188 results about "Ship control" patented technology

The invention discloses an unmanned ship control method based on deep reinforcement learning in a multi-task scene. The method comprises the following steps: constructing dynamics and kinematics models of an unmanned ship; the method comprises the following steps: constructing a high-fidelity simulation environment based on Isaac Sim and a parallel training framework thereof, and respectively designing a state space and an action space for various unmanned ship tasks; reward functions are respectively designed; constructing an unmanned ship control strategy, and designing an algorithm framework of a centralized importance sampling and shearing strategy optimization mechanism based on an end-to-end deep reinforcement learning algorithm; and for different task scenes, multiple times of training-verification are performed on the strategy network through a PPO algorithm, and the trained strategy network is used for realizing multiple control tasks of the unmanned ship. According to the method, a high-fidelity simulation environment is constructed through Isaac Sim and a parallel training framework thereof, parallelization support which is crucial to deep reinforcement learning training is achieved, and various actual control tasks of the unmanned ship can be achieved.

The invention relates to the technical field of intelligent ship control, and particularly discloses an area control integration method and system based on an intelligent ship engine room, original operation data and multi-source communication data of equipment in each area of the engine room are collected, a unified real-time state vector is generated through protocol analysis and standardization processing, and a plurality of redundant processing nodes are processed in a unified mode. Synchronizing and verifying state data through a high-speed channel, constructing a global consistent state synchronization set, disassembling composite logic into atomic operation units with state constraints according to an upper-layer instruction and the synchronization set, packaging the atomic operation units into a private instruction sequence bound with the state, executing the instruction sequence by a main node, and executing the state synchronization set by a slave node; seamless switching to a standby node is realized through independent hardware monitoring when a fault occurs, and the standby node continuously executes based on the continuity of a state synchronization set, so that high-reliability uninterrupted operation of area control is realized; according to the method, the problems of instruction semantic distortion and single-point fault risk in heterogeneous equipment integration are solved, and the control accuracy and the intelligent level are improved.

The invention discloses a geometric constraint fitting point cloud filtering method for sea surface three-dimensional reconstruction, and belongs to the technical field of computer vision and three-dimensional reconstruction. The objective of the invention is to solve the problem of insufficient subsequent three-dimensional reconstruction precision caused by interference of reflection noise, mismatching points and the like in sea surface point cloud. The method specifically comprises the following seven steps: firstly, acquiring sea surface original point cloud through three-dimensional data acquisition equipment; a filtering technology is adopted to obtain a to-be-fitted point cloud; fitting a quadric surface through an improved RANSAC (Random Sample Consensus) algorithm to solve an initial parameter; constructing a comprehensive error function, and optimizing the model through gradient descent; effective inner points are screened through quadratic term coefficient constraint and a distance threshold value; and finally, iterating until a termination condition is met, and outputting an optimal effective point cloud. The method is high in noise rejection rate, the point cloud fits the sea surface form, and high-quality data support can be provided for sea surface fitting, sea wave simulation and unmanned ship control.

The invention provides an unmanned surface vehicle course tracking control method with signal quantization based on a double-expansion observer, and the method comprises the steps: building a third-order response type unmanned surface vehicle course control mathematical model according to the characteristics of a ship and the sea condition information of a surrounding environment; designing a double-expansion observer model for simultaneously estimating matched interference and non-matched interference in the ship course tracking control system and observing uncertain items and external interference in the ship control system; based on a backstepping method and a dynamic surface control algorithm, a course controller of the unmanned surface vehicle is designed, and the calculation complexity brought by a virtual control law is reduced; based on the Lyapunov stability theory, the stability of the designed unmanned surface vehicle course tracking control system with state quantization and input quantization is proved, all signals in a closed-loop system are consistent and bounded in a semi-global mode, and the tracking error is arbitrarily small by adjusting parameters of a controller.

The invention belongs to the field of ship control, and provides a self-adaptive active stabilization method and system for a ship. The ship is configured to be provided with a plurality of water pressing plate executing mechanisms, each water pressing plate executing mechanism comprises a water pressing plate assembly and an executor connected with the water pressing plate assembly, and the method comprises the following steps that ship body attitude information of the ship is obtained; calculating a target moment according to the hull attitude information; generating an execution instruction corresponding to each actuator according to the target torque; and the executor responds to the execution instruction so as to drive the connected water pressing plate assembly to execute water pressing movement. According to the self-adaptive active stabilization method and system for the ship, the ship can be effectively controlled to reduce shaking, and the navigation stability, comfort and safety of the ship are improved.

The invention discloses a ship autonomous collision avoidance decision-making method and system based on cognitive entropy near-end strategy optimization, and belongs to the field of intelligent ship control. The method comprises the following steps: acquiring ship and environment information, and constructing a state vector containing a collision risk index; the method comprises the following steps of: inputting a cognitive entropy into a cognitive entropy near-end strategy optimization decision model, introducing a cognitive entropy regular term under a near-end strategy optimization framework to regulate and control exploration and balance of a strategy, realizing smooth transition from high exploration to high utilization, and outputting a propulsive force / rudder angle instruction; after the instruction is executed, calculating a multi-component reward based on target proximity, track deviation, fused / collision risk and COLREGs compliance; and iteratively optimizing network parameters by utilizing rewards and state feedback. The problems that exploration and utilization of reinforcement learning in ship collision avoidance are difficult to balance and convergence efficiency is low are solved, and decision safety, compliance and training stability are improved.

Embodiments for a battery pack for an electric marine vessel are described herein. In a particular embodiment, a battery pack for an electric marine vessel comprises a waterproof chassis, a high voltage battery comprising a plurality of battery cells disposed within the chassis, positive and negative high voltage connectors disposed on a front flange of the chassis, a manual disconnect connector disposed on the front flange of the chassis, and a signals connector disposed on the front flange of the chassis, the signals connector configured for signal communication with at least a power distribution unit and a vessel control unit. A battery management system disposed within the chassis and coupled to the signals connector comprises a battery management controller, a plurality of relays operable by the battery management controller, and a plurality of sensors electrically coupled to the battery management controller.

The invention discloses a PID (Proportion Integration Differentiation) tracking control method based on error perception nonlinear gain, which is used for high-precision tracking control of an MIMO (Multiple Input Multiple Output) nonlinear system. Comprising the following steps: 1) constructing an adaptive gain by using current error information, historical error information and prediction error information; 2) realizing intrinsic integral saturation resistance through nonlinear integral design; and 3) complete autonomous operation can be realized without accurate system dynamics priori knowledge or manual adjustment. According to the method, the nonlinear compensation capability and the robust adaptive performance are enhanced while the structural simplicity of the PID controller is kept. Through rigorous Lyapunov analysis, the stability of the method to a non-linear system in a general form is verified, and the method shows excellent performance in both adjustment and time-varying reference tracking scenes. The method can be widely applied to the fields of linear motor servo systems, sea surface ship control, unmanned vehicle dynamics control and the like needing high-precision tracking control.

The invention relates to the technical field of ship control and navigation simulation, in particular to a ship trajectory visualization method and system based on combination of STM32 and Simulink, and the method comprises the following steps: an inertial measurement module and an ultra wide band positioning module collect attitude position information of a ship; the attitude position information is transmitted to an STM32 chip, the STM32 chip fuses the three-axis angular velocity, the three-axis linear acceleration and the three-axis geomagnetic data through a quaternion fusion algorithm to obtain a quaternion calculation result, and the quaternion calculation result and the position information in the three-dimensional space are fused to obtain fused data; the STM32 chip is used for fusing data, the fused data are packaged into data frames, the STM32 chip is used for transmitting the data frames to a ship model in a Simulink platform through a MAVLink protocol, the ship model is used for extracting the attitude angle and space coordinate information of the ship based on the data frames, and the visual motion trail of the ship is generated based on the attitude angle and space coordinate information of the ship. According to the invention, visual display and control algorithm verification are realized, and a semi-physical simulation closed-loop process is completed.

This invention relates to the field of ship control technology, and more particularly to an intelligent switching and control method for ship operation modes. The method involves collecting data on ship attitude, propulsion system, operating devices, and the marine environment, and establishing a multi-dimensional state-space model that integrates the semantics of the operational task and the physical constraints of the ship. Projecting this model yields a state vector to identify the current operation mode. Based on a preset operational process and the current mode, combined with the ship's dynamic response characteristics and the coupling relationship of the operating devices, a comprehensive optimization objective function incorporating time cost and energy consumption is established to solve for the target mode and a hierarchical switching strategy. Based on the switching strategy, two-layer control commands are generated for the propulsion system and operating devices. A ship response prediction model is established to perform rolling predictions of the switching process and generate trajectory correction commands, driving the system to collaboratively complete the mode switching. This invention achieves intelligent switching and precise control of ship operation modes, improving the safety and efficiency of the switching process.

The application provides a method and system for controlling air-borne radioactivity in a control area cabin of a water surface nuclear power ship. A gradient negative pressure is formed in the control area cabin of the nuclear power ship, such as a nuclear power plant containment cabin, an auxiliary cabin, a pollution monitoring and decontamination cabin, and an access passage cabin, by using facilities such as an exhaust fan and a negative pressure compressor, so that the air-borne radioactivity generated during normal operation of the nuclear power plant is controlled. The application can better limit the range of air-borne radioactivity in the control area cabin, prevent the air-borne radioactivity from spreading and leaking to other cabins, and provide strong protection for the radiation safety of personnel on the nuclear power ship.

The invention discloses a radial well cluster mining system and method for deep sea natural gas hydrate and shallow gas. The small and medium-sized workboat is sequentially connected and fixed with the seabed drilling machine and the multi-well guide suction anchor, and the small and medium-sized workboat controls the seabed drilling machine through an umbilical cable to complete drilling and arrangement of a vertical well and an inclined well of drilling and fixing integrated hydrate in the multi-well guide suction anchor; the vertical well and the inclined well are connected with a multi-pipe Christmas tree arranged on the multi-well guide suction anchor, and then the multi-pipe Christmas tree is connected with a mining and transportation pipeline through a seabed supercharging electric submersible pump to form a natural gas hydrate one-machine multi-well type radial well cluster efficient mining and transportation path. According to the hydrate anchor base radial well cluster mining system, the mining range is greatly enlarged, the mining efficiency is improved, integrated drilling and one-machine multi-well arrangement are achieved through the seabed drilling machine, the operation cost is remarkably reduced, the drilling and mining efficiency is improved, and the integrated operation process of drilling, well cementation, well completion and mining of the deep sea hydrate reservoir is achieved.

The application relates to a kind of unmanned ship control method based on fixed time expansion state observer, comprising the following steps: step S1: the state information of unmanned ship and the information data of various sensors are acquired, and are sent to control center;Step S2, the information data is classified and matched according to data type, and the corresponding state information of unmanned ship is obtained;Step S3: fixed time expansion state observer is constructed, disturbance and uncertainty term are accurately estimated and controller is compensated, and the estimation value of the auxiliary speed variable of unmanned ship is obtained;Step S4: the desired trajectory is specified, and the actual position in the state information is subtracted to obtain the position error;Step S5: the desired control input of unmanned ship is obtained through the controller;Step S6: the control input is packaged and checked, and is sent to the main control of unmanned ship;Step S7: the main control controls unmanned ship to execute control command, and completes the trajectory tracking task.The application realizes that unmanned ship accurately and stably tracks desired trajectory.

This application discloses a remote start-stop control system and method for ships, including a ship-end system and a shore-end system. The ship-end system includes: a ship-end sensing unit for acquiring ship status information and execution result data; a ship-end communication unit for uploading ship status information and execution result data to the shore-end system and receiving remote control commands; and a ship-end control unit for performing preparation control, start control, and stop control of the ship's power system according to the remote control commands. The shore-end system includes: a shore-end control unit for receiving remote control commands; a shore-end communication unit for receiving ship status information and execution result data and issuing remote control commands; and a shore-end display unit for displaying ship status information, remote control commands, and execution result data. This application can reduce the system's reliance on manual labor, improve its intelligence, operational efficiency, and reliability, and can be widely applied in the field of ship control technology.

A human-machine integrated ship control method based on a shared panel, the method comprising the following steps: our own ships in a fleet collecting multi-source sensing data by means of a multi-source sensor; fusing the multi-source sensing data to obtain fused data, and calculating a future track of an enemy target ship; sharing encrypted fused data to our own fleet, and synchronously receiving encrypted fused data of other shared panels; after receiving the encrypted fused data, our own ship determining a planned route and an intention of our own ship, and sharing the planned route and the intention; and a human commander changing a track or a combat objective of the own ship, and the rest of our own ships re-optimizing planned paths and then sharing same, so as to complete real-time human-machine integrated ship control. A multi-machine interaction mode based on shared panels enhances the cognitive capability and coordination of marine fleets on law enforcement and rights protection missions.

The invention is suitable for the field of offshore platform or intelligent ship control, and provides an offshore interference estimation and observer design method using multi-source sensor fusion, comprising the following steps: S1, sensor data acquisition and preprocessing; s2, constructing an interference estimation model; s3, converting a state space model; according to the invention, based on a'time alignment + coordinate conversion 'structure of a sensor data acquisition and preprocessing module, the problems of time sequence deviation and coordinate system difference of multiple sensors are solved: time alignment ensures that data are synchronized at the frequency of 5Hz, and interference estimation delay caused by data asynchronization is avoided; coordinate conversion is combined with ship attitude and navigational speed to obtain accurate interference data under an absolute coordinate system, and compared with a traditional preprocessing method, the interference data accuracy is improved by 40%-50%, and reliable input is provided for subsequent modules.

Embodiments of the present application disclose a kind of control method, device and ship control system of ship.The method comprises: obtaining the current heading of the ship, target heading, wind force, wind direction, flow force and flow direction;According to the current heading, the wind force, the wind direction, the flow force and the flow direction, determine total yaw torque;According to the difference of the current heading and the target heading, determine feedback torque;According to the total yaw torque and the feedback torque, determine rudder direction angle, and according to the rudder direction angle, control the ship to adjust to the target heading.The technical scheme provided by the embodiments of the present application can ensure that the ship travels according to the target heading, reduce the risk of deviation of the ship, improve the accuracy and stability of ship navigation, and also do not need manual control, reduce labor cost.

The invention provides an unmanned ship course control method and system, relates to the field of automatic control, and solves the technical problems of navigation track control deviation, response lag and insufficient anti-interference capability of the existing unmanned ship control technology. The method comprises the following steps: acquiring the position, attitude, motion state and environmental data of an unmanned ship in real time through a shipborne sensor system, and performing fusion processing on the acquired data based on an extended Kalman filtering algorithm to obtain system state vectors including a course angle, an angular velocity, a drift angle, a wind speed and a flow velocity; according to a preset target path and the system state vector, an expected course angle is obtained through calculation by adopting a self-adaptive integral sight guidance algorithm; the deviation between the expected course angle and the course angle in the system state vector is used as input data, and a rudder angle control quantity is calculated by using an adaptive sliding mode control algorithm; and driving the unmanned ship to track the expected course angle according to the rudder angle control quantity.

This invention discloses an intelligent recovery system for mother and daughter ships and its recovery method. The intelligent recovery system includes a mother ship and at least one daughter ship. The mother ship includes a hull, a hull frame, and a hull body. The hull includes left and right hollow floating materials. The hull frame connects the hull and the hull body. The hull body is a rectangular waterproof hull. The inner sides of the left and right hollow floating materials and the lower part of the rectangular waterproof hull body form a receiving space for recovering the daughter ship. The daughter ship's hull is set to a first color. The mother ship captures an image from directly in front of it using a camera, identifies the daughter ship based on a color recognition algorithm and the first color, determines the azimuth angle of the daughter ship relative to the mother ship, and then combines this with the distance between the mother and daughter ships to obtain the Cartesian coordinates of the daughter ship relative to the mother ship. Based on the mother ship's attitude angle and the daughter ship's Cartesian coordinates relative to the mother ship, the mother ship controls the PWM of a brushless motor to adjust the speed, achieving a dual-loop control of position and angle, thereby controlling the mother ship to move towards the daughter ship to complete the recovery operation. This invention can efficiently complete the recovery task.

The invention provides an unmanned ship control method and device, electronic equipment, a storage medium and a program product, and relates to the technical field of unmanned ship control, and the method comprises the steps: obtaining the operation data and environment data of an unmanned ship in a preset time period; detecting the system state of the unmanned ship based on the operation data to obtain a system state self-inspection result, obtaining a system fault prediction result based on the operation data and the environment data, and obtaining an environment risk assessment result based on the environment data; fusing the system state self-checking result and the system fault prediction result to obtain a system state fusion result; determining a starting strategy of the unmanned ship according to the environmental risk assessment result and the system state fusion result; and controlling each subsystem of the unmanned ship to execute corresponding operation according to the starting strategy. According to the invention, the misjudgment rate of remote starting of the unmanned ship can be reduced, and meanwhile, the starting safety and the starting success rate in a complex environment are improved.

The invention provides a self-adaptive wind feedforward unmanned ship course control system based on active disturbance rejection, and belongs to the technical field of unmanned ship course control. The system comprises an ultrasonic anemometer for collecting relative wind speed and relative wind direction; the gradient descent module outputs compensation gain based on the difference value between the actual course angle and the expected course angle; the wind feedforward module receives the relative wind speed, the relative wind direction and the compensation gain and outputs wind disturbance compensation; the expansion state observer outputs an actual course angle pre-estimated value, an actual course angle differential pre-estimated value and other unknown disturbance pre-estimated values; the non-linear state error feedback unit performs non-linear combination by using the state error to obtain an expected control quantity; the disturbance compensation unit determines the control quantity of the unmanned ship based on the expected control quantity, the wind disturbance compensation and other unknown disturbance estimation values. Rapid compensation of wind disturbance is achieved through self-adaptive wind feedforward control, and the response speed and stability of sailing direction control of the unmanned ship in a complex wind field are stably improved.

The invention provides an intelligent monitoring and early warning method and system for real-time ship dragging, and the method comprises the steps: firstly obtaining trajectory data in a normal anchoring state based on a ship control simulator, extracting a bias width, a to-ground navigational speed and a heading change rate as dragging monitoring indexes, and constructing a standard cloud model of each index through employing a Gaussian function; inputting the indexes collected in real time into the corresponding cloud model to obtain a membership degree, and calculating a real-time dragging probability in combination with an entropy weight method; net resultant force is calculated based on wind, flow and anchor chain parameters, and the drift velocity vector range after anchor dragging is estimated; aIS data are used for fitting an actual anchor position, a drift end point set is generated through Monte Carlo simulation, and four drift danger level intervals of danger, partial danger, partial safety and safety are divided; generating a ship space density distribution diagram covering the interval in combination with kernel density estimation; finally, the dragging probability and density information are fused to calculate a comprehensive risk value, acousto-optic grading early warning is triggered according to a preset threshold value, and high-precision and early-warning intelligent prevention and control of the dragging risk are achieved.

A marine vessel control system operable to be used with a shallow water anchor and a motor. The marine vessel control system comprising a memory and a processor. The processor is configured to receive a user command to maintain a position of a marine vessel, receive sonar data, determine a water depth relative to a water bottom based on the sonar data in response to receiving the user command, and transmit a command to use the shallow water anchor and / or the motor based on the water depth.

A thermal system for a marine vessel includes a thermal liquid circuit; a pump system for circulating a thermal liquid in the thermal liquid circuit; a number of thermal consumers; and a control device for controlling the pump system. The thermal consumers are arranged in parallel in the thermal liquid circuit, and the thermal consumers are arranged in series with respective Pressure Independent Control Valves (PICVs). A differential pressure sensor is adapted to sense a differential pressure indicative for the differential pressure over a critical one of the Pressure Independent Control Valves, and a signal from the differential pressure sensor is used by the control device as basis for controlling the pump system.

Machine learning device (2) which learns a correlation between shipping control information (X1n) obtained by checking an object during its shipping and operational alarm information (X2n) issued during the operation of the object, and which includes: - a condition monitoring unit (21) that monitors the shipping control information (X1n) and the operational alarm information (X2n) as data input from an environment (1), and - a learning unit (22) which generates a learning model based on the shipping control information (X1n) and operational alarm information (X2n) monitored by the condition monitoring unit (21), wherein the object includes a motor the environment (1) comprises an engine control device (11) that controls the engine during its shipment and outputs the shipping control information (X1n), and an engine control device (12) that gives an alarm during the operation of the engine and outputs the operating alarm information (X2n), The shipping control information (X1n) includes control element results associated with a motor model and motor inspection date, an insulation resistance value, an earth resistance value, a current value and / or a switching impulse voltage for the motor, and The operating alarm information (X2n) includes an overcurrent alarm, a noise alarm and / or an overload alarm for the motor.

A ship control device is provided with an input unit capable of acquiring operation inputs from each of a first operator used in a low-speed navigation control mode and a second operator used in a high speed navigation control mode, and a control unit for determining a target direction and a throttle opening in the direction control at the time of navigation based on the operation inputs acquired in the input unit. The low-speed navigation control mode has a manual operation control mode by the operation of the first operator and an automatic navigation control mode for holding a direction or a throttle opening using the target direction. The control unit is provided with a setting unit for setting the target direction and the throttle opening used for automatic navigation based on the operation input to the first operator in the automatic navigation control mode.

The invention relates to the technical field of ship control, in particular to an unmanned ship seaborne path planning system and method.The planning system comprises a vision module, a laser radar, a Beidou data receiving module, an inertial navigation system, a log, a data switch, an industrial personal computer, an encoder, a propelling device and a controller; the industrial personal computer is connected to the Beidou data receiving module, the inertial navigation system, the vision module, the laser radar and the data switch, the log is connected to the data switch, the encoder is connected to the propulsion device, the controller is connected to the encoder, the vision module is installed on the front portion of the unmanned ship, and the laser radar is installed on the front portion of the unmanned ship. The propelling device is installed on the rear portion of the unmanned ship. According to the invention, the technical problem that the path planned by the one-way path planning method of the unmanned ship in the prior art has many break points and is not smooth is solved, the calculation efficiency of the A star algorithm is improved, the calculation time is reduced, and the path planning speed is accelerated.

The invention discloses a mechanical-electrical-hydraulic joint simulation method, system and device and a medium, and belongs to the technical field of ship control, the method comprises the following steps: obtaining input parameters, and obtaining target expected data through analog calculation according to the input parameters; performing simulation operation in an electromechanical hydraulic joint simulation model by taking the input parameters as input to obtain first simulation data; on the basis of the deviation between the first simulation data and the target expected data, hydraulic side parameters are adjusted, simulation operation is conducted in the mechanical-electrical-hydraulic joint simulation model again, and iteration updating is conducted on the first simulation data; and obtaining second simulation data under the condition that the deviation between the first simulation data and the target expected data is within the first threshold range and meets the security constraint. Simulation operation is carried out in an electromechanical hydraulic joint simulation model, a mechanical structure, a hydraulic loop and a control strategy form a whole for simulation operation in a simulation stage, iteration is continuously carried out according to a simulation operation result, and therefore the deviation between target expected data and target expected data is reduced.

The invention discloses a Beidou measurement unmanned ship control method and system based on a hovering unmanned aerial vehicle, and belongs to the field of unmanned ship overwater measurement, and the method comprises the steps: receiving first command data transmitted by a shore remote controller through a local area network; forwarding the first command data to a Beidou measurement unmanned ship through a local area network, so that the Beidou measurement unmanned ship completes navigation parameter setting according to the first command data and performs water area data acquisition; and in the acquisition process, the downloaded first differential data is transmitted to the Beidou measurement unmanned ship through a local area network, so that the Beidou measurement unmanned ship adjusts the real-time position of the ship body during water area data acquisition according to the first differential data, and therefore, the real-time position of the ship body during water area data acquisition can be adjusted according to the first differential data. The water area measurement range of the Beidou measurement unmanned ship can be expanded by hovering the unmanned aerial vehicle.

The invention relates to the technical field of unmanned ship control, in particular to an unmanned ship control method, which is used for upgrading a sensing device of an unmanned ship so as to obtain more accurate environmental data. According to the characteristics of unmanned ship control, a deep learning algorithm is designed and optimized, so that the deep learning algorithm can more effectively extract characteristics from sensing data and generate a control instruction. On the basis of a deep learning algorithm, an automatic intervention mechanism is designed, and when the control of the unmanned ship is interfered by the external environment, a control strategy can be automatically adjusted to maintain the accuracy and stability of the control. And a real-time monitoring system is established, and the control process of the unmanned ship is monitored and evaluated in real time. By collecting and analyzing feedback information of the unmanned ship, the performance of the automatic intervention mechanism is continuously adjusted and optimized. The problem caused by the lack of an effective automatic intervention mechanism of the unmanned ship is effectively solved, and the accuracy and stability of unmanned ship control are improved.