1520 results about "Control models" patented technology

Controlled devices according to a device control model maintain a state table representative of their operational state. Devices providing a user control point interface for the controlled device obtain the state table of the controlled device, and may also obtain presentation data defining a remoted user interface of the controlled device and device control protocol data defining commands and data messaging protocol to effect control of the controlled device. These user control devices also subscribe to notifications of state table changes, which are distributed from the controlled device according to an eventing model. Accordingly, upon any change to the controlled device's operational state, the eventing model synchronizes the device's state as represented in the state table across all user control devices.

The invention relates to a micro-interface enhanced reactor bubble scale structure-activity regulation and control model building method. The diameter dmax of the largest bubble of a micro-interface enhanced reactor and the diameter dmin of the smallest bubble of the micro-interface enhanced reactor serve as independent variables, the average diameter d32 of the bubble Sauter serve as a dependentvariable, and a numerical relationship is built; based on the Kolmogorov-Hinze theory, the relationship between the diameter dmax of the largest bubble of the micro-interface enhanced reactor, the diameter dmin of the smallest bubble and the parameters of the reactor is built. According to the method, the reactor bubble scale is associated with the structural parameter, the operation parameter andthe physical property parameter of the reactor by using specific numerical relationship, the numerical relationship has the guiding significance for the design of the reactor and can be applied to avariety of reactors, the versatility is good, by means of a bubble scale regulation and control model built through the method, by adjusting the structural parameter and the operation parameter of thereactor, and the maximization of energy efficiency and material efficiency in the reaction process can be achieved, or under the condition that reaction targets, energy consumption and material consumption are given, a high-efficiency reactor structure is designed.

A cluster recovery and maintenance system, method and computer program product for use in a server cluster having plural nodes implementing a server tier in a client-server computing architecture. A first group of N active nodes each run a software stack comprising a cluster management tier and a cluster application tier that actively provides services on behalf of one or more client applications running in a client application tier on the clients. A second group of M spare nodes each run a software stack comprising a cluster management tier and a cluster application tier that does not actively provide services on behalf of client applications. First and second zones in the cluster are determined in response to an active node membership change involving one or more active nodes departing from or being added to the first group as a result of an active node failing or becoming unreachable or as a result of a maintenance operation involving an active node. The first zone is a fault tolerant zone comprising all active nodes that remain operational. The second zone is a fault containment zone comprising all active nodes participating in the membership change and at least a corresponding number of spare nodes to the extent that the membership change involves a node departure. During recovery and maintenance, fast recovery/maintenance and high application availability are implemented in the fault containment zone, while continuous application availability is maintained in the fault tolerant zone.

A processor integrating and controlling at least two A/V devices by constructing a control model, referred to as a filter graph, of the at least two A/V devices as a function of a physical connection topology of the at least two A/V devices and a desired content to be rendered by one of the at least two A/V devices. The filter graph may be constructed as a function of at least two device filters corresponding to the at least two A/V devices, in which the device filters include certain characteristics of the at least two A/V device. These characteristics may include the input or output pins for each device, the media type that the A/V device may process, the type of functions that the device may serve, etc. The desired content may be received as a user input which is entered via a keyboard, mouse or other comparable input devices. In addition, the user input may be entered as a voice command, which may be parsed by the processor using conventional speech recognition algorithms or natural language processing to extract the necessary information. Once the filter graph is constructed, the processor may control the at least two A/V devices via the filter graph by invoking predetermined operations on the filter graph resulting in the appropriate commands being sent to the at least two A/V devices, thereby results in the rendering of the desired content.

A method and system for selecting an optimal set of management and risk controls for a given set of risks within a variable control budget. Specifically, optimization according to the present invention is defined using a method and system to calculate the greatest reduction in an organization's risk exposure with the minimum investment in cost and time as measured by the economic value added of the risk system change. Risk control models and management risk control models are client customized into a risk control system specifically addressing a clients applicable risks and their associated exposures. An operator is able to determine which risk control system maximizes available resources while also reducing an organization's total risk exposure.

A method of creating and using an adaptive DMC type or other MPC controller includes using a model switching technique to periodically determine a process model, such as a parameterized process model, for a process loop on-line during operation of the process. The method then uses the process model to generate an MPC control model and creates and downloads an MPC controller algorithm to an MPC controller based on the new control model while the MPC controller is operating on-line. This technique, which is generally applicable to single-loop MPC controllers and is particularly useful in MPC controllers with a control horizon of one or two, enables an MPC controller to be adapted during the normal operation of the process, so as to change the process model on which the MPC controller is based to thereby account for process changes. The adaptive MPC controller is not computationally expensive and can therefore be easily implemented within a distributed controller of a process control system, while providing the same or in some cases better control than a PID controller, especially in dead time dominant process loops, and in process loops that are subject to process model mismatch within the process time to steady state.

The invention discloses a machine-learning-based air conditioner control method and device as well as an air conditioner. The air conditioner control method comprises the steps that operation parameters and set time, set by a user, of the air conditioner are acquired; when the user sets the operation parameters of the air conditioner, environment parameters corresponding to the set time is obtained; the operation parameters, recorded repeatedly, of the air conditioner are used as the output, the corresponding environment parameters are used as the input, and training is carried out on a neuralnetwork control model so as to obtain a trained neural network control model; and control is carried out on the air conditioner according to the trained neural network control model. According to themachine-learning-based air conditioner control method, self learning of behaviors of controlling the air conditioner by the user can be achieved, and intelligentization of air conditioner control isimproved; when the air conditioner is started, the user does not need to input a control parameter, and the air conditioner can be started through one key, so that complex operation is avoided; and full automatic control of the air conditioner is even realized.

The invention discloses an air conditioner control method, which comprises the following steps that the indoor temperature is detected; a difference value between the indoor temperature and the temperature set by a user is calculated according to the indoor temperature and the temperature set by the user; the initial operation frequency increment of an air conditioner compressor is calculated according to the difference value and a fuzzy control rule, and the initial operation frequency is calculated according to the initial operation frequency increment for controlling the compressor to operate at the initial operation frequency; the operation time of the compressor is detected; when the operation time is greater than the preset time, and if the absolute value of the difference value is smaller than or equal to a preset threshold value, the operation frequency modification value is calculated according to the difference value and a PID (proportion integration differentiation) control model, and in addition, the operation frequency modification value is overlapped onto the initial operation frequency for controlling the compressor to operate at the modified operation frequency. Therefore the operation frequency of the compressor can realize fast response to the load change, the fast refrigeration and heating can be realized, meanwhile, the temperature can be precisely controlled, and the energy sources can be effectively saved. The invention also discloses an air conditioner control device.

The invention discloses a regional path tracking control method for an autonomous land vehicle. A problem that collision of a vehicle with a road boundary or surround obstacle occurs because shapes and sizes of the vehicle and the road are not considered by the existing tracking control method can be solved. The method comprises the following steps: establishing a two-dimensional road model; establishing a mathematical model associated with a vehicle path tracking problem; calculating a roadable region boundary line within a certain distance in front of the vehicle; establishing a vehicle system model; carrying out a design of a regional path tracking control model and selecting a controlled quantity being an optimum front wheel steering angle at current time; according to the optimum front wheel steering angle, controlling a steering execution mechanism to make motion to enable the controlled vehicle to be driven in a roadable region, provided by a vehicle sensing system, within a certain distance in front of the vehicle. When the two-dimensional road model is established, the shapes and sizes of the vehicle and roads are taken into consideration, thereby reducing the possibility of collision of the vechile with the road boundary and thus improving safety of the autonomous land vehicle.

The invention discloses a V2X Internet of Vehicles (IoV) on-loop simulation system, and belongs to the field of IoV. The system is mainly composed of an IPG carmaker IoV simulation platform (01), a Simulink environment module (02), a channel simulator (03), a V2X communication terminal (04) and a V2X road side device (05), wherein the IPG carmaker simulation tool is responsible for building a simulation scene and configuring simulating parameters, the Simulink environment module is responsible for building a channel model, a simulation scene and real scene mapping model, a control model and acommunication model, the channel simulator is used for conducting performance test on LTE-V, 802. 11p communication protocol, the V2X communication terminal is connected with the Simulink communication model to obtain the scene information and realize on-loop simulation, and the V2X road side device imports the obtained information of the real scene into a simulation scene to achieve an outdoor test function. All the modules supplement each other to form a perfect on-loop simulation system and provide a good testing and verifying platform for the IoV application.

The invention discloses an optimal control method for intersection group traffic flow, which resolves the defect that the smallest unit of current urban traffic control is a single intersection, which cannot satisfy the needs of actual traffic control, can realize the optimization of local traffic flow, and provides helps for micro control of traffic flow. The steps of the method are:(1) real time acquiring actual traffic flow of ''intersection group'' on roads through a ground induction coil which has been paved in a city; (2) constructing an optimal control model with a smart approach and inferring and optimizing the parameters of a controller according to real-time traffic information;(3) the controller carrying out optimal control for traffic flow according to the control model.

Embodiments relate to a unified management interface and related resources for managing sets of model objects. A modeling client can host modeling logic and an application programming interface (API) to create, access, manipulate, and import/export modeling objects used in modeling applications, such as engineering, medical, financial, and other modeling platforms. The source data accepted into the modeling client can include consumer or business-level applications, whose spreadsheet, database or other content can be extracted and encapsulated in object-oriented format, such as extensible markup language (XML) format. A graphical control application can be used to manage one or more sets of modeling objects from a unified interface, to permit, for instance, the selection and configuration of the connections, activation status, security settings, and/or other attributes of model objects. The management interface can be used to control how the model objects and other resources can exchange outputs, share internal data, and otherwise operate.

The invention discloses an Internet financial risk monitoring system based on knowledge map, which comprises a data source module, a multi-label graph module and an analysis module. The data source module extracts entities according to different data sources, fuses entity knowledge, constructs relationships, integrates all the basic data sources from different business systems, and organizes theminto unambiguous and well-defined entity knowledge and definite relationships among entities according to business logic. The multi-tag graph module constructs a multi-tag knowledge map according to the knowledge acquired from the data source, and maps the social behavior and attributes of the members into the network map to form the behavior attributes association map of the members; The analysismodule analyzes the potential risk factors and characteristics of members in the process of Internet finance by constructing a good knowledge map. The invention changes the existing analysis dimension of the wind control model, thereby optimizing the traditional method that only the analysis dimension is added to improve the model precision.

The invention discloses a realizing method of engine system of political examination and approval working flow, which comprises the following steps: transmitting complex working flow into control model and data flow model of engine system; extracting flow information through engine system to analyze and operate; transplanting the complex examination and approval business into the system; allocating different resources according to different examination and approval businesses; proceeding individual allocation for the resource on the flow model; defining the data limit and individualization of resource difference of the system; butting the business among departments seamlessly under combined examination and approval condition; realizing uniform dispatching and information sharing.

The invention discloses an unmanned aerial vehicle (UAV)-unmanned ground vehicle (UGV) combined formation cooperative control method, comprising the following steps: step 1, establishing nonlinear dynamical models of unmanned vehicles in UAV-UGV combined formation; step 2, processing the nonlinear dynamical models of a UAV and a UGV via equivalent transformation, and taking acceleration as a common control target quantity, obtaining a unified control model taking acceleration as a control input in the combined formation; step 3, establishing a ground-air combined formation structure based on a virtual pilot to obtain a stable control signal for the UAV-UGV combined formation and obtain an error model of the combined formation, wherein the control signal is acceleration obtained in step 2 as a common control target quantity; and step 4, designing a UAV-UGV combined formation controller by adopting a RBF (Radial Basis Function) network algorithm according to the control model, the error model and the acceleration serving as a control signal and a control target quantity at the same time, so that the combined formation is stable and reliable.

A system and method for camera navigation that provides a player with an unobstructed, non-disorienting view of a target is provided. The system includes a memory for storing a camera navigation/control model, a central processing unit for executing the camera navigation/control model to provide unobstructed and non-disorienting target character views, and a graphics processing unit configured to render the unobstructed views of the target in an image for display. In addition, the camera navigation/control model includes an object detection model, line-of-sight restoration models to restore a line-of-sight view of an obstructed target, and a camera navigation path model. In the method, a collision probe is sent on a straight line path between a camera and a target whereby line-of-sight obstructions are detected if the probe intersects with polygonal sides of an object. A line-of-sight restoration method is used to move the camera to provide an unobstructed view of the target.

A rate based model predictive controller for air path control for a diesel engine regulates turbine lift and EGR valve flow rate to specified set points by coordinated control of intake manifold air pressure and EGR valve flow rate. The controller utilizes a rate-based reduced order linear model for model predictive control.

The invention relates to a robot autonomous obstacle avoidance moving control method based on distance vectors. In the moving process of a moving robot in the environment, the distance vectors from the robot to obstacles are measured through a distance measuring sensor and an angle sensor which are carried on the robot, the current position of the robot serves as the original point all the time to set up coordinate systems for unknown environments with multiple nearby obstacles, the distance vectors from the robot to the edges of the obstacles are measured, the steering angles of the collision prevention obstacles are obtained, the distance vector, larger than the radial size of the robot, between the two adjacent obstacles is obtained, the distance vector, at which collision with the two adjacent obstacles can be avoided at the same time, composed of the central points of the distance vectors between the current position to the robot and the two adjacent obstacles is obtained and serves as the moving direction of the robot and the moving path through which the robot can pass through the two obstacles, safety obstacle avoidance can be achieved to the maximum, and the autonomous obstacle avoidance moving from the starting point to the target point is achieved. According to a control model, the practical radial sizes of the moving robot and the environment obstacles are taken into consideration, and the robot autonomous obstacle avoidance moving control method has the practical application significance.

The present teaching relates to method, system, medium, and implementation of human-like vehicle control for an autonomous vehicle. Information related to a target motion to be achieved by the autonomous vehicle is received, wherein the information includes a current vehicle state of the autonomous vehicle. A first vehicle control signal is generated with respect to the target motion and the given vehicle state in accordance with a vehicle kinematic model. A second vehicle control signal is generated in accordance with a human-like vehicle control model, with respect to the target motion, the given vehicle state, and the first vehicle control signal, wherein the second vehicle control signal modifies the first vehicle control signal to achieve human-like vehicle control behavior.

The invention discloses a device and method for thickened oil deposit gas injection huff-puff oil extraction physical simulation experiments. The device comprises an injection system, a model system, an output control system and a data collection and control system, wherein the injection system is connected with the model system so as to inject formation water, crude oil and huff-puff gas into the model system, the outlet end of the model system is connected with the output control system, the output control system is used for controlling the output of oil-gas mixtures of the model system and calculating gas flow and oil production in the outputted oil-gas mixtures, the model system is further connected with the data collection and control system, and the data collection and control system is used for collecting pressure, temperature and huff-puff gas flow data in a model body and monitoring and processing data in real time. The device can be used for truly simulating processes of injecting gas into a stratum, soaking and extracting indoors and monitoring pressure and pressure gradient distribution rules of different positions from the well bottom of a gas injection well to the far end of the stratum in gas injection and extraction simulation processes.

The invention relates to a CPG (Certified Program Generator) feedback control method of biomimetic robot fish movement, comprising the following steps of: providing a CPG feedback control model for receiving feedback signals by using different parts of a high-level control module, a CPG, a motor neuron, and the like; receiving biomimetic robot fish body state information and water environment information by the high-level control module; transmitting a corresponding command by treating the information and making a decision; and selecting a corresponding movement moulding plate to determine a suitable CPG configuration, wherein the suitable CPG configuration is used for controlling the parts of the biomimetic robot fish body to carry out rhythmic movement and non-rhythmic movement. The invention provides a reference for the feedback control theoretical design of the biomimetic robot fish movement and can realize mobile, flexible and independent autokinetic movement.

The invention discloses a control method for ordered charging of an electromobile. The control method comprises the following steps of firstly, establishing a charging load characteristic model of the electromobile by integrating factors of battery characteristics, a charging mode and behaviors and habits of users; secondly, with the goal of minimizing the difference between the peak and the valley of a load, establishing a centralized optimization model according to the minimal variance of load demands at all time intervals and the average load level, enabling the load fluctuation to be minimized, and realizing the stabilization of the load to obtain reference optimized power; thirdly, establishing a distributed optimization model, and optimizing an individual charging scheme according to the reference optimized power obtained by a power grid and a middle manager in the optimizing process of the second step and dynamic electricity price in 24 hours. A cooperative control model is established by adopting a centralized and distributed combined optimized control idea, so that the negative effect of large-scale disordered charging of the electromobile on planning and operation of the power grid is reduced.

The present invention provides haptic sensations for a haptic feedback device and especially for a rotational device such as a knob. Force effects such as a hill force effect and barrier force effect allow easier selection of menu items, menus, values, or other options by the user. Force models are also described to allow greater selection functionality, such as a scrolling list with detents and rate control borders, a jog shuttle, a push-turn model, a double-push model, and a cast control model.

The invention discloses a congestion control method and system based on deep reinforcement learning. The congestion control method includes: firstly, initializing the environment and model parametersof a network; and training a congestion control model by utilizing the collected current window, the throughput, the time delay, the data transmission rate and the like in the network, selecting the congestion control model with the minimum model loss function value and the maximum reward function value according to a training result, and deploying the model into the network to perform congestioncontrol. According to the method, the size of the congestion window is dynamically adjusted according to the current network throughput, round-trip time delay and data packet loss rate, so that the data transmission rate is controlled, the network throughput is improved, the data transmission delay and the data packet loss rate are reduced, the network congestion is reduced, and the aim of optimizing the network performance is fulfilled.

The invention relates to a sheet shape control method for strip rolling. A model self-adapting sheet shape prediction and control method comprises the following steps: a sheet shape decomposition method and a sheet shape control model are given, and the input signals of the sheet shape control model include a rolling force and a crown of incoming material; then a sheet shape model which includes executing mechanism characteristics is obtained according to history sheet shape actual output data, the model is dynamically corrected according to real-time rolling parameters and corresponding actual sheet shape values, a correction model is used for accurately predicting the sheet shape and determining the optimal control quantity, and a feedback path, which removes transmission time-delay of strip steel between a frame and a measuring system, is established, thus carrying out regulation of a feedback controller in real time and ensuring rapid and dynamical sheet shape control. As the sheet shape control model is corrected in real time according to actual data, constantly changing actual conditions of the sheet shape model of a rolling mill are satisfied, thus predicting the sheet shape more accurately to increase the control accuracy of the sheet shape.

The invention discloses a mining operation multi-operation realization method based on virtual reality and augmented reality, and belongs to the technical field of the virtual reality and the augmented reality. The method comprises two patterns including the virtual reality and the augmented reality. Under a virtual reality scene, the selection and the replacement of a material and a material in the virtual reality scene can be realized, scene exploration is realized, the model can be moved and placed at will, a video is embedded, a two-dimensional code is generated, and a trigger realizes natural interaction, voice interaction and the like; under an augmented reality scene, the model can be selected, voice is played, the operation dynamics of the model can be demonstrated, and the rotation stopping, screen capture and function expansion of the model can be controlled; and under two patterns, various interaction ways of voice control, gesture control and keyboard mouse control can be realized. The method is applied to the virtual simulation application scene of the mining operation, can be used for training mine lot mining workers and students of the mining engineering specialty, reducing training capital and improving the skills of workers and provides an advanced and quick meaning for guiding production construction and science and technology studies.

The invention discloses a mobile robot route planning method based on a distance grid map. The mobile robot route planning method includes selecting front grids by a moving window method in the process of moving of a robot, updating the distance grid map, managing the front grids to be updated by an array management method during updating, and updating a control model of the mobile robot by an A*search algorithm in the mobile robot route planning method based on the distance grid map. The mobile robot route planning method based on the distance grid map is of great fundamental significance in high-ranking tasks like generating topological maps and planning a route in the unknown environment.

The invention discloses an improved multi-time scale coordinated control method for independent microgrid containing hybrid energy storage, this method is based on the day-ahead planning decision model, The intra-day rolling optimization model based on model predictive control, the quasi-real-time coordinated control model based on comprehensive criteria and the real-time coordinated control modelare constructed. Firstly, the day-ahead planning decision-making model takes the operation economy as the optimization objective, the operation restriction of distributed generation and the safety and stability of the system as the constraint conditions. Then the controllable unit start-stop plan deviation and load switching plan deviation are introduced into the rolling optimization model as soft constraints, which allow to revise the unit start-stop plan and load switching plan before the day. Secondly, a comprehensive criterion is introduced into the quasi-real-time coordinated control todecide the priority of distributed generation. Finally, in the real-time coordinated control, the hybrid energy storage system adopts the improved first-order low-pass filter algorithm to compensate the second-order unbalanced power adaptively.

The invention discloses a lane change track optimization and visualization achievement method based on vehicle models and vehicle speeds. The method includes the following steps of (1) calling whole vehicle models of the four vehicle models in ADAMS software according to the following steps: (1-1) obtaining a whole vehicle structure parameter, and (1-2) obtaining vehicle dynamic characteristics; (2) analyzing tracking errors of an existing lane change track model and extracting lane change track models suitable for different vehicle models and different vehicle speeds; (3) optimizing lane change tracks on the basis of safety and comfort according to the following steps: (3-1) building a driving control DCD file on the basis of a lane change track constraint condition, and (3-2) creating a driver control model and a double-lane three-dimensional road model, creating a driver, road and vehicle simulation system, and obtaining an optimal lane change track after simulation. According to the method, lane change behaviors of a vehicle can be observed dynamically in real time, an intelligent vehicle lane change system is optimized, comfort of drivers is improved, and road driving safety is guaranteed.

The present teaching relates to method, system, medium, and implementation of lane planning in an autonomous vehicle. Sensor data are received that capture ground images of a road the autonomous vehicle is on. Based on the sensor data, a current lane of the road that autonomous vehicle is currently occupying is detected. Information indicating presence of a passenger in the vehicle is obtained and used to retrieve a personalized lane control model related to the passenger. Lane control for the autonomous vehicle is planned based on the detected current lane and self-aware capability parameters in accordance with the personalized lane control model. The self-aware capability parameters are used to predict operational capability of the autonomous vehicle with respect to a current location of the autonomous vehicle. The personalized lane control model is generated based on recorded human driving data.