19 results about "System reconfiguration" patented technology

A system receives a natural language request for configuring a computing infrastructure using a cloud platform. The system executes a machine learning based language model to generate infrastructure-as-code (IaC) to configure a cloud platform to obtain the desired computing infrastructure. The system may display the IaC generated by the machine learning based language model via a user interface as an example for use by the user. The system may send instructions to the cloud platform to provision computing infrastructure in accordance with the IaC obtained from the machine learning based language model. The system may repeatedly determine whether the desired computing infrastructure is deployed on the cloud platform and if the computing infrastructure currently provisioned on the cloud platform fails to match the desired computing infrastructure according to the natural language request, the system reconfigures the computing infrastructure deployed on the cloud platform.

A system receives a natural language request for configuring a computing infrastructure using a cloud platform. The system executes a machine learning based language model to generate infrastructure-as-code (IaC) to configure a cloud platform to obtain the desired computing infrastructure. The system may display the IaC generated by the machine learning based language model via a user interface as an example for use by the user. The system may send instructions to the cloud platform to provision computing infrastructure in accordance with the IaC obtained from the machine learning based language model. The system may repeatedly determine whether the desired computing infrastructure is deployed on the cloud platform and if the computing infrastructure currently provisioned on the cloud platform fails to match the desired computing infrastructure according to the natural language request, the system reconfigures the computing infrastructure deployed on the cloud platform.

The cloud service provider reconfigures the memory subsystem during routine operations while minimizing the amount of time the server is not online. Server downtime is reduced by offloading reconfiguration of system memory to an operating system with the assistance of a platform. The operating system enumerates potential memory configurations and associated performance characteristics of the memory subsystem in an abstract manner and performs reconfiguration of the memory subsystem without a cold reset. When the operating system considers that reconfiguration of the memory subsystem is necessary, the operating system checks the enumerated memory subsystem configuration provided by the system firmware. After selecting the memory subsystem configuration, the operating system initiates a reconfiguration process. The reconfiguration process saves any existing memory context to the secondary device, requests system firmware to perform memory subsystem reconfiguration, and restores the existing memory context from the secondary device after the memory subsystem reconfiguration has completed.

The application discloses a kind of multi-sensor data fusion and online reconfiguration method based on planetary topology structure, including the following steps, construct three-layer multi-sensor data fusion framework based on planetary topology structure, with sensor as outer layer satellite, the subsystem of two two combinations of sensor as middle layer planet, inner layer is main filter;Two-stage fault detection unit is set in satellite and planet layer, sensor fault information is provided by sensor, the effective probability of subsystem is obtained by substituting chi-square test value into fuzzy membership function by subsystem;Filter system reconfiguration table is designed, when fault occurs, the influence brought by fault is reduced online when system reconfiguration is carried out to multi-sensor data fusion system;Finally, global state estimation is completed in inner layer main filter based on the fault information of sensor and subsystem.

This disclosure relates to methods, apparatus, devices, storage media, and computer program products for generating FPGA measurement and control systems. It generates development data describing the structure and function of the target FPGA measurement and control system based on received system configuration description text data, automatically extracts matching hardware IP cores, embedded drivers, and host computer interface templates from a preset resource library, and automatically completes logic engineering construction, constraint generation, synthesis, placement and routing, and bitstream compilation using the FPGA development environment. Then, it automatically generates embedded processor control programs, communication interface programs, system image files, software development kits, and graphical user interface programs based on the generated files, and supports system reconfiguration and automatic optimization using difference analysis. This application enables rapid construction and reconfiguration of FPGA measurement and control systems through a unified configuration description, reducing development complexity and lowering the technical threshold while improving development efficiency. It is suitable for the rapid development of automatic measurement and control equipment and software-defined hardware systems.

The invention discloses a self-evolutionary computing system based on dynamic logic and recursive tensor, which defines a dynamic logic system comprising an uncertainty state (U-State) and an abnormal evolutionary state (A-State), and a logic value set of the dynamic logic system is {-1, 0, + 1, U, A}. The system generates a high-dimensional solution space through iteration of a recursive tensor, when system-level contradiction is caused by exploration of a U state, an A state is triggered, then a Meta-System Receiving mechanism is started, a new rule is searched in the solution space and permanently integrated into the system, and dimension transition of system functions is achieved. According to the method, normal form transformation of a computing system from'preset instruction execution 'to'autonomous knowledge creation' is realized, and a fundamental solution is provided for solving'unknown problems' in the fields of general artificial intelligence, adaptive control systems and the like.

Reconfiguring a storage system based on resource availability, including: limiting a number of storage devices in a storage system that may be simultaneously servicing write operations; determining that an amount of required write bandwidth has changed; and subsequent to determining that the amount of required write bandwidth has changed, adjusting, by a computer processor, the number of storage devices in the storage system that may be simultaneously servicing write operations.

A battery charging system includes a buck switching converter configured to operate in either a buck mode or a boost mode depending on a system reconfiguration, a linear charger having a first terminal and a second terminal, wherein at least one terminal of the first terminal and the second terminal of the linear charger is used for the system reconfiguration, and a switched capacitor converter configured to operate in either a 2:1 charge pump mode or a 1:2 reverse charge pump mode depending on the system reconfiguration.

The invention relates to the technical field of electric vehicle power battery management, and particularly discloses a high-precision active and passive intelligent equalization system for a vehicle power battery pack, which is characterized in that a unified clock signal is generated by establishing a global synchronous time sequence reference and adopting a temperature compensation crystal oscillator and a multi-stage phase-locked loop; based on a battery state parameter, identifying an equalization demand, and applying a golden section proportion to distribute an initial phase offset; accurate phase alignment of the pulse width modulation signals is realized through a digital delay phase locking technology; phase configuration is dynamically adjusted through spectral analysis and an iterative optimization algorithm to minimize bus current ripples; establishing a priority sequence according to the state change of the battery pack, and completing system reconfiguration by adopting a progressive switching strategy; according to the invention, the problem of beat frequency oscillation during multi-branch parallel equalization is solved, and the equalization precision of the battery pack, the system stability and the electromagnetic compatibility are improved.

The present invention discloses a stability control method for the reconfiguration of a metamorphic robot, including: 1. Generating the desired trajectories of each joint during the reconfiguration of the metamorphic robot; 2. Inputting the deviations between the desired trajectories of the joints and the mass-centroid adjustment sliders and the actual trajectories into a sliding mode controller, calculating and outputting the actual required torques for the movement of each joint and the mass-centroid adjustment sliders during the reconfiguration process; 3. Inputting the actual required torques for the movement of each joint and the mass-centroid adjustment sliders during the reconfiguration process into a dynamic model to obtain the actual trajectories of each joint and the mass-centroid adjustment sliders; 4. Calculating the actual value of the ZMP of the metamorphic robot using the actual trajectories of the movement of each joint and the mass-centroid adjustment sliders, and feeding it back to the fuzzy PID control module to form an upper closed-loop control for stability. The present invention can make the actual ZMP position of the whole vehicle approach the theoretical reference position, thereby improving the stability during system reconfiguration.

This invention discloses an atmospheric data system design method and atmospheric data sensing system based on a simplified bird configuration. The method includes: establishing a dimensionless generalized aerodynamic model suitable for the shape of a bird-configured aircraft, and constructing a standard database of surface pressure distribution of the target aircraft within its complete flight envelope; based on the standard database, with the atmospheric parameter calculation accuracy as the optimization objective, and under given engineering constraints, using a global optimization algorithm to automatically optimize the number and spatial location of pressure gauges; based on the optimal layout of the pressure gauges, implementing a hybrid-driven atmospheric parameter calculation algorithm, which first estimates initial values ​​through a data-driven approach, and then iteratively optimizes under the constraints of the dimensionless generalized aerodynamic model, outputting the calculation results; during the calculation process, integrating a fault diagnosis and fault tolerance mechanism based on reverse verification of machine learning models and physical models to achieve online identification of faulty sensors and system reconfiguration.

The embodiments provide for a method and system for dynamic configuration of a storage system to facilitate independent scaling of resources. The method and system include detecting a change to a topology of a storage system consisting of different sets of storage nodes, where at least one of the different sets of storage nodes has solid-state memory having differing storage capacities. Responsive to detecting the change, the storage system reconfigures to change an allocation of resources to one or more authorities that control a range of identifiers.

A method in an illustrative embodiment comprises collecting performance measurement data for processing of input-output operations sent by a host to a storage system for a first period of time prior to a configuration change and a second period of time subsequent to the configuration change, processing performance measurement data for the first period of time to determine a first point in a plane defined by a first performance metric and a second performance metric, processing performance measurement data for the second period of time to determine a second point in the plane defined by the first and second performance metrics, determining one or more characteristics of a positioning of the second point relative to the first point, and controlling execution of at least one automated action relating to at least one of the host and the storage system based at least in part on the one or more characteristics.

This invention provides a health management method for an unmanned surface vessel's integrated power system. It employs fault prediction-based early warning and system reconfiguration-based fault recovery, enabling fault early warning / pre-location, fault reconfiguration / pre-reconfiguration, and maintenance recommendations. This ensures the healthy operation of the integrated power system during unmanned surface vessel operation. During unmanned surface vessel operation, real-time monitoring of data reflecting the operational information of various devices in the integrated power system is performed. Alarm judgments are issued for each monitored data point. When a monitored data point exceeds a set threshold, a steady-state assessment is conducted. For monitored data determined to be in a non-steady-state state, a trend assessment is further performed. If the trend is normal, it indicates that the integrated power system is operating normally; if the trend is abnormal, fault location is performed, and then fault reconfiguration is carried out based on the fault location results.

The invention discloses a five-phase permanent magnet synchronous motor dead-beat fault-tolerant direct torque control method based on harmonic current closed-loop suppression, and the method comprises the steps: firstly constructing a subspace and a virtual voltage vector in the subspace based on a principle that the harmonic current of the subspace is suppressed to be zero in a normal operation state of a motor; and then, analyzing the distribution characteristics of a double-sub-space virtual voltage vector under any phase open-circuit fault, introducing a simplified dead-beat direct torque control structure, and inhibiting motor open-circuit disturbance by combining a disturbance observer. Furthermore, a virtual voltage vector of the subspace is selected in an open-circuit fault state, and the virtual voltage vector is combined with deadbeat direct torque control to realize closed-loop suppression of harmonic current of the subspace, so that the system can effectively suppress third harmonic current in both normal operation and fault states. According to the method, open-circuit fault diagnosis and system reconstruction are not needed, the torque ripple and the third current harmonic can be suppressed at the same time, and the method has a good engineering application prospect.

The application provides a configuration method for traction power supply system reconfiguration self-healing function, which adopts hierarchical configuration mode, and gradually expands mode flow according to optional power supply network configuration scheme by configuration tool, intelligently selects applicable action flow according to current network condition in engineering application, and realizes simple and rapid completion of reconfiguration self-healing function configuration. All action steps involved in the reconfiguration self-healing flow are switched, and switch type, action time, synchronous action and other switch attributes are set for each switch, which is beneficial to more accurate, effective and rapid completion of reconfiguration self-healing function. The method can provide real-time reconfiguration self-healing flow confirmation and modification, modify mode flow through real-time man-machine interaction interface without restarting the device, and send the modified reconfiguration self-healing mode flow to the dispatching end for confirmation, which is beneficial to flexible response to various unexpected field conditions.

The application discloses a reconfigurable intelligent car-milling composite machine tool and a reconfiguration method, and relates to the technical field of machine tools, and comprises system development and function design based on function modules, a topological structure based on a modular reconfigurable numerical control machine tool, an image recognition technology based on a deep convolutional neural network and an unloading system based on a structure light system guiding a mechanical arm, and a modular mechanical system and a reconfigurable control system are designed, the reconfigurable, modular mechanical system and the control system are designed, on the basis of maximizing the use of existing resources, efficient and economical conversion of hardware and software is realized, system reconfiguration is realized, and customized production capacity and function requirements are met.

An application may receive an indication of a status event. A first model may determine, based on a system component repository, a first system component associated with the status event. The first model may determine, based on the first system component and the status event, a modification to the first system component. A second model may generate one or more instructions to implement the modification to the first system component. The application may initiate execution of the one or more instructions to implement the modification to the first system component.