580 results about "Model control" patented technology

A method and apparatus for reducing the workload of titrating drug to effect while leaving clinician users in control of a related procedure is described. A drug delivery device is controlled to achieve a target drug concentration at a selected site in the patient or a predetermined infusion rate waveform. The time profile of the target drug concentration or a predetermined infusion rate waveform is controlled by a drug state model that uses clinical heuristics to implement safe, pre-defined changes in the target drug concentration or infusion rate and user-commanded changes in target drug concentration or infusion rate. The invention allows time to assess the response of the patient to changes in drug level by making small incremental and conservative changes in drug level over time.

A system and process for controlling the coding bit rate of streaming media data is presented. This coding bit rate control involves dynamically adjusting the coding bit rate to control client buffer duration to prevent the buffer from underflowing, while keeping the average coding bit rate close to the average transmission bit rate of the network (an thus maximizing the quality of the data playback). Using the theory of optimal linear quadratic control, the client buffer duration is kept as close as possible to a target level while still keeping the coding bit rate (and hence the quality) as constant as possible. In addition, a leaky bucket model is incorporated into the control loop so that the changes in buffer duration due to natural variation in the instantaneous coding bit rate are not mistaken for changes in buffer duration due to network congestion.

Presently described is a decompilation method of operation and system for parsing executable code, identifying and recursively modeling data flows, identifying and recursively modeling control flow, and iteratively refining these models to provide a complete model at the nanocode level. The nanocode decompiler may be used to determine if flaws, security vulnerabilities, or general quality issues exist in the code. The nanocode decompiler outputs in a standardized, human-readable intermediate representation (IR) designed for automated or scripted analysis and reporting. Reports may take the form of a computer annotated and / or partially human annotated nanocode listing in the above-described IR. Annotations may include plain English statements regarding flaws and pointers to badly constructed data structures, unchecked buffers, malicious embedded code or “trap doors,” and the like. Annotations may be generated through a scripted analysis process or by means of an expert-enhanced, quasi-autonomous system.

Provided is an apparatus and method for immediately creating and controlling a virtual reality interactive human body model for a user-centric interface. The apparatus and method can transform a whole body three-dimensional (3D) default model into a model close to the body of a user by collecting data from the user's hands, generates a user coincident 3D model by selecting a skin texture map and applying it to the transformed model, and controlling the user coincident 3D model in a deformable polygon mesh structure to naturally visualize the motion of the user coincident 3D model. The apparatus and method can make users participate in a virtual reality system conveniently and work naturally in the same manner as reality, i.e., interaction. The apparatus and method provides ordinary users with an easy access to virtual reality systems and overcomes the shortcomings of existing virtual reality systems which simply provide visual effects.

The invention discloses a three-dimensional multi-missile cooperative guidance method with finite time convergence. The method comprises the steps that for an unknown target, a multi-missile cooperative guidance model with attacking angle constraint in three-dimensional space is established; by adaptive control, integral sliding model control and a finite time consistency protocol, an acceleration guidance law in the sight direction is established to make all missiles hit the target at the same time; through the adaptive control and non-singular fast terminal sliding model control, and the acceleration guidance law in the sight direction is designed to make the finite time convergence of a sight angular velocity rate and a sight angle of each missile achieved. According to the three-dimensional multi-missile cooperative guidance method with the finite time convergence, all the missiles can hit the target at a desired angle at the same time on condition that no maneuvering information of the target is known, and at the same time the occurrence of buffeting is avoided.

An apparatus for recognizing a fingerprint includes a fingerprint sensing unit for scanning a fingerprint of a user; a storage using for storing a comparison model of the fingerprint of the user and various threshold values; a control unit for obtaining similarity between the fingerprint of the user scanned by fingerprint sensing unit and the comparison model stored in the storage unit, comparing it with a certain threshold value, and controlling a mobile terminal according to the comparison result; and a display unit for transferring a result (success or failure) of the fingerprint recognition or a request from the control unit to the user.

A Computer-Telephony Integration (CTI) system is used to control an Automatic Call Distribution (ACD) system, and non-ACD phone functions, where all functions can be performed at either the phone or the computer display by creating a Bidirectional CTI Model (BCM) in software. The ACD system is used in call centers to route incoming calls to call takers according to attributes such as dispatcher skill-sets or time since last call received. The ACD system is also able to send a call to a dispatcher without ringing, using an auto-answer system. The CTI system allows telephone functions such as originating calls, answering calls, and hold, transfer, and conference features to be controlled by a computer workstation.

A universal Automatic Train Protection ATP vehicle mounted system and mode control method. The invention mainly uses digital signal processing and safe redundant control technology, designs a safe Protection Automatic control system which can receive many varieties of ground vehicles information transmission modus, realize the combination of the train speed steps control and the first-order speed-distance model curve and realize the generalization of vehicle automatic protection system vehicle mounted equipments. And the ground vehicles information transmission modus consists of analog and digital track circuit, responder, GSM-R transmission, 2.4GHz wireless transmission, etc. the safe protect control is the safe braking model control using the combination of speed steps and first-order speed-distance model curve. The system mainly consists of power module, ground vehicles information transmission reception module, central processing module, recording module and man-machine interface MMI module, etc. The beneficial result is getting a solving program for users on the base of reducing construction costs and intercommunicating transport operation.

A robust method of creating process models for use in controller generation, such as in MPC controller generation, adds noise to the process data collected and used in the model generation process. In particular, a robust method of creating a parametric process model first collects process outputs based on known test input signals or sequences, adds random noise to the collected process data and then uses a standard or known technique to determine a process model from the collected process data. Unlike existing techniques for noise removal that focus on clean up of non-random noise prior to generating a process model, the addition of random, zero-mean noise to the process data enables, in many cases, the generation of an acceptable parametric process model in situations where no process model parameter convergence was otherwise obtained. Additionally, process models created using this technique generally have wider confidence intervals, therefore providing a model that works adequately in many process situations without needing to manually or graphically change the model.

A controller for directing operation of an air pollution control system performing a process to control emissions of a pollutant has multiple process parameters (MPPs). One or more of the MPPs is a controllable process parameter (CTPP) and one of the MPPs is an amount of the pollutant (AOP) emitted by the system. A defined AOP value (AOPV) represents an objective or limit on an actual value (AV) of the emitted AOP. The controller includes either a neural network process model or a non-neural network process model representing a relationship between each CTPP and the emitted AOP. A control processor has the logic to predict, based on the model, how changes to the current value of each CTPP will affect a future AV of emitted AOP, to select one of the changes in one CTPP based on the predicted affect of that change and on the AOPV, and to direct control of the one CTPP in accordance with the selected change for that CTPP.

A method controls an operation of a spacecraft according to a model of the spacecraft. The method determines control inputs for controlling concurrently thrusters of the spacecraft and momentum exchange devices of the spacecraft using an optimization of a cost function over a receding horizon subject to constraints on a pose of the spacecraft and constraints on inputs to the thrusters. The cost function includes components for controlling the pose of the spacecraft and a momentum stored by the momentum exchange devices. The method generates a command to control concurrently the thrusters and the momentum exchange devices according to at least a portion of the control inputs.

The invention relates to an adaptive nonsingular terminal sliding model control method for permanent magnet synchronous motors on the basis of disturbance observers. An adaptive nonsingular terminal sliding model controller is introduced into speed loops of vector control systems for the permanent magnet synchronous motors. The adaptive nonsingular terminal sliding model control method is characterized in that an adaptive variable-speed exponential approach law is proposed, first-order norms of state variables are introduced into the approach law, index approach speeds and constant approach speeds are adaptively adjusted according to the distances from the state variables to balance points, accordingly, the approach time can be shortened, and system buffeting can be weakened; the disturbance observers are designed for solving the problems of external disturbance of existing systems and load perturbation, and observation values are fed into designs of the sliding mode controllers. Rotational speeds can be quickly tracked when the systems are disturbed or load fluctuates, accordingly, overshoot and steady-state static difference of the systems can be reduced, and the robustness of the systems can be greatly enhanced.

A vehicle crash safety system includes a pre-crash sensing system generating an object threat assessment and vehicle dynamics data, an occupant sensing system generating occupant characteristic data, and an Occupant Safety Reference Model (OSRM) controller for generating a reference safety restraint deployment profile as a function of the object threat assessment, vehicle dynamics data and occupant characteristic data. An active restraint adaptation (ARA) controller in operative communication with the OSRM controller and a decentralized restraint controller. The ARA controller sends restraint deployment targets, and the safety restraint deployment profile to the decentralized restraint controller. The ARA controller may modify input signals to the decentralized controller based on the real-time occupant position trajectory. The decentralized restraint controller is adapted to operate the restraint system as a function of signals from the ARA controller and real-time occupant-restraint system interactions.

Managing data mining activities in a data mining environment, including selecting a model scoring results table, wherein the selecting is carried out in dependence upon metadata included in a model scoring results control table, the model scoring results control table being related to a data set control table including data set metadata; reading a scoring output data record from the selected model scoring results table; storing the scoring output data record in a managed representation table for scoring results; selecting a model training results file, wherein the selecting is carried out in dependence upon metadata included in a mining model control table; reading training results data from the selected model training results file; and storing the training results data in a model training results table, the model training results table comprising a relational representation of the training results data from the selected model training results file.

A robust method of creating process models for use in controller generation, such as in MPC controller generation, adds noise to the process data collected and used in the model generation process. In particular, a robust method of creating a parametric process model first collects process outputs based on known test input signals or sequences, adds random noise to the collected process data and then uses a standard or known technique to determine a process model from the collected process data. Unlike existing techniques for noise removal that focus on clean up of non-random noise prior to generating a process model, the addition of random, zero-mean noise to the process data enables, in many cases, the generation of an acceptable parametric process model in situations where no process model parameter convergence was otherwise obtained. Additionally, process models created using this technique generally have wider confidence intervals, therefore providing a model that works adequately in many process situations without needing to manually or graphically change the model.

The invention provides an upper limb rehabilitation system and method based on a myoelectric signal and a virtual reality interaction technology. The system comprises a myoelectric signal acquiring and processing part, a virtual reality man-machine interaction part and a muscle function evaluation part, wherein the myoelectric signal acquiring and processing part is composed of a data acquiring module, a signal processing module and a model control module; the virtual reality man-machine interaction part is composed of an upper computer virtual environment module and a force feedback device module; the muscle function evaluation part is composed of a muscular tension quantitative evaluation module and a muscle cooperativeness quantitative evaluation module. According to the rehabilitation method, myoelectric control is used so that a patient subjective intention can be reflected better; a patient keeps initiative in a rehabilitation process by using a virtual reality technology, and the portability, the safety and the effectiveness of rehabilitation trainings are improved. According to the upper limb rehabilitation system and method, an existing clinical rehabilitation evaluation manner can be combined and a muscle function state of the patient is objectively evaluated, so that rehabilitation training standards are provided for the patient and evidences for formulating a therapeutic scheme are provided for rehabilitation doctors.

Commands regarding printing of a plurality of types are stored in a non-volatile memory of a digital still camera and in a non-volatile memory of a printer. Print processing is executed by a command-based model with regard to types of printing for which commands are held in common by the digital still camera and printer. With regard to print processing for which the digital still camera does not possess the command, the digital still camera is made to function as a client and the printer as a server, whereby the print processing is executed by a user-interface export model.

The invention relates to a heat supply energy saving control method and system based on neural network prediction. The heat supply energy saving control method comprises the following steps that (S1) a neural network prediction model is built; and (S2) a heat supply system control unit is controlled through the neural network prediction model to enable a building to reach an anticipant room temperature at set time. Through a remote communication unit and a task control unit, users can set the temperature demands of the building locally or through remote equipment, that is, the indoor temperature reaches the set temperature at the appointed time. The control method and system, provided by the invention, can predict optimal advance starting time of a heat supply system according to the operation history data of the heat supply system and the hot water flow, the hot water temperature, the indoor temperature and the outdoor temperature at the present time, finishes the starting of the heat supply system through a heat supply system control unit to realize reduction of the energy consumption under the precondition of satisfying the heat supply demands, and is excellent in economic benefit and social benefit.

A hybrid cascade Model-Based Predictive control (MBPC) and conventional control system for thermal processing equipment of semiconductor substrates, and more in particular for vertical thermal reactors is described. In one embodiment, the conventional control system is based on a PID controller. In one embodiment, the MBPC algorithm is based on both multiple linear dynamic mathematical models and non-linear static mathematical models, which are derived from the closed-loop modeling control data by using the closed-loop identification method. In order to achieve effective dynamic linear models, the desired temperature control range is divided into several temperature sub-ranges. For each temperature sub-range, and for each heating zone, a corresponding dynamic model is identified. During temperature ramp up / down, the control system is provided with a fuzzy control logic and inference engine that switches the dynamic models automatically according to the actual temperature. When a thermocouple (TC) temperature measurement is in failure, a software soft sensor based on dynamic model computing is used to replace the real TC sampling in its place as a control system input. Consequently, when a TC failure occurs during a process, the process can be completed without the loss of the semiconductor substrate(s) being processed.

Presently described is a decompilation method of operation and system for parsing executable code, identifying and recursively modeling data flows, identifying and recursively modeling control flow, and iteratively refining these models to provide a complete model at the nanocode level. The nanocode decompiler may be used to determine if flaws, security vulnerabilities, or general quality issues exist in the code. The nanocode decompiler outputs in a standardized, human-readable intermediate representation (IR) designed for automated or scripted analysis and reporting. Reports may take the form of a computer annotated and / or partially human annotated nanocode listing in the above-described IR. Annotations may include plain English statements regarding flaws and pointers to badly constructed data structures, unchecked buffers, malicious embedded code or “trap doors,” and the like. Annotations may be generated through a scripted analysis process or by means of an expert-enhanced, quasi-autonomous system.

The invention provides a combination automatic control method with a single-joint manipulator under mixed suspension microgravity environments. The combination automatic control method comprises the following steps of 1, enabling a combination to be equivalent to an underwater robot, and establishing a kinematics equation and a dynamics equation; 2, approximating the dynamics equation of the combination by a radial basis function neural network, so as to obtain control force and control torque corresponding to the radial basis function neural network; 3, using a sliding mode control method, so as to obtain control force and control torque corresponding to sliding model control; 4, synthesizing the control force and control torque corresponding to the neural network and the control force and control torque obtained by the sliding model control method, and distributing thrust, so as to obtain a general vector which consists of thrust and joint torque of each propeller; approximating the thrust deviation of the corresponding thruster through the radial basis function neural network, so as to obtain the estimation value of the thrust deviation; 5, combining the results obtained in step 2, step 3 and step 4, obtaining the general vector consisting of the thrust and the joint torque of the corresponding propeller, and further obtaining the thrust and the joint torque of the corresponding propeller, so as to realize the automatic control.

Managing data mining activities in a data mining environment, including selecting a model scoring results table, wherein the selecting is carried out in dependence upon metadata included in a model scoring results control table, the model scoring results control table being related to a data set control table including data set metadata; reading a scoring output data record from the selected model scoring results table; storing the scoring output data record in a managed representation table for scoring results; selecting a model training results file, wherein the selecting is carried out in dependence upon metadata included in a mining model control table; reading training results data from the selected model training results file; and storing the training results data in a model training results table, the model training results table comprising a relational representation of the training results data from the selected model training results file.

The invention relates to a vehicle yaw stability predicting model control method and belongs to the technical field of a vehicle control. The disturbance-observer-based vehicle yaw stability predicting model control method uses a model predicting control method to design a linear model predicting controller, considers constraint conditions and can reduce computation time, track an expected value as much as possible and keep vehicle stability. The method includes: designing a reference model; performing linearization on a vehicle two-freedom-degree nonlinear model to obtain a linear model withmodel error disturbance terms; designing error terms in a disturbance observer pair model according to the linear model; using a model predicting control algorithm to build a target function, and solving an optimal problem corresponding to a cost function to obtain control input acting to a system to allow the vehicle system to track the expected value as much as possible so as to guaranteed vehicle stability. By the method, model complexity can be lowered effectively, control precision requirements are satisfied, and the constraint of driving torque is considered.

The invention relates to a method and a system for centralized management of an electric saver of a central air-conditioner; a water flow pressure difference sensor between a water supply main pipe and a return water main pipe of a central air-conditioner freezing water system, a flow meter for a two-way freezing water return pipe, a water temperature sensor for a back-way freezing water return pipe of a freezing water pump, the water temperature sensor for a freezing water outlet pipe of an air conditioning mainframe, the water temperature sensor for a cooling water outlet pipe of the air conditioning mainframe and the water temperature sensor for a cooling water inlet main pipe of the air conditioning mainframe respectively collect pressure difference, flow speed and water temperature of the corresponding position; collection values are transferred into a fuzzy controller, the fuzzy controller gains dynamic flow and speed parameters through the control of a fuzzy prediction model and an optimal algorithm model, the dynamic flow and speed parameters are transferred into each electric saver, and the speed and the flow of corresponding fans and water pumps are controlled through the frequency change of the electric saver. The invention has the advantages of the high temperature-adjusting precision, the good dynamic performance, the small mechanical loss, the fully-automatic remote monitoring, the closed-loop control of temperature, the soft starting and stopping of a motor and the optimum system electricity-saving rate.

A dynamics-based motion generation apparatus includes: a dynamics model conversion unit for automatically converting character model data into dynamics model data of a character to be subjected to a dynamics simulation; a dynamics model control unit for modifying the dynamics model data and adding or modifying an environment model; a dynamics motion conversion unit for automatically converting reference motion data of the character, which has been created by using the character model data, into dynamics motion data through the dynamics simulation by referring to the dynamics model data and the environment model; and a motion editing unit for editing the reference motion data to decrease a gap between reference motion data and dynamics motion data. The apparatus further includes a robot motion control unit for controlling a robot by inputting preset torque values to related joint motors of the robot by referring to the dynamics motion data.

The invention discloses a permanent magnet synchronous motor (PMSM) quasi dead-beat model prediction flux linkage control method comprising steps of: computing a stator flux linkage vector reference value at a next moment within a limited control framework, and obtaining a target voltage vector according to the reference value and a dead-model control idea; determining the sector of the target voltage vector in virtue of the position angle of the target voltage vector and selecting three valid voltage vectors by using the sector; predicting the stator flux linkage vector at the next moment according to the three valid voltage vectors; and obtaining the optimum on-off state of an inverter by optimizing a value function, wherein the inverter outputs voltage to a PMSM according to the optimum on-off state. The value function does not include weight calculation. When the value function is optimized, only the three valid voltage vectors are optimized so that algorithm operation time is shortened.

A remote control toy system includes a plurality of sets. Each set includes a controller, and a model controlled based on data transmitted from the controller so as to correspond to an operation of a user. An accessory device is provided as a device independent from the controllers and models. The accessory device can conduct data communication with the controllers and models. Each of the controllers, the models, and the accessory device includes a radio communication module serving as a device for executing the data communication and can conduct bilateral data communication based on the Bluetooth standards, and a control device for implementing various controls based on data communication conducted through the radio communication module.

A system which operates a digitally controlled model railroad transmitting a first command from a first client program to a resident external controlling interface through a first communications transport. A second command is transmitted from a second client program to the resident external controlling interface through a second communications transport. The first command and the second command are received by the resident external controlling interface which queues the first and second commands. The resident external controlling interface sends third and fourth commands representative of the first and second commands, respectively, to a digital command station for execution on the digitally controlled model railroad.

The invention discloses a dissolved oxygen model prediction control method based on a self-organization radial basis function neural network, not only belongs to the field of control, but also belongs to the field of water treatment. Aiming to the characteristics of high nonlinearity, strong coupling, time varying, large lag, serious uncertainty and the like in a sewage disposal process, the control method improves the disposal capability of the neural network by automatically adjusting a neural network structure, builds a prediction model of the sewage disposal process, carries out control through a prediction model control method, and therefore improves a control effect, and enables dissolved oxygen to achieve expected requirements fast and accurately. The method solves the problem that current methods based on a switch control and a proportion integration differentiation (PID) control are poor in adaptive ability. Experimental results show that the method can control dissolved oxygen concentration fast and accurately, has strong adaptive ability, improves the quality and the efficiency of sewage disposal process, reduces sewage disposal cost, and promotes a sewage treatment plant to run efficiently and stably.