45 results about "Virtual leader" patented technology

A position keeping system, useable to maintain a position of a vehicle in a vehicle formation, to keep all formation members flying at a specified velocity and altitude, and to perform commanded maneuvers, determines guidance corrections based on a track state referenced to a leader or a virtual leader of the formation and on a formation position error indicating the error in the position of the vehicle in the formation. The guidance corrections are required so as to maintain the vehicles in the formation.

The invention provides manned / unmanned platform formation following and obstacle-avoidance method based on an obstacle graph model and a potential function, so that a problem that the existing potential function has a local extreme point and needs track planning and a problem can be solved and control of unknown obstacle avoidance autonomous formation forming and formation position adjustment of an unmanned platform during the marching process of going to a predetermined site of the unmanned platform formation following an manned platform in a complex environment is realized. Therefore, graph model construction and connected structure identification of a practical obstacle environment by an manned platform are realized; and thus a collision-free path of a virtual leader is planned and the unmanned platform forms formation autonomously by following the virtual leader, and the detected obstacle is avoided. Meanwhile, during the obstacle avoidance process, the predetermined task of the unmanned platform is not damaged, so that the unmanned platform still can carry out formation autonomously after obstacle avoidance to follow the manned platform.

The invention discloses an unmanned aerial vehicle and unmanned vehicle heterogeneous cluster formation tracking control method under topology switching. The tracking control method comprises the following steps: constructing a virtual leader of a heterogeneous formation; constructing a time-varying formation vector of the heterogeneous formation according to an expected time-varying formation configuration of the heterogeneous formation; establishing a distributed state observer for estimating the state of the virtual leader by members in the heterogeneous formation under a topology switchingcondition; establishing a system state observer for estimating the states of the members in the heterogeneous formation; constructing a distributed time-varying formation tracking controller; controlling the virtual leader to move according to the expected movement track of the heterogeneous formation; and controlling the members of the heterogeneous formation to track the motion tracks of the virtual leader through the distributed time-varying formation tracking controller. Therefore, a cluster system composed of multiple unmanned aerial vehicles and unmanned vehicles can track the expectedreference track while forming an expected time-varying formation configuration under a topology switching condition, and distributed time-varying formation tracking motion of a heterogeneous cluster system is realized.

The invention discloses a multi-underwater-robot formation control method based on reinforcement learning, and relates to the field of control of underwater robots. In the invention, after each robotnode in an underwater robot formation acquires the position of the robot node, a control center gives track information of a virtual leader and sends the track information to neighbor nodes of the virtual leader; a topological communication network is established among underwater robot nodes, and each underwater robot node only communicates with the neighbor nodes to keep the formation stable; theunderwater robot formation uses the current control strategy to track, each node calculates a one-step cost function by interacting with the environment and the neighboring nodes, the current controlstrategy is improved by minimizing a value function, when two steps including value iteration and strategy improvement both reach convergence, the control strategy of the underwater robots tracking an expected trajectory is optimal, and the optimal control strategy is used to achieve the goal of accurate tracking.

The invention discloses a fixed-wing unmanned aerial vehicle finite time formation fault-tolerant control method based on a neural network, and the method comprises the steps: firstly, carrying out the formation control through a virtual leader-follower structure, and carrying out the information interaction through a distributed formation method, based on this, designing a corresponding communication topological graph and calculating a corresponding adjacency matrix and a Laplacian matrix; then, aiming at a longitudinal model of the fixed-wing unmanned aerial vehicle, simplifying a dynamic model into a strict feedback form based on a reasonable assumed condition, and considering a failure fault of elevator deflection; on the basis of a backstepping method, sliding mode control is combined, an unknown nonlinear function of a model is processed through a radial basis function neural network, and the failure fault of the elevator is estimated in a self-adaptive mode, so that fault-tolerant control within finite time is achieved. The problem that formation fault-tolerant control is difficult due to the fact that the longitudinal model of the fixed-wing unmanned aerial vehicle serves as a high-order nonlinear system is solved, and the system has high robustness and can be stable within finite time.

The invention relates to a virtual leader-based collaborative adaptive tracking control method for a flight formation, belonging to the field of formation flight control. This method introduces the coordination strategy of the virtual pilot UAV, sets the relative position of each UAV and the pilot as feedback information, adopts the backstepping method to design the control input, and realizes the coordinated trajectory tracking according to the flight formation. The neural network is used to estimate the dynamic uncertainty, the online data is collected to construct the prediction error to evaluate the estimation ability, and the neural network weight adaptive update law is designed in combination with the tracking error. The present invention considers the influence of the dynamic uncertainty of the model of the multi-UAV system on the tracking performance during the formation flight process, and designs a composite estimation algorithm based on data analysis, which enhances the accuracy of the uncertain estimation and improves the formation flight. Performance offers new technological avenues.

The invention provides a multi-agent system cooperative control method capable of maintaining connectivity. After the running of a multi-agent system is started, when detecting that the multi-agent system with an agent is divided into two or more mutually disconnected connected subsystems according to the conditions of mutual connection with other agents at any time t, the agent determines whether the connected subsystem with the agent is a piloting subsystem or an adjoint system according to a preset election strategy, and elects a leader of the connected subsystem by communicating with the other agents in the connected subsystem; the leader in the piloting subsystem is called a virtual leader, and the leader in the adjoint subsystem is called a supporter; long-range connection is established between the virtual leader and each supporter; and each agent determines values of sigmai(t) according to own roles, and is self-controlled in real time by adopting the expression of a control rate. By the method, the problem that the connectivity cannot be maintained by the conventional multi-agent system cooperative control methods is solved.

The invention relates to the technical field of unmanned surface vessel formation control, in particular to an encircling and tracking method based on a distributed control unmanned surface vessel cluster. The method includes the following steps: encircled objects are sensed and detected, unmanned surface vessels are distributed, and a virtual leader is set; the signs and overall structures of encircled boats are identified, and kinematics models of the encircled boats are built; the unmanned surface vessels work cooperatively, and form a cluster to track the encircled objects; and the movingcoordinate systems of the virtual leader and the encircled objects are identified in real time, and when the moving coordinate systems overlap, the unmanned surface vessels move around and encircle the encircled objects. The invention provides an encircling and tracking method based on a distributed control unmanned surface vessel cluster. By matching the kinematics models of the encircled objectsthrough a database, the encircling of the encircled objects is not limited to the form of unmanned surface vessel formation. Based on an artificial potential field, an encircled object can be trackedand expelled efficiently. The method has the advantages of being safe, quick, efficient, and the like.

The invention provides a networked surface ship tracking control method, device, equipment and storage medium. The method includes: modeling the surface ship, obtaining a dynamic and kinematic model, setting a virtual leader, and setting the rest It is a follower; establish a directed topology map between surface ships; according to the dynamic and kinematic model and directed topology map, design the sliding mode surface and control algorithm under the hierarchical control framework, including: distributed estimation layer The control algorithm and the control algorithm of the local control layer; the state of the virtual leader is estimated according to the control algorithm of the distributed estimation layer, and the followers reach the formation formation at this layer to realize formation control; each water surface is driven according to the control algorithm of the local control layer The ship is tracked to the virtual leader for a predefined time. The layered control algorithm is used to realize the formation tracking control of surface ships, and the system state can converge to the origin on the new sliding surface, and can be applied to different complex systems.