6 results about "Matrix differential equation" patented technology

The invention relates to the technical field of intelligent construction, and discloses a construction steel structure fabricated building assembly method which comprises the steps that real-time pose data of a steel structure component is collected through a multi-source sensor array; performing multi-rate fusion processing on the pose data to generate six-dimensional state estimation containing position and pose errors; constructing an error matrix in the Lie group SE (3) space based on the state estimation, wherein the error matrix represents the deviation between the component pose and the target pose; and establishing a matrix differential equation model according to the error matrix, and solving an optimal compensation control quantity in a future time domain in a rolling manner through a model prediction control algorithm. Through combination of Lie group space error modeling and rolling time domain optimization, the system can sense the pose deviation of a component in real time and dynamically adjust a control strategy, limitation of traditional static error compensation and online parameter identification and disturbance suppression under complex working conditions are broken through, and uncertainty caused by dynamic changes of a construction environment is effectively dealt with.

This invention provides an adaptive admittance method and system based on the optimal control LQR theory, including constructing an environmental dynamics model and a robotic arm admittance control model, and deriving their interactive dynamics model; defining state variables and control inputs, and establishing a standard form state-space equation; constructing a quadratic performance index function, transforming admittance parameter optimization into an LQR problem; substituting the linear quadratic regulator framework into the quadratic performance index function, transforming the LQR problem into solving the Riccati matrix differential equation, and deriving analytical expressions for virtual optimal stiffness and virtual optimal damping; within the robotic arm control sampling frequency, inputting real-time collected environmental contact forces and the actual pose of the robotic arm end effector, along with set weighting coefficients, into the analytical expressions to calculate optimal virtual stiffness and damping; and then calculating pose corrections based on the admittance control model to correct the robotic arm's motion trajectory.

Disclosed is a method for digitally simulating polymerase chain amplification of at least one target, comprising simulating a plurality of successive amplification cycles, each cycle comprising: a hybridization stage; an extension stage; then, a denaturation stage; wherein the hybridization phase comprises, for each cycle: obtaining, for said cycle, initial values of a concentration vector of a plurality of nucleic acid molecules in the form of a single strand; initializing a concentration matrix of a duplex formed by hybridization of a plurality of nucleic acid molecules in a single strand form; the evolution of the concentration matrix during the hybridization phase is calculated by applying to the concentration matrix a matrix differential equation representative of the kinetics formed by the duplex according to the concentrations of the plurality of nucleic acid molecules.

The invention discloses an excitation brushless motor accurate calculation method based on an equivalent magnetic circuit method. The method comprises the following steps: acquiring parameter information of a target excitation brushless motor; constructing an initial equivalent magnetic circuit as a current equivalent magnetic circuit; calculating yoke plate magnetic flux and tooth magnetic flux; constructing an air gap magnetic flux expression and expressing the rest of magnetic fluxes as air gap magnetic fluxes; carrying out loop calculation by adopting a KVL law; calculating to obtain an intermediate matrix differential equation; decomposing and processing the intermediate matrix differential equation to obtain an air gap magnetic flux calculation result based on the current equivalent magnetic circuit; updating the current equivalent magnetic circuit of the target excitation brushless motor at the next moment based on the pre-trained graph structure neural network; and repeating the steps to realize real-time calculation of the air gap magnetic flux of the target excitation brushless motor. And completing calculation of the excitation brushless motor based on the equivalent magnetic circuit method according to the real-time air gap magnetic flux. The invention also discloses a system for realizing the accurate calculation method of the excitation brushless motor based on the equivalent magnetic circuit method. The method is high in reliability, good in precision and high in dynamic precision.

The invention relates to a neural network control method for solving a time-varying matrix based on integral enhancement. The invention provides a novel recurrent neural network based on integral enhancement so as to solve a time-varying matrix equation. The method comprises the following steps: firstly, introducing a group of non-negative slack variables, converting a time-varying inequality group into a matrix equation form, and constructing a matrix differential equation about an error function; secondly, deriving an explicit solution of a differential equation of the matrix through pseudo-inverse transformation of the matrix, and adding an integral enhancement item on this basis to improve the anti-interference capability of a solving model; according to the method, the time-varying matrix equation is solved by adopting the advanced integral enhanced recurrent neural network method, and the method has the characteristics of high calculation efficiency, fast convergence, strong anti-noise capability and good robustness.

The application is directed to the non-cooperative target observation task with large navigation information error and low update frequency, thereby a strong security efficient non-cooperative target active observation trajectory planning method is provided, and the application relates to the field of spacecraft orbit optimization technology. The state gain reachable set is calculated from the navigation initial error by the matrix differential equation, and the spacecraft structure size compensation is carried out, the boundary of the safety strategy is taken as the path inequality constraint, the optimization model with the path fuel consumption and the path length as the composite performance index, the optimization variable is the observation path state and the corresponding control, and the trajectory planning model is established comprehensively, and then the model prediction control is used to solve the optimization problem, so as to obtain the corresponding path state. The application is suitable for the trajectory planning of the non-cooperative target active observation in the space orbit optimization.