90 results about "Order control" patented technology

The invention relates to a mechanical arm safe obstacle avoidance control method and system based on a high-order control obstacle function, aiming at a multi-degree-of-freedom mechanical arm system with an obstacle in a task trajectory space, the high-order control obstacle function suitable for a high-relative-order system is used, and the method comprises the following steps: establishing a dynamic model of a multi-degree-of-freedom mechanical arm; designing a stable tracking controller based on the task trajectory in combination with a backstepping control method; an obstacle collision detection model is established, and safety constraints are provided for a control system through a high-order control obstacle function; and in combination with the control constraint and the optimal control problem, solving the optimal control input through quadratic programming. According to the method, the optimal task trajectory tracking can be completed on the premise that the tail end of the mechanical arm meets the safety constraint, the calculation complexity is effectively reduced, and the real-time performance is guaranteed.

The invention relates to an unmanned aerial vehicle path planning method and system based on GNN and high-order security constraints. The method comprises the steps that a navigation scene where an unmanned aerial vehicle is located is represented as a heterogeneous directed graph, message passing and feature updating are conducted through the GNN, a risk-aware attention mechanism is introduced, and an interpretable decision result is output; a differentiable HoCBF-QP optimization layer is introduced, an original control command output by a strategy network is used as input, quadratic programming with high-order control barrier function constraints is solved online, minimum-amplitude safety correction is carried out on the control command, and an actuator control command meeting safety constraints is output; starting a HoCBF safety shield during operation so as to strictly ensure that all safety constraints are met before execution; a calculation task of the whole control cycle is modeled into a directed acyclic graph form, and parallel execution is carried out on heterogeneous multiple cores by utilizing a real-time scheduling strategy. The problem that unmanned aerial vehicle navigation control is not effective and unified in three aspects of structure, safety and scheduling is solved.

Provided are an order processing method and apparatus and a warehousing system. The method comprises: acquiring a set of orders to be processed (202), said set comprising a plurality of orders to be processed; on the basis of order information of the plurality of orders and warehouse goods information of a plurality of storing apparatuses in a warehousing area, determining pre-hit information (204), the pre-hit information comprising a matching relationship between the orders and the storing apparatuses; on the basis of the pre-hit information, determining a first target storing apparatus from amongst the plurality of storing apparatuses, and determining a first target order that hits the first target storing apparatus (206); and controlling a target handling device to move the storing apparatus hit by the first target order to a target workstation, and controlling the target workstation to execute a picking task (208).

The invention relates to the technical field of data processing, in particular to an activation feeder outlet baffle adjusting device and method, and the device comprises a data collection module, a parameter optimization module, a control decision module and an execution module. The data acquisition module acquires load data of a conveying belt and material state data of a discharge port in real time; the parameter optimization module adopts a genetic algorithm to dynamically optimize first-order control parameters and second-order control parameters, the control decision module triggers an adjustment strategy based on a load deviation step by step, preferentially adjusts the width of a discharge port through the angle adjustment amount of an outlet baffle, and if the deviation is continuous, a vibration amplitude adjustment instruction is generated in combination with material state data; the execution module converts the adjusting quantity into displacement and vibration driving signals. Through hierarchical cooperative control and a closed-loop feedback mechanism, the problem of nonlinear control instability caused by dynamic changes of material humidity, granularity and viscosity is solved, the output matching precision under the multivariable coupling working condition is improved, and the material viscosity and the secondary bridging risk are reduced.

The invention discloses an offline multi-channel customer demand processing system based on grid control. According to the system, a layered system and a multi-module cooperation mode are adopted, WeChat, phone and other multi-channel customer appeal data are collected through the data collection layer, and after cleaning and fusion are conducted through the data processing layer, the functions of work order control, service quality analysis and the like are achieved through the service logic layer. The system utilizes a plurality of advanced algorithms, such as natural language processing, voice recognition, intelligent work order distribution and other technologies, improves the appeal processing efficiency and quality, constructs a service quality evaluation model, and carries out risk prediction and intelligent decision making. In the aspect of performance, a cache and distributed architecture is adopted to guarantee the response speed and the concurrent processing capability, and good expansibility and compatibility are achieved. In addition, data security and privacy protection are ensured through an AES encryption algorithm and a block chain technology, and an algorithm model is optimized regularly. The system effectively solves the problem of a traditional service mode, and improves the service level and customer satisfaction of a power enterprise.

The invention discloses a robot safe near-optimal motion planning method based on hybrid reinforcement learning, and belongs to the technical field of robot motion. The method comprises the following steps: initializing an initial state of a robot, a multilayer neural network weight and a high-order control barrier function HOCBF parameter; generating a target navigator through forward propagation of the multi-layer neural network; screening a safety controller from a safety control set defined by the HOCBF; fusing the target navigator and the safety controller to generate a final control strategy; calculating a Bellman error; and updating the initial state of the robot and the weight of the multi-layer neural network based on the final control strategy and the Bellman error. According to the invention, a neural network approximation target navigator and an HOCBF safety controller are deeply fused, so that a hybrid control system with a layered guarantee framework is constructed. The problem of safety guarantee failure caused by Lie derivative disappearance of a traditional CBF in a high-order system is solved, and meanwhile, the technical bottleneck that an existing HOCBF scheme is limited to local optimization is broken through.

The invention relates to the use of an electronic element (E) with at least one processor—and memory function (27b), for use as an arithmetic element (6) and / or computer element (6) and / or device element (2a) and / or component element (2a), the electronic element comprising an identification—(1c) and / or authentication function (1c) of a user in a digital network (12) by means of a computer-assisted, at least partly automated and / or autonomously ordered encrypted method (14e), and / or comprising a computer-assisted, at least partly automated and / or autonomously ordered control function (1b), wherein the electronic element (E) consists of at least one hardware element (27) and / or software (26).

The purpose of the present invention concerns a control command for a machine tool, and is to make it possible to adopt a high-frequency repetitive oscillation command, without restrictions on communication capacity, when acquiring a control command created by superimposing a command with repeatability on a normal move command such as a move command having no repeatability. The purpose can be achieved by: acquiring, from an higher-order control device, only information about the form of a command, and parameter information on numerical information relating to an amplitude, a period, and other feature amount; creating a repetitive movement command that is a command with repeatability only from the parameter information; and superimposing the repetitive movement command on a normal move command such as a move command having no repeatability.

The invention relates to the technical field of intelligent cabinets, and discloses an intelligent cabinet delivery control method and device, an intelligent cabinet and a storage medium. The intelligent cabinet delivery control method comprises the steps that when it is confirmed that a target intelligent cabinet is of a login-free delivery type, if a login-free delivery request corresponding to at least one cabinet operator is received, cell selection requests are sent to all the cabinet operators according to the login-free delivery request; obtaining a grid selection result and article waybill information sent by each cabinet operator; according to the grid selection result, determining a target grid, and when it is determined that the target grid is an unoccupied grid, generating a target delivery order associated with the target grid according to the article waybill information; and the target intelligent cabinets are controlled to execute grid opening operation corresponding to all the target grids, so that all cabinet operation parties put the to-be-delivered articles into the target grids and close the doors, and the state of the target delivery order is updated to be a delivered state. According to the invention, the delivery process is simplified, and the utilization rate and delivery efficiency of the cabinet are improved.

The invention discloses a flexible cooperative control method for an air exhaust system, a medium and equipment, and relates to the technical field of air exhaust system control, and the method comprises the steps: constructing a second-order control system of the air exhaust system; defining an optimization problem of the air exhaust system, and designing a penalty function; designing a flexible control algorithm of the air exhaust system, designing an augmented objective function according to the penalty function and the flexible control algorithm, and converting an optimization problem; designing an ADRC controller according to the second-order control system; performing optimization iteration on parameters of the augmented objective function according to ADRC, and continuously updating a converted optimization problem; and cooperative control of the air exhaust system is carried out by combining the optimization problem which is continuously updated and converted and a proportional differential controller. The control efficiency and robustness of the air exhaust system are improved, and the safety of the compressor of the air exhaust system is improved.

The invention discloses a man-machine interaction control method and device based on a high-order data driving control obstacle function, and the method comprises the steps: considering a mechanical arm dynamic model containing unknown parameters, and building an admittance model to generate a robot expected track conforming to interaction force feedback; constructing a robot nonlinear tracking controller based on a neural network; the method comprises the following steps: collecting input and output information of a robot system, establishing an equivalent dynamic data model, and designing a data-driven sliding mode adaptive controller; and a high-order control barrier function based on data driving is constructed, and a final control input is obtained by solving a quadratic programming problem under a unified framework of a control function and a data-driven sliding mode controller. According to the method, a more complex interaction control problem can be solved while robot dynamic model information is not needed, and reliable transient response and steady-state tracking precision are ensured under the condition that a robot dynamic model is unknown.

The invention relates to the technical field of unmanned aerial vehicles, in particular to a control method of a freight unmanned aerial vehicle, a scheduling system, electronic equipment and a storage medium. The control method comprises the steps of S1, controlling the unmanned aerial vehicle to fly to a working airspace S2, judging whether the unmanned aerial vehicle receives an order or not; s3, if the order is stopped, the unmanned aerial vehicle is controlled to return to the base; s4, if the order is received, judging whether there is an order in the working airspace; s5, if no order exists, controlling the unmanned aerial vehicle to fly to the circling airspace to wait for the order; s6, if the order exists, the unmanned aerial vehicle is controlled to take or deliver the goods; and S7, after the unmanned aerial vehicle completes delivery, the steps S2-S6 or the steps S5-S6 continue to be repeated. The unmanned aerial vehicles are dispatched to the working airspace by adopting the control method, the order is distributed to the unmanned aerial vehicles in the airspace according to the current situation, and compared with the process of taking off, taking goods and delivering goods according to the order information, the flight efficiency of the unmanned aerial vehicles is optimized, and the delivery speed of the unmanned aerial vehicles is improved.

The disclosure relates to systems and methods for facilitating efficient load balancing in a network interface controller (NIC). A network interface controller (NIC) capable of efficient load balancing between hardware engines is provided. The NIC may be equipped with a plurality of ordering control units (OCUs), queues, selection logic blocks, and allocation logic blocks. The selection logic block may determine an OCU from the plurality of OCUs for a command from the queue, which may store one or more commands. The allocation logic block may then determine a selection setting for the OCU, select an egress queue for the command based on the selection setting, and send the command to the egress queue.

The invention provides a spot welding robot tail end arm zero motor fixed point control method and equipment. The method comprises the following steps: constructing a kinetic model of the spot welding robot, and converting the kinetic model into a second-order control model; the second-order control model is converted into a first-order controllable model through the intermediate parameters, and the path constraint condition of movement of the tail end arm of the spot welding robot is determined according to the first-order controllable model; determining a first joint controller and a second joint controller of the spot welding robot by adopting the path constraint condition and a first-order controllable model; and a first joint controller and a second joint controller are adopted to control the kinetic model, and it is ensured that the tail end arm of the spot welding robot moves to a preset point position. Dependence of the spot welding robot on an execution motor can be reduced, the production cost of industrial products machined by the spot welding robot is reduced, and the market competitiveness of the industrial products is improved.

The invention discloses an energy storage resource cooperative control method, system and device and a medium, and belongs to the field of electric power systems.The method comprises the steps that real-time topology, power flow and device data are obtained by periodically scanning the operation state of a power grid, and an adjustable energy storage resource pool is dynamically updated; comprehensively evaluating the security risk level of the power grid according to the multi-dimensional analysis results of the electric power and electric quantity balance, the system power flow, the reactive voltage and the stability; according to the risk level assessment result, an optimization control strategy is generated in combination with optimization control with the minimum adjustment cost as the target, and a preset control mode of sequence control based on a preset priority or proportional control based on a sharing factor; and finally, the control strategy is issued to each energy storage node for execution. Therefore, by implementing the method, dynamic self-adaption and refined coordination of power grid safety control can be realized, and the coping capacity and the operation reliability of the power grid to high-proportion new energy access are effectively improved.

The invention provides a paperboard production steam pressure self-adaptive temperature control system and method based on order association, belongs to the technical field of paperboard production, and solves the problem that a steam pressure set value cannot be controlled according to an associated order when a conventional steam pressure temperature control system is used for paperboard production. Therefore, the technical problems of low steam pressure accuracy and poor energy-saving effect are solved. The paperboard production steam pressure self-adaptive temperature control system based on order association comprises an order information management device, a data analysis and processing unit and a data acquisition unit, the outside of the order information management device is in wireless communication connection with the data analysis and processing unit, and the outside of the data analysis and processing unit is electrically connected with the data acquisition unit. According to the invention, the order information management device obtains the order, and under the action of the data analysis processing unit, the data analysis processing unit calculates the approximately required steam pressure according to the characteristics of the order, and quickly adjusts the main adjusting valve to realize quick response.

The invention discloses an intelligent regulation and control method and system for an electric precipitator, and relates to the technical field of intelligent regulation and control, and the method comprises the steps: collecting data through a sensor, constructing an electric precipitation process mathematical model, and simplifying a deep learning model to obtain a state space model; estimating a current state parameter of the state space model based on sensor data, and recurring future output in combination with a deep learning model in a given prediction time domain and a control time domain; setting an adaptive weighted quadratic objective function of a tracking error and a control increment, and outputting a security constraint; and calculating an optimal control parameter sequence by using a genetic algorithm in combination with a target and constraints, executing first-order control, and updating control parameters in a rolling manner. According to the method, the control precision and the response stability of the electric dust remover are remarkably improved, the energy consumption of the system is effectively reduced, and the dust removal efficiency is improved. And meanwhile, the self-adaptability of the system is further enhanced, so that the system can always maintain efficient operation under different working conditions.

Control arrangement (10) for an electric stunning device (1), wherein the electric stunning device (1) is designed to introduce an electric current into a slaughtered animal, characterized in that a control unit (11) is provided, by means of which at least one characteristic of the electric stunning device (1) is determined.

The invention relates to a method for determining the position of a motor, a phase-locked loop and a motor control system. The method comprises the following steps: acquiring a first counter electromotive force and a second counter electromotive force corresponding to the motor; the method further comprises the step of determining a position error between the actual position and the observation position of the motor according to the first counter electromotive force and the second counter electromotive force based on a multi-order control module, and the order of the multi-order control module is larger than 3. Further, the method includes determining an observed position of the motor based on the position error. As the multi-order control module can track high-order dynamic changes such as acceleration and jerk, dynamic lag errors caused by acceleration / deceleration of the motor can be eliminated. According to the method for determining the position of the motor provided by the embodiment of the invention, accurate prediction of the position of the motor can be realized when the motor is in any working condition, so that the stability and the reliability of a motor control system are improved.

A navigation information processing method, apparatus, and computer-readable storage medium for coordinating vehicle navigation with item ordering and preparation. The method displays a navigation interface with an order control for generating orders during vehicle navigation operations. Order information including the navigation destination is generated and displayed based on user operations. A first duration is determined from real-time remaining travel time to the navigation destination, while a second duration is determined from real-time preparation and delivery times of the target item. When the first duration is less than or equal to the second duration, a preparation state is generated and displayed to indicate the target item is in preparation, enabling synchronized timing between arrival and item preparation.

A computer-supported manufacturing method for manufacturing workpieces from a workpiece blank according to a manufacturing plan using a machine tool (18), has a processing device. The method includes at least partly transmitting the manufacturing plan by means of an order control device. At least one work piece is manufactured from the workpiece blank according to the manufacturing plan. The manufacturing progress of the processing device is determined during the manufacturing of the at least one workpiece by the order control device. The manufacturing plan is changed on the basis of the manufacturing progress during the manufacturing of the at least one workpiece by means of the order control device.

This disclosure relates to systems and methods for facilitating efficient load balancing in a network interface controller (NIC). A network interface controller (NIC) capable of efficient load balancing across hardware engines is provided. The NIC may be equipped with multiple ordering control units (OCUs), queues, selection logic blocks, and allocation logic blocks. The selection logic block can determine an OCU from the multiple OCUs for commands from the queues, which may store one or more commands. The allocation logic block then determines selection settings for the OCU, selects an egress queue based on the selection settings for the command, and sends the command to the egress queue.

According to embodiments of the present disclosure, a method, an apparatus, a device, a computer readable storage medium and a computer program product for an autonomous vehicle are provided. The method comprises: in response to the autonomous vehicle currently not being assigned a passenger order, determining a test order list associated with the autonomous vehicle; determining a target test order from the test order list based on an execution mode of the test order list; controlling the autonomous vehicle to travel towards a first starting point location of the target test order; and before the target test order is completed, in response to the autonomous vehicle being assigned a target passenger order, controlling the autonomous vehicle to travel to a second starting point location of the target passenger order to serve the target passenger order. Based on such a manner, embodiments of the present disclosure can improve the utilization rate of the autonomous vehicle.

The invention discloses a variable fractional order active-disturbance-rejection control method applied to a second-order controlled system, and relates to the field of second-order controlled system control, and the method comprises the steps: building a variable fractional order expansion state observer according to a state equation of the second-order controlled system; according to the variable fractional order expansion state observer, a fractional order proportional differential controller is established, and variable fractional order active disturbance rejection control applied to the second-order controlled system is completed. According to the invention, the problem of contradiction among the anti-interference performance, the anti-noise capability and the stability margin in the prior art is solved.

The application provides a control method and a control system of a chopper converter, the chopper converter comprising a Buck converter and a Boost converter connected in series, the control method comprises the following steps: sampling an output voltage value and an output current value of the Buck converter, performing closed-loop adjustment based on the collected output voltage value and the output current value, outputting a control duty ratio of the Buck converter, and calculating a control duty ratio of the Boost converter based on the control duty ratio of the Buck converter, so as to control the output of the chopper converter; the application has the beneficial effects that the traditional four-order control system is changed into a two-order control system, the difficulty of control parameter adjustment is reduced, the calculation and configuration of the control margin are improved, the system response speed is improved, and the front-stage Boost converter and the rear-stage Buck converter are synchronously controlled in a closed loop, so that the output ripple and the EMI influence are effectively reduced.

The invention discloses a feasibility-enhanced robust safety critical control method. The method fully considers the influence of the non-matching disturbance on the system safety when the relative orders of the input and the disturbance are inconsistent. Unknown disturbance is estimated through a robust integral type nonlinear disturbance observer based on error symbol integration, and an estimation result is applied to a high-order control barrier function, so that the high-order safety of the system is ensured. Furthermore, according to the method, unknown terms in high-order control barrier function constraints are replaced by estimating disturbance and the lower bound of errors of the disturbance, and the unknown terms are embedded into a quadratic programming controller. For the feasibility problem possibly caused by multi-input and multi-obstacle function constraints, the method introduces a volume control obstacle function to quantify the feasible region volume, and further combines a disturbance observer with the volume obstacle function to ensure that the feasible region volume is always positive, thereby improving the feasibility of a controller when disturbance exists. By integrating the method, the unification of the system security and the multi-constraint compatibility is realized.

The present invention provides an order processing method and system, including: obtaining a charging order issued by an electric vehicle owner, determining the remaining power information and charging demand information of the corresponding electric vehicle, configuring a corresponding charging priority for the electric vehicle, establishing order information corresponding to the electric vehicle, transmitting the order information to a mobile charging vehicle management platform, allocating a corresponding mobile charging vehicle to the order information according to the work preference corresponding to each charging vehicle, determining a priority charging time period corresponding to the electric vehicle according to the order information, controlling the corresponding mobile charging vehicle to charge the electric vehicle within the priority charging time period, and controlling the mobile charging vehicle with charging conditions to charge the electric vehicle within the time period specified by the owner or the time period preferred by the owner according to the order issued by the owner, thereby realizing an automated charging and power-off process, improving charging efficiency, and improving the owner's experience.

The invention relates to a computer-supported production method (10) for producing a workpiece (12, 12a, 12b) from a workpiece blank (14, 14a, 14b) according to a production plan (16, 16a, 16b) using a machine tool (18), in particular a flat-bed machine tool, comprising a machining device (20). The method comprises the following steps: a) producing (22) at least one workpiece (12, 12a, 12b) using a machine tool (18); b) identifying (24) a defective workpiece (26); c) reading (28) manufacturing information relating to the identified defective workpiece (26) by means of the order control device (30); d) ascertaining (32) a workpiece blank (34) suitable for the complementary production of the defective workpiece (26) in the planned production process (36) on the basis of the production information read by means of the order control device (30); and e) arranging (38) the workpiece (40) to be complementarily manufactured on the suitable workpiece blank (34) by means of the order control device (30). The invention also relates to a manufacturing system (42) comprising a processing device (20) and an order control device (30) for carrying out the manufacturing method (10).

The invention discloses an automatic express delivery control method and an automatic logistics cabinet loading control method and system.The automatic express delivery control method comprises the steps that express delivery is controlled to be correspondingly loaded into logistics cabinets at sorting line grids, and one face or multiple faces of each logistics cabinet are provided with multi-bit integrated codes; after each logistics cabinet completing the express loading task is stored in a specified storage area, a transport capacity request order is generated according to the address code and information in the multi-bit-one code; the mobile carriers responding to the transport capacity request orders are controlled to run to the corresponding boxing waiting areas, and the logistics cabinets are controlled to be loaded to the corresponding mobile carriers; and planning a driving path of the unmanned vehicle according to a first-level address in the address code of each logistics cabinet so as to distribute each logistics cabinet to a target post, and decrypting a second-level address in the address code after the logistics cabinet arrives at the target post so as to obtain a specific address of a recipient. The method has the advantages of simplicity in operation, low implementation cost, high execution efficiency, high intelligent degree and the like.

The invention relates to the technical field of information processing, and particularly discloses an order sorting control system for an unmanned intelligent kitchen, and the system comprises an automatic order receiving module which is used for obtaining order information of different channels, and carrying out the integration of all order information, and obtaining an integrated order list; the order analysis module is used for obtaining multiple pieces of dish cooking information according to the integrated order list, merging the same dish names in the dish cooking information to obtain dish cooking merging information, and obtaining dish arrangement cooking information according to the dish cooking merging information; and an order ordering module. According to the invention, multi-channel orders are integrated through the automatic order receiving module, information dispersion and chaos are avoided, a foundation is laid for subsequent processes, and the convenience and efficiency of order management are improved.