of control. At a system level, the micro grid power control system may include a system controller configured to selectively allocate the sources and centrally control electrical distribution of electric power within the micro grid based on system conditions to optimize system operation. Optimization of system operation may be dynamically varied by the system controller based on priorities and modeling of system operation. At a source level, each of the sources may include a source controller configured to optimize generation of electrical energy of the respective source. Optimization of a source with a respective source controller may be based on a source objective independently associated with each of the sources and source modeling.

Abstract: The disclosure describes a system that includes a closed-loop reference module, an adaptation module, and a control module. The closed-loop reference module is configured to execute a reference model that represents operation of an engine and determine a reference control signal and a reference state trajectory signal. The adaptation module is configured to determine an adaptation signal based on a difference between the reference state trajectory signal and an engine state trajectory signal representative of actual operation of the engine. The control module is configured to receive the reference control signal from the closed-loop reference module, the adaptation signal from the adaptation module, and the engine state trajectory signal. The control module is further configured to determine a demand signal based on the engine state trajectory signal, the adaptation signal, and the reference control signal, and output the demand signal to control operation of at least one engine component.

Abstract: The disclosure describes a system that includes a closed-loop reference module, an adaptation module, and a control module. The closed-loop reference module is configured to execute a reference model that represents operation of an engine and determine a reference control signal and a reference state trajectory signal. The adaptation module is configured to determine an adaptation signal based on a difference between the reference state trajectory signal and an engine state trajectory signal representative of actual operation of the engine. The control module is configured to receive the reference control signal from the closed-loop reference module, the adaptation signal from the adaptation module, and the engine state trajectory signal. The control module is further configured to determine a demand signal based on the engine state trajectory signal, the adaptation signal, and the reference control signal, and output the demand signal to control operation of at least one engine component.

Abstract: The disclosure includes a system that includes a real-time engine model module and an adaptive control module. The real-time engine model module is configured to determine an engine parameter estimate signal based on at least one feedback signal indicative of an operating parameter of an engine. The adaptive control module is configured to receive a power request signal and receive, from the real real-time engine model module, the engine parameter estimate signal. The adaptive control module is further configured to determine a power demand signal based on the power request signal and the engine parameter estimate signal, wherein the adaptive control module is configured to determine the power demand signal based on the power request signal using a set of control laws. The adaptive control module is further configured to output the power demand signal to control at least one component of the engine.

Abstract: A micro grid power control system may control a plurality of different sources of electrical energy, such as generators, renewable energy sources, and stored energy sources. The micro grid power control system may include hierarchical levels of control. At a system level, the micro grid power control system may include a system controller configured to selectively allocate the sources and centrally control electrical distribution of electric power within the micro grid based on system conditions to optimize system operation. Optimization of system operation may be dynamically varied by the system controller based on priorities and modeling of system operation. At a source level, each of the sources may include a source controller configured to optimize generation of electrical energy of the respective source. Optimization of a source with a respective source controller may be based on a source objective independently associated with each of the sources and source modeling.

Abstract: A multi-engine power system is described that includes a load requiring a total amount of electrical power, a first engine configured to provide a first portion of the total amount of electrical power to be provided to the load, and a second engine configured to provide a second portion of the total amount of electrical power to be provided to the load. The system further includes a controller configured to determine the total amount of electrical power to be provided to the load, estimate a respective service time associated with each of the first and second engines, and control each of the first and second engines to provide the total amount of electrical power to the load and to coordinate the respective service times associated with the first and second engines.

Abstract: The disclosure describes a system that includes a closed-loop reference module, an adaptation module, and a control module. The closed-loop reference module is configured to execute a reference model that represents operation of an engine and determine a reference control signal and a reference state trajectory signal. The adaptation module is configured to determine an adaptation signal based on a difference between the reference state trajectory signal and an engine state trajectory signal representative of actual operation of the engine. The control module is configured to receive the reference control signal from the closed-loop reference module, the adaptation signal from the adaptation module, and the engine state trajectory signal. The control module is further configured to determine a demand signal based on the engine state trajectory signal, the adaptation signal, and the reference control signal, and output the demand signal to control operation of at least one engine component.

Abstract: The disclosure includes a system that includes a real-time engine model module and an adaptive control module. The real-time engine model module is configured to determine an engine parameter estimate signal based on at least one feedback signal indicative of an operating parameter of an engine. The adaptive control module is configured to receive a power request signal and receive, from the real real-time engine model module, the engine parameter estimate signal. The adaptive control module is further configured to determine a power demand signal based on the power request signal and the engine parameter estimate signal, wherein the adaptive control module is configured to determine the power demand signal based on the power request signal using a set of control laws. The adaptive control module is further configured to output the power demand signal to control at least one component of the engine.

Abstract: A multi-engine power system is described that includes a load requiring a total amount of electrical power, a first engine configured to provide a first portion of the total amount of electrical power to be provided to the load, and a second engine configured to provide a second portion of the total amount of electrical power to be provided to the load. The system further includes a controller configured to determine the total amount of electrical power to be provided to the load, estimate a respective service time associated with each of the first and second engines, and control each of the first and second engines to provide the total amount of electrical power to the load and to coordinate the respective service times associated with the first and second engines.

Abstract: The present techniques provide for the processing of color tissue images based on image segmentation. In an exemplary embodiment, the color and texture features of pixels in a tissue image are used to generate a matrix of feature vectors. A subset of feature vectors is selected from the matrix of feature vectors and a set of colors and textures are derived using the tissue image and the subset of feature vectors. An initial segmented tissue image is then generated from this set of colors and textures.

Abstract: The present techniques provide for the processing of color tissue images based on image segmentation. In an exemplary embodiment, the color and texture features of pixels in a tissue image are used to generate a matrix of feature vectors. A subset of feature vectors is selected from the matrix of feature vectors and a set of colors and textures are derived using the tissue image and the subset of feature vectors. An initial segmented tissue image is then generated from this set of colors and textures.

Abstract: An RF coil assembly for use in a multiple receive-channel MRI system is provided. The RF coil assembly is configured as a multi-turn-element RF coil assembly 200 to operate as a surface-coil array in cooperation with the MRI system 100 which is configured to operate in a multiple-channel receive mode.

Abstract: A matrix coil for generating a variable magnetic field is provided, including a plurality of loops arranged in a series so as to have a substantially common axis and segmented into at least one arc-shaped segment, a variable current source for each of the arc-shaped segments, and a controller. The controller is configured to selectively vary an amount of current provided to each of the arc-shaped segments by the variable current sources so as to achieve a variable base field, one or more variable gradient fields, and one or more variable second order shim fields.

Abstract: In an alternate technique, a magnetic resonance imaging system comprises a set of gradient coils for producing controlled gradient field; a radio frequency coil for applying excitation signals to a subject of interest; a detecting coil for detecting magnetic resonance signals resulting from the excitation signals; and a control circuitry configured to energize the set of gradient coils, the radio frequency coil and to obtain a three dimensional phase wrapped image from the magnetic resonance signals detected by the detecting coils, and the control circuitry comprising a phase unwrap component to perform phase unwrapping in a volume of interest of the phase wrapped image to obtain a phase unwrapped image.

Abstract: A method and system for detecting iron using magnetic resonance imaging (MRI) is provided. The method comprises generating a substantially high magnetic field strength within the MRI system, acquiring magnetic resonance (MR) images by a pulse sequence adapted to create a magnetic field map of the brain for use in enhancing brain iron deposits, and, characterizing regions of interest using the magnetic field map to detect statistically relevant quantities of brain iron deposits to indicate a given disease.

Abstract: A method is provided for detecting a compromised condition of a patient including the steps of (a) providing for imaging in three dimensions a region of interest; (b) providing for generating a set of 3-D image data corresponding to the imaging; (c) providing for processing the set of 3-D image data for determining a first volume of an imaged first structure within the region of interest, wherein the volume of the first structure does not change substantially during adulthood over a time interval selected from the group consisting of months and years; (d) providing for processing the set of 3-D image data for determining a second volume of an imaged second structure within the region of interest, wherein a substantial change during adulthood of the volume of the second structure over a time interval selected from the group consisting of months and years is indicative of the compromised condition; and (e) providing for calculating a ratio of the second volume to the first volume.

Abstract: In an alternate technique, a magnetic resonance imaging system comprises a set of gradient coils for producing controlled gradient field; a radio frequency coil for applying excitation signals to a subject of interest; a detecting coil for detecting magnetic resonance signals resulting from the excitation signals; and a control circuitry configured to energize the set of gradient coils, the radio frequency coil and to obtain a three dimensional phase wrapped image from the magnetic resonance signals detected by the detecting coils, and the control circuitry comprising a phase unwrap component to perform phase unwrapping in a volume of interest of the phase wrapped image to obtain a phase unwrapped image.