914 results about "Dynamic equation" patented technology

A camera array captures plural component images which are combined into a single scene from which “panning” and “zooming” within the scene are performed. In one embodiment, each camera of the array is a fixed digital camera. The images from each camera are warped and blended such that the combined image is seamless with respect to each of the component images. Warping of the digital images is performed via pre-calculated non-dynamic equations that are calculated based on a registration of the camera array. The process of registering each camera in the arrays is performed either manually, by selecting corresponding points or sets of points in two or more images, or automatically, by presenting a source object (laser light source, for example) into a scene being captured by the camera array and registering positions of the source object as it appears in each of the images. The warping equations are calculated based on the registration data and each scene captured by the camera array is warped and combined using the same equations determined therefrom. A scene captured by the camera array is zoomed, or selectively steered to an area of interest. This zooming- or steering, being done in the digital domain is performed nearly instantaneously when compared to cameras with mechanical zoom and steering functions.

A method, system, and computer-readable storage medium for creating and executing containerized applications in cloud computing are disclosed. For example, one method involves identifying a command. Such a command indicates an application to be executed by a compute node. The method also involves generating a job for transmission to the compute node. The job indicates a container. The compute node, upon receipt of the job, is configured to create an environment for such a container, execute the application within the container, and generate results of the execution of the application.

A method and apparatus for dynamically generating a persona is provided. In one embodiment, the method includes receiving an identity policy, determining a required identity information data set based on the policy, requesting a site reputation, receiving the site reputation, determining a set of site reputation parameters, and generating a persona based on the required identity information data set and the site reputation parameters.

Described are computer-based methods and apparatuses, including computer program products, for dynamic deduplication. Data is processed using an algorithm that deduplicates the data based on a first set of parameters. A first moving average of a first deduplication performance metric is calculated for the algorithm over a time period. A second moving average of a second deduplication performance metric is calculated for the algorithm over the time period. It is determined that the first moving average satisfies a first criterion, the second moving average satisfies a second criterion, or both. The algorithm is reconfigured based on a second set of parameters to deduplicate data.

The invention relates to a spacecraft fault tolerance attitude cooperation tracking control method based on a normalized neural network, and belongs to the technical field of spacecraft formation flight. According to the method, an attitude motion model of a single spacecraft is built, errors are defined, a control law is designed for the model, a sliding mode function is designed, the derivative of the sliding mode function is solved, an error model is obtained, a control law based on an input normalized neural network is designed, and the states of the spacecrafts are cooperative and consistent; each spacecraft calculates the required control torque according to attitude information of itself and the adjacent spacecraft, the calculated control torque is acted on the corresponding spacecraft via an execution mechanism of each spacecraft, the angular velocity is solved via an obtained attitude dynamic equation, a unit quaternion attitude tracks an expected attitude via the attitude dynamic equation, and consistent attitude of the spacecraft formation is finally realized. According to the method, estimation errors of non-linear function approximation are reduced, the calculating time is reduced, and the convergence rate and the control precision of the system are increased.

The invention discloses a four-rotor aircraft control method based on PID neural network (PIDNN) control. First, dynamic equations of a four-rotor aircraft are established based on the Newton-Euler equations, and then, a nested controller is proposed. An inner loop decentralized controller is designed based on a PIDNN method to realize attitude control, and the outer loop adopts a classical PID control method. Next, online learning of a PIDNN controller is realized by an error back propagation method, the connection initial weight of PIDNN is determined based on the principle of PID control, and an appropriate learning step is selected according to the discrete Lyapunov theory to guarantee the convergence of the controller. Thus, the control problem of a four-rotor aircraft caused by high degree of nonlinearity, strong coupling and under-actuating capability, disturbance from the external environment in the process of flight and other factors can be effectively solved.

The invention discloses a micro-gyroscope tracking control method based on an adaptive fuzzy sliding mode. The method comprises the following steps of: designing a control law according to the linear feedback technology and a micro-gyroscope dynamic equation; adding the sliding mode control to the control law based on the method to obtain a sliding mode control law; approaching to a practical system with a fuzzy system to obtain a fuzzy sliding mode control law; and determining an adaptive law of parameters based on the method. As the fuzzy approaching error is greater than or equal to the least approaching error, a parameter in the control law is selected as the absolute value of the approaching error plus a constant greater than 0, thus the unconditional stability of the system is ensured, the system response is accelerated and the system buffeting is reduced. Through the invention, the problems that the control accuracy of a traditional micro-gyroscope control system is relatively low due to the influence of environment change as the parameter variation is not considered and the like are solved, the micro-gyroscope can be effectively and reliably controlled in the case of uncertain parameters caused by the manufacturing error or unknown and existing environmental interference, and the overall stability of the system is ensured.

The invention provides a DC-DC buck converter high-order sliding mode control method. The method comprises the steps that firstly, a finite-state machine second-order sliding mode controller is built for a buck converter, a sliding mode variable is defined, a sliding mode surface is built, an effective state and a primary state are set so that the effective state corresponds to output quantity of the controller; secondly, sliding mode quantity is defined by using output quantity of the buck converter and a set value, a sliding mode dynamic equation is built and analyzed, and the convergence condition of the finite-state machine second-order sliding mode controller is obtained under the condition that no output overshoot exists; thirdly, a finite-state machine second-order sliding mode controller with a time-lag value is built according to the finite-state machine second-order sliding mode controller, the sliding mode variable is converged to a balance point under the condition of limited frequency, and namely output of the buck converter tracks the set value without deviation.

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.

The invention discloses a step-by-step teaching robot based on motor power. The step-by-step teaching robot comprises a base and a multi-joint arm connected with the base. The multi-joint arm is in transmission connection with a connecting joint of the base through a join shaft, and all joints of the multi-joint arm itself are all in transmission connection through joint shafts. The step-by-step teaching robot further comprises an encoder for detecting and recording the movement situations of the joint shafts, the joint shafts are connected with a motor, and the encoder is electrically connected with a control system. A power computing system is further arranged. A manipulation sensing mechanism is arranged at the tail end of the multi-joint arm, and the power computing system is electrically connected with the motor and the manipulation sensing mechanism. The invention further discloses a control method of the robot. According to the step-by-step teaching robot based on the motor power and the control method of the robot, the rotation directions of the joint shafts are determined through trigger signals on the manipulation sensing mechanism to enable the motor power torque providing process to be smooth and sensitive. The computing amount in signal processing is small, complex dynamics equations do not need to be solved, and therefore the requirement for the computing capacity of a CPU is greatly lowered. The step-by-step teaching robot based on the motor power and the control method of the step-by-step teaching robot can be used in the fields such as spray coating production lines.

The invention discloses a control method of a hypersonic vehicle orienting the uncertainty condition. The control method comprises the following steps that step S1, full state feedback linearization processing is performed on flight speed V and flight height h according to a hypersonic vehicle longitudinal dynamic equation so as to obtain a corresponding state equation; step S2, an anti-step sliding mode controller is designed according to the state equation, and the double exponential approximation law of the selected sliding mode surface is S<.>=-k<1>|S|<eta>sgn(S)-k<2>|S|<lambda>sgn(S), wherein k<1>>0, K<2>>2, eta>1 and 1>lambda>0 are parameters in the formula; and step S3, a test platform is established based on the anti-step sliding mode controller to perform performance simulation. According to the method, the double exponential sliding mode controller based on the backstepping method is adopted, and switching gain and the problem of buffeting existing in sliding mode control can be effectively reduced by the method.

The present invention discloses a social network based message propagation model, which is a method, based on the special line of the crowd in the network and the average degree of the nodes in the social network, for carrying out modeling analysis on message propagation in the social network and proposing a node importance based rumor immune strategy. The dynamic equations of the <k> SLIR message propagation model are established in the small-world network; by virtue of the method disclosed by the present invention, influences of nodes in various states in the social network, on message propagation can be realistically taken into consideration; and according to the node importance based improved rumor immune strategy proposed by the present invention, propagation of rumors in social network can be better inhibited.

The invention provides an electromagnetic formation satellite attitude and track relative control method. The method comprises the following steps: 1, attitude dynamics equations are built; 2, according to the attitude dynamics equation in a linear form with quaternion representation built in the first step, an attitude dynamics equation in a body coordinate system and a rigid satellite dynamics equation, a satellite attitude control system feedback control law is designed and obtained; and 3, according to the feedback control law obtained in the second step, relative control is carried out on the electromagnetic formation satellite attitude and the track. The method of the invention has the advantages that the attitude dynamics equations, a relative motion dynamics equation and electromagnetic force and electromagnetic torque models are built, the designed satellite attitude control system feedback control law, a flywheel angular momentum magnetic unloading algorithm, a large angle attitude maneuver method, an electromagnetic formation flying satellite motion controller and a magnetic dipole control distribution method can have good working performance, and high-efficiency relative control on the electromagnetic formation satellite attitude and the track can be realized.

The invention belongs to the technical field of the network security, and especially relates to a network active defense policy selection method and device based on Bayesian evolutionary game. The method comprises the following steps: constructing a network attack Bayesian evolutionary game model according to an incomplete information game scene in an actual attack-defense adversarial network; setting a selection strength factor for describing gamer learning capacity, and constructing a random replicate dynamic equation about the attacker-defender policy evolution; combining the random replicate dynamic equations about the attacker-defender policy evolution, solving to acquire a stable balance point of the attacker-defender policy evolution, and determining and outputting an optimal defense policy. From the limited intellectual visual angle of the participant, a replicate dynamic equation about the participant decision process is constructed and solved by means of the replicate dynamicmechanism for describing the biological evolution, the method is suitable for incomplete information network attack-defense adversarial network and more suitable for the actual application, the generality and operability in the network decision implementation process are enhanced, and the effective guidance is provided for selecting the active defense policy.

The invention discloses a half-cycle repetitive controller for a position servo system. Reference signals with half-cycle symmetry are set, a half-cycle feedback link is constructed, and an ideal error dynamic is formed according to a power attraction law; and according to an ideal error dynamic equation, an e/v signal conversion module is constructed, a signal obtained by calculating through the controller is used as control input of a controlled servo object, and the position servo system changes together with the reference signals by completely eliminating half-cycle symmetrical interference signals. By the half-cycle repetitive controller, the internal memory of the controller can be obviously reduced and the periodic interference is quickly and completely suppressed under the half-cycle symmetrical reference signals, and the half-cycle repetitive controller has high cost performance.

A method and an apparatus that provide rewriting code to dynamically mask program data statically embedded in a first code are described. The program data can be used in multiple instructions in the first code. A code location (e.g. an optimal code location) in the first code can be determined for injecting the rewriting code. The code location may be included in two or more execution paths of first code. Each execution path can have at least one of the instructions using the program data. A second code may be generated based on the first code inserted with the rewriting code at the optimal code location. The second code can include instructions using the program data dynamically masked by the rewriting code. When executed by a processor, the first code and the second code can generate identical results.

The invention discloses a collaborative path planning method for a kinematic redundant two-arm space robot. The collaborative path planning method for the kinematic redundant two-arm space robot comprises the following steps that a dynamic equation and a kinematic equation of a space robot system are established; a redundant solution of an inverse kinematics equation of an end-effector is solved,and a system non-holonomic constraint equation is obtained through a momentum conservation equation; a task space constraint equation of the relationship between the end-effector motion and the attitude of a base is obtained through the system non-holonomic constraint equation; the path planning of the end-effector in a task space is obtained by using a quintic bezier curve, and path execution time is determined by the velocity and acceleration boundary of the end-effector; and the joint motion trajectory planning corresponding to different task priorities is obtained through the end-effectormotion equation and the task space constraint equation. The collaborative path planning method of the space two-arm robot is implemented, various tasks can be performed according to the priorities ofthe tasks such as a multi-arm collaborative task and a dynamic balancing task, and the operation ability of a space manipulator is greatly expanded.

The invention discloses a vehicle longitudinal follow control method in expressway heavy truck queue driving. The vehicle longitudinal follow control method comprises the steps that based on a nonlinear model predictive control theory, according to obtained current road information and taking into account constraint of a physical actuator, the situation that vehicles in a queue is controlled to maintain the same speed with adjacent front vehicles and to maintain the desired vehicle distance is taken as the control target, and the control quantity is optimized and calculated and acts on a controlled vehicle; and based on a nonlinear dynamic equation of the vehicle, the state of the adjacent front vehicles at the next moment is predicted and serves as a part of a tracked and controlled target, and the speed deviation between the controlled vehicle and the front vehicles due to vehicle-mounted controller delay, transmission system delay and communication delay is reduced effectively; andtherefore, the vehicle distance can be controlled at a smaller numerical value in the travelling process of the vehicle queue, and the vehicle longitudinal follow control method indirectly improves the overall fuel economy of the vehicle queue according to the relationship between the air resistance and the vehicle distance in the travelling process of the vehicle.

The invention discloses a static and dynamic identification method for a dynamic parameter for a robot, which needs to provide a robot substrate six-axis force as well as the driving torque, the angular velocity and the angular acceleration of each joint. During static identification, a multidimensional matrix is built by the rotation transformation relationship between connecting rod coordinate systems of the robot by changing the configuration of a mechanical arm, a static identification model is built, and the product of the quality of each connecting rod and the coordinate of the centroid is solved with a least square method. According to a static identification result, a mechanical arm dynamics equation of a dynamics parameter decoupling form is deduced on the basis of the Newton-Euler algorithm. In the dynamic identification, each joint is planned to move in a specific combination mode, and the inertia tensor and the coordinate of the centroid from a tail-end connecting rod to a connecting rod 1 are successively identified with a pseudo inverse method so as to the full identification of the dynamic parameter for the robot. The parameter identification result disclosed by the invention comprises the mechanical arm joint characteristics, and therefore, the inertia parameter value in the practical work of the robot can be reflected.

The invention discloses an aircraft attitude fault-tolerant control method based on dynamic control redistribution. The method includes the steps that firstly, an attitude angle rate loop dynamic equation of a near-space aircraft X-33 is given, and a control surface jamming and damage fault model is established; then according to the control surface damage fault model of an attitude angle rate loop, a self-adaptive sliding-mode observer is designed; the attitude angle loop and the designed observer dynamic equation are combined, and an angle loop controller and an angular speed loop controller are designed. Accurate damage fault information, interference information and the like are not needed, the information is implied in the designed self-adaptive sliding-mode observer, the implicit information is fed back to a pseudo control law and online distribution algorithm LMI in real time, and then robust fault-tolerant control is achieved. Finally, the designed method is applied to attitude stability control and tracking control of the near-space aircraft under the control surface fault condition, flight attitude robust fault-tolerant control is achieved, and good control performance and effects are achieved.

The invention relates to a nerve self-adaption fault-tolerant control method for train unknown perturbation. Based on the stress analysis of the longitudinal motion of a train, the longitudinal motion dynamic equation of the train is established. According to an actuator fault and the longitudinal motion dynamic equation of the train, a neural network radial basis function is used to approximate unknown additional resistance. The longitudinal motion dynamic equation of the train in the case of the actuator fault is established, and then a proportional-integral-differential sliding-mode surface is constructed. According to the longitudinal motion dynamic equation of the train in the case of the actuator fault, the closed-loop dynamic equation of train is established through an unknown self-adaption law and a controller. The stability of the system is proved, and then an observer and a controller equation are used to control the actual displacement and velocity of the train to approach expected displacement and velocity. According to the invention, the influence of the actuator fault on the train system can be compensated; the influence of additional resistance on the train system is attenuated or removed; and the train system has a good position and velocity tracking performance.

The invention discloses an attack time and attach angle constrained guidance strategy. The attack time and attach angle constrained guidance strategy comprises the following steps of using a two-dimensional horizontal plane where a missile and a target are located as an attack plane, establishing a missile and target mathematical model and acquiring a missile sight angle second-order dynamic equation; designing the guidance strategy based on a virtual collision point, dividing the guidance process into two stages, designing an attack angle constrained guidance law based on the virtual collision point for the first stage and designing a proportional guidance law for the second stage; designing a switching strategy of the attack angle constrained guidance law and the proportional guidance law based on the virtual collision point; and adjusting the location of the virtual collision point. By means of the guidance strategy based on the virtual collision point, there is no need to conduct linearization and differential equation conversion based on the cross-range on the model and depend on estimation on remaining time information; the attack time and attach angle constrained guidance strategy is applicable to target moving tasks under multiple constraint conditions and has the characteristics that the design method is simple, and the applicability is high.

The invention discloses a method for optimizing plunge milling machining of a slotting of an integral impeller. The method comprises the steps of establishing a plunge milling dynamics model and a milling model of a large filleted corner milling cutter asymmetry milling; substituting a modal parameter obtained from a modal experiment and a dynamic milling force obtained through a milling force model into a dynamics equation so as to further modify the cutting force; establishing an equivalent cutter bar stability analyzing finite element model, introducing a deformation ratio and a cutter bardanger position radial offset so as to obtain an optimized cutting parameter. According to the method, the problem of selection optimization of cutting parameters in the plunge milling machining of the slotting of integral impellers is solved, so that the interference phenomenon between cutters and work pieces is avoided; and the beneficial effects of small impeller deformation and high cutting efficiency are achieved. The method is also applicable for rough milling machining of slotting of similar parts.