9results about How to "Reduce tracking error" patented technology

The invention discloses a crisscross optimization robust model predictive control method for an automatic sweeping robot. The crisscross optimization robust model predictive control method is adaptive to a trajectory tracking system with parameter uncertainty. According to the method, a discrete time controlled system with parameter uncertainty, a reference trajectory system and a tracking error system are constructed, performance evaluation indexes are defined, the stable control gain range of a basic RMPC controller is determined by solving a minimum and maximum optimization problem and linear matrix inequality constraints, and a multi-objective optimization function is combined in the range to achieve the stable control of the RMPC controller. The optimal additional control gain is iteratively searched by means of a crisscross algorithm, an optimized controller is formed, the stability and the dynamic performance are considered, the influence caused by parameter uncertainty can be overcome, the rising time and the adjusting time of trajectory tracking are remarkably shortened, the tracking error and the energy consumption are reduced, and the tracking efficiency is improved. And the dual requirements of the automatic sweeping robot on real-time response and control precision are met.

This application discloses a control method, device, dexterous hand, makeup robot, storage medium, and program product for a makeup robot, belonging to the technical fields of makeup robots and dexterous hands. The makeup robot includes an execution component, which comprises a robotic arm and a dexterous hand disposed at the end of the robotic arm. The execution component is used to hold matching makeup tools. The method includes: acquiring target compliant interaction parameters; obtaining visual displacement compensation based on the user's facial image information; obtaining force-controlled displacement compensation based on the target compliant interaction parameters and the actual force between the matching makeup tools and the user's face; correcting preset trajectory parameters based on visual displacement compensation and force-controlled displacement compensation; and controlling the movement of the execution component based on the corrected preset trajectory parameters. The control method of the makeup robot in this application can adapt to changes in spatial position caused by slight movements of the user during the makeup process, improving the makeup quality and user experience of automated makeup operations.

This invention provides a residential aggregator-based optimal energy management method, comprising the following steps: constructing an aggregator model, building generalized energy storage models for three types of residential appliances—batteries, HVAC systems, and electric vehicles—and aggregating them into a residential aggregator for centralized management; generating scheduling instructions for the aggregator, in the first decision-making stage, formalizing the optimization control process into a Markov decision process, interacting with the environment based on the Soft Actor-Critic framework, learning the optimal scheduling strategy, and tracking the upper-level power grid scheduling while ensuring operational constraints; decomposing the aggregator's control instructions, in the second decision-making stage, the residential aggregator generates scheduling plans for each appliance through a three-step decomposition algorithm to follow the aggregated power scheduling defined in the first decision-making stage. This invention achieves automated and integrated control of residential energy, improves the integration and intelligence level of the energy system, reduces operating costs, and enhances user comfort.

This invention discloses a group train tracking operation optimization method considering communication delay, comprising the following steps: establishing a heavy-haul railway train group with a "leader-follower" topology; constructing a multi-objective optimization model based on vehicle characteristic constraints, speed limits, and safety distance constraints; generating random communication delays in the model, calculating the time steps corresponding to the delays, and having the following train make control decisions based on the state information of the preceding train at the previous time step; and solving for the running speed of the following train in the multi-objective optimization model using a particle swarm optimization algorithm. This group train tracking operation optimization method effectively solves the problems of uncertainty and dynamic response lag caused by communication delays during the tracking operation of heavy-haul railway train groups. It can not only significantly reduce tracking errors between trains and improve speed synchronization, but also effectively reduce distance fluctuations during acceleration and deceleration phases, ensuring stable train spacing.

The application discloses a rope driving mechanical tracking control method based on TDE and recursive non-singular terminal sliding mode, and relates to the technical field of mechanical hand control. The application comprises the following steps: through mechanical dynamics analysis, the dynamics standard equation of the mechanical hand is determined and is converted into a TDE simplified equation, and a tracking error is defined; an FNTSM function containing a proportional control parameter is constructed, a recursive non-singular terminal sliding mode variable is formed in combination with a recursive integral term; an interference adaptive law is designed to dynamically adjust the proportional control parameter, the convergence speed and the chattering characteristics of the tracking error are analyzed, and a composite reaching law is generated; based on the composite reaching law and the updated TDE simplified equation, a generalized output vector of a joint controller containing a fluctuation parameter is extracted, a complete control law is formed, the generalized vector is output in real time through the control law, the motion trajectory of the mechanical hand is simulated, and high-precision tracking control is realized.

The application discloses a high-precision PID trajectory tracking control method for a space manipulator, and relates to the technical field of spacecraft control. The method first establishes a dynamic model of the rotating motion of the manipulator containing system uncertainty; a nonlinear disturbance observer is constructed to estimate the unmodeled dynamics and external disturbances of the system in real time; a PID compound controller is designed in combination with the uncertainty estimation value; a PID parameter optimization problem is established with the minimum trajectory tracking error as a target and the joint angle, angular velocity and control torque as physical constraints; the physical constraints are converted into finite-dimensional constraints by using a constraint transcription method, and the gradient of the objective function and the constraints with respect to the PID parameters is calculated, and the optimal PID parameters are solved by an iterative optimization algorithm. The application realizes high-precision trajectory tracking of the free-flying space manipulator by using the compound control architecture and parameter optimization, effectively suppresses system uncertainty, and ensures strict satisfaction of multiple physical constraints, and has good engineering generality.

The utility model relates to fast knife servo device technical field, especially, it relates to a double stroke fast knife servo device. Including: in target displacement direction, series connection setting first displacement component and second displacement component, first displacement component and second displacement component are used for superimposed formation total target displacement amount, wherein, second displacement component is used for compensating the displacement error that first displacement component generates. The utility model series connection sets two displacement components to superimposed realization total expected displacement, namely total target displacement amount. Among them, first displacement component is used to reduce the error between the actual displacement of output and the expected displacement signal of input, second displacement component is used for further compensating and eliminating the error that first displacement component generates, and then the tracking error of fast knife servo device whole keeps at low level, to improve the machining precision.

This invention discloses a target tracking method for robot vision; belonging to the technical field of target tracking methods; it includes the following steps: (1) manually obtaining the upper left and lower right coordinates of the target to be tracked on the two-dimensional image in the first frame of the image, extracting the target image and its surrounding sample image blocks as templates, and obtaining the template sample feature tensor through a feature extraction deep network; (2) inputting the search region sample into the feature extraction deep network to obtain the search region sample feature tensor; (3) simultaneously inputting the template feature tensor and the search region feature tensor into a feature enhancement and feature fusion network based on an involution-attention model to obtain a fused feature tensor containing template features and search region features, and then passing it through a classification network and a regression network to obtain the tracking result; this invention aims to provide a target tracking method for robot vision with high tracking success rate, small tracking error and real-time tracking capability; for real-time target tracking.

The application discloses a dynamic liquid level detection system and method based on a stirred tank, and belongs to the field of liquid level detection. The system comprises a differential pressure sensor module, a rotating speed acquisition module and a signal processing unit. The signal processing unit comprises a vortex dynamic compensation module, an adaptive filtering module and a delay prediction compensation module connected in series. The application collects the differential pressure signal of the liquid column in the tank and converts it into an apparent liquid level value, and simultaneously collects the rotating speed signal of the stirring paddle. The liquid level deviation caused by the vortex at the tank wall is calculated according to the rotating speed signal, and a first-order recursive tracking output dynamic compensation is used to eliminate the vortex liquid level deviation. The low-pass filter cutoff frequency is adaptively determined according to the rotating speed signal to suppress the stirring fluctuation noise. The change rate of the filtered liquid level value and the group delay are used for forward prediction correction to reduce the filtering delay. The application realizes dynamic cooperation of each link by using the rotating speed signal as a link, and improves the accuracy and response speed of the liquid level measurement under the stirring condition.