14 results about "Nonlinear motion" patented technology

The application discloses a rotor coupling dynamics calculation method of complex three-dimensional shape layout. A coordinate conversion relationship caused by a front protrusion / after-sweeping / downward-reversing configuration is established; nonlinear elastic deformation of elastic blades waving, oscillating and twisting and nonlinear coupling relationship among them are described; nonlinear motion caused by the complex three-dimensional shape layout is described based on the coordinate conversion relationship and the nonlinear coupling relationship; and the relationship among strain energy, kinetic energy and virtual work of external force of the rotor is established based on the Hamilton principle according to the description of the nonlinear motion, and a finite element method of a 15-degree-of-freedom beam element is used to establish a rotor dynamics equation. The application can effectively reflect the structural coupling characteristics and coupling degree of the waving-torsion direction caused by the front / rear sweep of the blade tip, effectively reflect the structural coupling characteristics and coupling degree of the oscillation-torsion direction caused by the upward / downward reversal of the blade tip, and effectively reflect the rotor dynamics characteristic behaviors caused by the three-dimensional shape of the blade.

This invention relates to an active disturbance rejection control method and system suitable for biomimetic chest cavity motion simulation. The method includes: acquiring and preprocessing a nonlinear motion trajectory signal to generate an original target position command; processing the original target position command using a tracking differentiator to generate a smoothly transitioning desired position signal and desired velocity signal; receiving the actual position feedback signal of the controlled object and the control input of the previous control cycle through an extended state observer, and estimating the actual position state observation value, actual velocity state observation value, and total disturbance state observation value of the controlled object in real time; calculating the position tracking error and velocity tracking error based on the desired position signal, desired velocity signal, and the actual position state observation value and actual velocity state observation value of the controlled object, and calculating the initial state feedback control quantity; generating an actual control command and sending it to the motor driver to drive the biomimetic chest cavity motion simulation platform to reproduce the target respiratory motion trajectory.

The application discloses a kind of matching and mismatched interference under unmanned ship preset time control method and system, comprising the following steps: establishing the nonlinear motion model of unmanned ship under matching and mismatched interference;Design preset time adjustment function, the dynamic evolution process of system error is regulated;Kinematic disturbance observer and dynamics disturbance observer are designed to online estimate matching interference and mismatched interference;According to interference estimation information, construct kinematic controller, filter and dynamics controller, realize the robust preset time tracking control of reference trajectory of unmanned ship.The method proposed in the application can realize the online observation and compensation of multi-source disturbance, ensure that the system tracking error and disturbance observation error converge within the preset time, and the convergence time is adjustable, while having the advantages of continuous smooth control input, strong anti-interference ability and high engineering realizability, which can improve the control performance and reliability of unmanned ship in complex sea conditions and time-sensitive tasks.

The application discloses a preset time control method and system for a wheeled mobile robot under multiple disturbances, and comprises the following steps: establishing a nonlinear motion model of a wheeled mobile robot under matched and unmatched disturbances; designing a preset time adjustment function to regulate and control the dynamic evolution process of system errors; designing a kinematic disturbance observer and a dynamic disturbance observer to online estimate the matched and unmatched disturbances; and constructing a kinematic controller, a filter and a dynamic controller according to the disturbance estimation information, so as to realize robust preset time tracking control of the wheeled mobile robot on a reference trajectory. The method provided by the application can guarantee the convergence of system errors within a preset time without relying on the ideal no-slip assumption, has the advantages of adjustable convergence time, continuous and smooth control input, strong anti-interference ability and high engineering realizability, and improves the anti-interference performance of the robot in a complex dynamic environment and the reliability of a time-sensitive task.

This application discloses a multimodal data collaborative intelligent detection and 3D localization method for maritime vessels, comprising: fine preprocessing of collected multi-source heterogeneous data and preliminary target detection; dynamic weighted fusion of the preprocessed multi-source heterogeneous data, combined with depth data from lidar, to achieve accurate coordinate recovery of the vessel target in 3D space; and prediction and updating of the motion state of the identified target based on a multi-tracking mechanism collaborative strategy. By fully utilizing the rich texture information of visible light images, the anti-interference capability of thermal imaging, and the precise spatial depth data of lidar through multimodal data perception and preliminary processing, heterogeneous data deep fusion and 3D localization, and advanced multi-target continuous tracking and state estimation, this method integrates a multi-tracking mechanism collaborative strategy to predict and update the motion state of the identified target, effectively addressing the problem of tracking interruption caused by nonlinear motion or temporary occlusion of maritime targets.

This invention discloses a high-efficiency and precise time control method for unmanned underwater vehicles (UUVs), comprising the following steps: constructing a six-degree-of-freedom nonlinear motion mathematical model of the UUV; designing a precise time disturbance observer to estimate environmental disturbances online; establishing a dynamic model of the UUV's tracking error; and designing a precise time sliding mode controller. The method proposed in this invention ensures precise time convergence while avoiding excessive initial control input from the controller, significantly reducing system control energy consumption and ultimately achieving high-efficiency and precise time tracking control for the UUV.

This application discloses an adaptive sliding mode control method, system, device, and medium for a quadrotor UAV. A nonlinear kinematic and dynamic model of the quadrotor UAV is established, and the mass and disturbance forces of the quadrotor UAV are estimated in real time and incorporated into the position adaptive sliding mode controller. A desired pull control law for outer-loop position tracking is calculated, and a desired attitude angle is generated through decoupling. The generalized moment of inertia and disturbance torque of the quadrotor UAV are estimated in real time and incorporated into the attitude adaptive sliding mode controller. Using the desired attitude angle as the input command, a desired torque manipulation quantity for driving the UAV is calculated, thus coordinating the position and attitude control of the UAV with the desired pull control law. This effectively suppresses system chattering without sacrificing the robustness of sliding mode control, significantly improving the control accuracy and anti-interference capability of the quadrotor UAV under complex disturbances and parameter variations.

This application provides an image motion compensation method, apparatus, and electronic device. The method, applied to an electronic device, includes: drawing a first nonlinear motion trajectory based on the frame order and motion position of the previous N frames; determining the motion position of a predicted frame image with frame order N+1 on the first nonlinear motion trajectory based on the image frame rate of the electronic device; and determining a motion vector from the Nth frame image to the N+1th frame image based on the image information of the Nth frame image, the image information of the N+1th frame image, the motion position of the Nth frame image, and the motion position of the predicted frame image, provided that the image information of the predicted frame image after moving a first distance remains consistent with the image information of the N+1th frame image. This narrows the search range of the motion vector from the Nth frame image to the N+1th frame image, improves search efficiency, and enhances the rendering performance of sliding screens.

The application claims a multi-target tracking method based on a linear camera model. The method first performs target detection on the input video sequence, and performs lens distortion compensation on the detection result; then based on the linear camera model, the detection result in the pixel coordinate system is inversely projected onto the ground plane in the three-dimensional world coordinate system to obtain the measurement parameters of the target in the real world coordinate system and the uncertainty description thereof; further, a camera motion compensation mechanism is introduced to correct the errors caused by camera jitter or displacement; on this basis, the Kalman filter is used to predict and update the target state; finally, a similarity calculation method combining the projection Mahalanobis distance and the intersection over union (IoU) is proposed to realize more robust and accurate target association. The application effectively reduces the tracking errors caused by occlusion, camera motion and nonlinear motion in a complex dynamic scene, and significantly improves the stability and accuracy of multi-target tracking.

The application discloses a kind of based on timing supervision and whole link occlusion perception's self-adapting target tracking method and system, the method constructs double-flow parallel prediction architecture, utilizes the Mamba network with linear calculation complexity to carry out nonlinear motion supervision to Kalman filter, when monitoring that prediction deviation exceeds threshold value, the process noise of filter or reset speed state and covariance matrix is adaptively adjusted, to eliminate cumulative inertia error;In detection stage, the intelligent non-maximum suppression strategy based on minimum area intersection-over-union (IoS) and depth difference is used, and the occluded effective target is retained;In association and update stage, appearance feature fusing is triggered by detecting trajectory collision risk, and feature update cooling lock is started for occluded or re-found target, and feature library pollution is blocked.The application can effectively improve the tracking accuracy of nonlinear maneuvering target, and significantly reduce the identity switching rate in dense crowded scene.

The application discloses an engineering machine driving path tracking control method and device, which can improve the prediction accuracy of the driving trajectory of a loader. The engineering machine driving path tracking control method comprises the following steps: constructing a nonlinear kinematics model of a loader based on simulation data of the loader; constructing a Koopman operator; linearizing the nonlinear kinematics model according to the Koopman operator to construct a whole vehicle dynamics prediction model; obtaining a deviation between a current state vector and a target state vector of the loader and a control increment between a current control vector and a target control vector; inputting the deviation and the control increment into the whole vehicle dynamics prediction model for calculation to generate an optimal prediction trajectory of the loader.

This invention belongs to the field of rigid body pose estimation technology, and discloses a rigid body pose estimation method, system, and device based on generalized correlation entropy geometric filtering. The method includes: acquiring target motion information and establishing a discrete nonlinear kinematic model; initializing the discrete nonlinear kinematic model; generating sigma points for the posterior state covariance matrix and the process noise covariance matrix, respectively, and propagating and updating the sigma points through a manifold fast unscented transformation; obtaining the predicted state mean, the prior state covariance matrix, and the square root of the prior state covariance matrix; updating the center parameters based on the information from historical moments; calculating the pseudo-measurement matrix and updating the gain; correcting the state estimate using the gain; determining whether convergence has occurred, and if not, continuing the iteration; otherwise, outputting the posterior state estimate as the final rigid body pose estimation result for that moment. This invention effectively solves the problems of robustness and accuracy degradation in rigid body pose estimation under non-zero mean and non-Gaussian noise environments.

This invention relates to the field of multi-agent drive control technology, specifically to an uncertain nonlinear intelligent agent drive control method based on linear quadratic adjustment. The method derives the standard differential equation mathematical model of the guide based on its uncertain nonlinear kinematic model, thus separating the unmeasurable nonlinear terms. The unmeasurable nonlinear terms are estimated using an observer, and a dynamic tracking controller is designed based on the observer. The input-to-state stability of the system is ensured by combining multi-loop nonlinear low-gain conditions, enabling the guide to track a time-varying reference signal. Subsequently, the reference signal generation system that generates this time-varying reference signal is used as a new guide. A drive controller is designed using linear quadratic adjustment, thereby utilizing state estimation and error optimization to solve for the optimal input. This simplifies the uncertain nonlinear drive control problem into a linear quadratic adjustment problem, achieving an integrated collaborative design of "guide tracking the reference signal" and "roamer reaching the target position."

This invention relates to the field of UAV-borne SAR imaging technology, specifically to a UAV-borne SAR imaging method based on complex convolution Unet, comprising: inputting a SAR complex feature map into a trained SAR imaging model and outputting a predicted SAR image; in the SAR imaging model: an encoder extracts abstract complex features layer by layer through a series of complex downsampling modules to obtain multi-scale low-resolution complex feature maps; a decoder recovers spatial resolution and image details layer by layer through a series of complex upsampling modules to obtain high-resolution complex feature maps; the low-resolution complex feature map output by the encoder is connected to the corresponding level of the complex upsampling module in the decoder; and the high-resolution complex feature map is converted into a complex image of the same dimension as the input SAR complex feature map as the predicted SAR image. This invention can learn and correct complex nonlinear motion distortions in the raw SAR echo end-to-end, achieving high-precision, well-focused UAV-borne SAR imaging.