4results about How to "Solve for stability" patented technology

The invention relates to a virtual power plant optimization scheduling method and system. The method comprises the following steps: establishing an operation model of a multi-type adjustable resource main body; constructing a master-slave game model of the aggregator and the resource main body, wherein the master-slave game model comprises an upper-layer model taking the aggregator as a leader and a lower-layer model taking the resource main body as a follower; solving a master-slave game model of the aggregator and the resource main body to obtain an optimal compensation price strategy and an optimal response power strategy, and constructing an optimal power scheduling plan according to the optimal response power strategy; the optimal power scheduling plan is used for being issued to each adjustable resource main body for execution so as to realize optimal scheduling of the virtual power plant. According to the method, the participation enthusiasm of the resource main body can be stimulated, the user participation degree can be improved, the scheduling instruction execution rate can be improved, the model accuracy can be improved, the cooperative capability of heterogeneous resources can be improved, and the overall operation economy and stability of the virtual power plant can be improved.

This invention is a method for inverting azimuth difference seismic data in inclined fractured rocks. Previous AVAZ inversion methods for fracture parameters were mostly based on the HTI medium assumption, with insufficient consideration for fracture dip angle. The fixed form of the inversion constraint terms made it difficult to adapt to changes in parameter statistical characteristics, and the regularization parameters were all manually adjusted, affecting inversion accuracy and efficiency. This invention establishes an approximate formula for the reflection coefficient of the TTI medium, characterized by the P-wave and S-wave velocities, density, and fracture elastic parameters of the background medium. It utilizes pre-stack azimuth difference data to perform AVAZ inversion of fracture parameters. Dynamic sparsity constraints are introduced, dynamically adjusting the sparsity of the constraints based on data characteristics, and a covariance matrix is ​​introduced to consider the statistical regularity between parameters. Combining iterative reweighted least squares and adaptive regularization parameter acquisition methods, the dynamic constraint inverse problem is transformed into a weighted... L A 2-norm objective function is used to achieve a stable solution. Data testing shows that this invention can effectively improve the inversion accuracy of crack elastic parameters.

The invention provides an equilibrium strategy generation method, device and equipment for a large-scale unmanned cluster game, relates to the technical field of large-scale autonomous system decision control, and aims to solve the defects of poor stability and low calculation efficiency when an equilibrium strategy is generated for a large-scale unmanned cluster in the prior art. And efficient collaboration and autonomous decision-making of a large-scale cluster in a complex environment are realized. Comprising the following steps: dividing devices included in a device cluster into a plurality of populations based on characteristic parameters of each device included in the device cluster; constructing an average field game model of the plurality of populations, wherein the average field game model is used for reflecting an interaction effect among the plurality of populations; iteration is carried out based on a target mode and the average field game model, a balance control strategy of the equipment cluster is obtained, and the target mode comprises at least one of exponential weighted aggregation, near-regularization, bootstrap regularization and heuristic acceleration; and controlling the equipment cluster to execute the target task based on the balance control strategy.

The application discloses a wheeled quadruped robot dynamic obstacle avoidance method, system and device, relates to the technical field of robot autonomous navigation and motion control, and comprises the following steps: collecting environment original point cloud data and pose information of a wheeled quadruped robot, pre-processing the point cloud data to obtain an obstacle cluster; calculating the centroid position and speed information of each obstacle cluster; predicting the position of the obstacle in a future time period; obtaining an initial predicted trajectory based on the pose information of the wheeled quadruped robot; combining the predicted position of the obstacle to construct a relative motion point stream of the obstacle; performing feature extraction to obtain a dual variable feature; constructing a model predictive control optimization problem; solving the optimization problem by using an alternating solution algorithm to obtain an optimal control sequence at the current moment; and finally generating an optimal control instruction to drive the wheeled quadruped robot to perform a dynamic obstacle avoidance action. The application can improve the motion real-time performance, stability and environmental adaptability of the wheeled quadruped robot in a complex environment.