Patents
Literature
Patsnap Copilot is an intelligent assistant for R&D personnel, combined with Patent DNA, to facilitate innovative research.
Patsnap Copilot

18161 results about "Intelligent control" patented technology

Intelligent control is a class of control techniques that use various artificial intelligence computing approaches like neural networks, Bayesian probability, fuzzy logic, machine learning, reinforcement learning, evolutionary computation and genetic algorithms.

User configurable raid system with multiple data bus segments and removable electrical bridges

A user configurable RAID system designed to provide RAID functions as well as mass storage functions in a non-RAID mode. Flexibility is built into the system to allow the user to configure the SCSI bus to which removable drive modules are connected into one or more channels to define some of the drive modules in a RAID set and others as stand-alone drives which are independently operated or logically grouped and operated in a non-RAID mode. Removable internal SCSI bridges allow the SCSI bus to be configured into one or more channels. In the RAID mode, the system is configured to prevent a wrong drive from being removed from the system in the event of a drive failure. The system automatically unlatches only the failed drive. The RAID system includes an intelligent control unit ("ICU"), a RAID controller and a modem. The ICU allows the system administrator to access the RAID system Monitor Utility so that the status of the system may be monitored and its configuration changed. The ICU also monitors the failure status of the various components of the system. The ICU has a built-in pager feature that can be configured with the Monitor Utility to page the system administrator via the modem when a component or system failure is encountered. The RAID controller controls the functions of the RAID set as programmed and configured using the Monitor Utility. The Monitor Utility may be remotely accessed using a computer via the modem. Redundant removable power supply and fan units are provided to improve system integrity. The removable power supply and fan units are configured such when the unit is plugged into the system housing, the fan is first turned on and the power through the unit is allowed to stabilize before turning on the power supply to begin providing DC power to the components in the system. A set of manual release buttons are provided for manually unlatching the drive modules from the system housing. A locking mechanism is provided for simultaneously locking all the manual release buttons.
Owner:MICRONET TECH

Electric vehicle lease management system on basis of charging piles and lease management method implemented by electric vehicle lease management system

The invention discloses an electric vehicle lease management system on the basis of charging piles. The electric vehicle lease management system comprises a system remote management control center, electric vehicles, the charging piles and intelligent terminals. A vehicle battery data acquisition module, a wireless communication module and an intelligent control module are mounted on each electric vehicle; an intelligent control unit and a communication module are mounted on each charging pile, each intelligent terminal is wirelessly communicated with the system remote management control center, and the wireless communication module of each electric vehicle is wirelessly communicated with the system remote management control center. The electric vehicle lease management system has the advantages that lease systems which are used by vehicle lease users and management staffs can be conveniently and quickly implemented by the aid of modern information network technologies, the users can order lease application and check relevant lease information via the intelligent terminals or directly via computers at any time in any places, and the management staffs can monitor various indexes such as electric vehicle location data and battery data in real time, and prompting effects can be timely realized.
Owner:WUHU HENGTIAN YIKAI SOFTWARE TECH CO LTD

Coolerless photonic integrated circuits (PICs) for WDM transmission networks and PICs operable with a floating signal channel grid changing with temperature but with fixed channel spacing in the floating grid

ActiveUS20050249509A1Requirements for a hermetically sealed package are substantially relievedEasy to controlLaser optical resonator constructionSemiconductor laser arrangementsElectro-absorption modulatorHermetic packaging
A coolerless photonic integrated circuit (PIC), such as a semiconductor electro-absorption modulator/laser (EML) or a coolerless optical transmitter photonic integrated circuit (TxPIC), may be operated over a wide temperature range at temperatures higher then room temperature without the need for ambient cooling or hermetic packaging. Since there is large scale integration of N optical transmission signal WDM channels on a TxPIC chip, a new DWDM system approach with novel sensing schemes and adaptive algorithms provides intelligent control of the PIC to optimize its performance and to allow optical transmitter and receiver modules in DWDM systems to operate uncooled. Moreover, the wavelength grid of the on-chip channel laser sources may thermally float within a WDM wavelength band where the individual emission wavelengths of the laser sources are not fixed to wavelength peaks along a standardized wavelength grid but rather may move about with changes in ambient temperature. However, control is maintained such that the channel spectral spacing between channels across multiple signal channels, whether such spacing is periodic or aperiodic, between adjacent laser sources in the thermally floating wavelength grid are maintained in a fixed relationship. Means are then provided at an optical receiver to discover and lock onto floating wavelength grid of transmitted WDM signals and thereafter demultiplex the transmitted WDM signals for OE conversion.
Owner:INFINERA CORP

Safe state recognition system for people on basis of machine vision

The invention discloses a safe state recognition system for people on the basis of machine vision, aiming to solve the problem that the corresponding intelligent control decision for the vehicle driving behaviour can not be formulated according to the safe state of the people in the prior art. The method comprises the following steps: collecting a vehicle-mounted dynamic video image; detecting and recognizing a pedestrian in an interested area in front of a vehicle; tracking a moving pedestrian; detecting and calculating the distance of pedestrian in front of the vehicle; and obtaining vehicle real-time speed; and recognizing the safe state of the pedestrian. The process of recognizing the safe state of the pedestrian comprises the following steps: building a critical conflict area; judging the safe state when the pedestrian is out of the conflict area in the relative moving process; and judging the safe state when the pedestrian is in the conflict area in the relative moving process. Whether the pedestrian enters a dangerous area can be predicted by the relative speed and the relative position of a motor vehicle and the pedestrian, which are obtained by a vision sensor in the above steps. The safe state recognition system can assist drivers in adopting measures to avoid colliding pedestrians.
Owner:JILIN UNIV

DC frequency converting air-conditioner compressor intelligent controller and control method thereof

The invention provides an intelligent controller used for a direct current (DC) frequency-conversion air conditioner compressor and a technical proposal of the control method thereof; the hardware proposal comprises a rectifier filter circuit and a power module which are electrically connected sequentially; the rectifier filter circuit (220) is also electrically connected with a single DSP controller used as a core processing unit by a switch power supply (240); the single DSP controller is also respectively and electrically connected with the power module, a communication isolation circuit which is used for communicating with the indoor machine of the air conditioner, a fan driving circuit (280), and a temperature sampling circuit (270); the control method comprises the steps as follows:the control software is embedded in the DSP controller; by a control type of dual close-ring FOC no-sensor magnetic field vector, the current ring at the internal ring realizes the decoupling controlto the driving current of the permanent magnetic synchronous motor of a compressor and indirectly controls the output torque of the motor; the speed ring at the external ring is used for controlling the working frequency of the compressor, thus not only meeting the stable requirement during fixed frequency but also meeting the dynamic response during the frequency conversion; and the control software comprises a primitive recursive function and a main interrupt function.
Owner:宁波德业变频技术有限公司

Autonomous underwater vehicle trajectory tracking control method based on deep reinforcement learning

ActiveCN108803321AStabilize the learning processOptimal target strategyAdaptive controlSimulationIntelligent control
The invention provides an autonomous underwater vehicle (AUV) trajectory tracking control method based on deep reinforcement learning, belonging to the field of deep reinforcement learning and intelligent control. The autonomous underwater vehicle trajectory tracking control method based on deep reinforcement learning includes the steps: defining an AUV trajectory tracking control problem; establishing a Markov decision-making process model of the AUV trajectory tracking problem; constructing a hybrid policy-evaluation network which consists of multiple policy networks and evaluation networks;and finally, solving the target policy of AUV trajectory tracking control by the constructed hybrid policy-evaluation network, for the multiple evaluation networks, evaluating the performance of eachevaluation network by defining an expected Bellman absolute error and updating only one evaluation network with the lowest performance at each time step, and for the multiple policy networks, randomly selecting one policy network at each time step and using a deterministic policy gradient to update, so that the finally learned policy is the mean value of all the policy networks. The autonomous underwater vehicle trajectory tracking control method based on deep reinforcement learning is not easy to be influenced by the bad AUV historical tracking trajectory, and has high precision.
Owner:TSINGHUA UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products