Vehicle Formation Control Based On Feedback Linearization

The controlling of vehicle formation is of great significance to improve the intelligence and security for the transport system. This paper investigates the problem of vehicle formation control in the framework of leader-follower methodology. The main contributions of this paper are as follows:1. Through the leader-follower method, we have established two dynamic models based on kinematics, which are not damped and pure rolling without sliding to vehicles of the formation. In one model, the sensor is designed as the fixed off-axis point; in the other model, variable off-axis point is designed whose offset is related to the expectations. And, in order to facilitate the calculation, we have established a new Coordinate system where the follower acted as the reference. Then, the tracing of the follower to the leader are translated to the tracing of the follower's off-axis point to the virtual vehicle, actually the controlling of three error systems.2. On the basis of the controlling structure model's third level, input-output feedback linearization tracking controllers with off-axis points of fixed and variable are designed using the two dynamic models. Both of the tracking controllers look the position error and angular error as the state variables, and look the follower's linear velocity and angular velocity as the controlled variables. Through the controlling to the two gains, the follower can maintain the desired distance and desired angle to the leader. And the two tracking controllers'asymptotic stability gets proved through Lyapunov theorems.3. The tracking controllers are extended to the formation of N vehicles by graph theory. And taking five-pointed star formation of ten vehicles as example, adjacency matrix and parameter matrix under different following relationships are designed. After the supposing of the two matrix and the initial conditions, simulate the entire formation, and compare the two tracking controllers'advantages and disadvantages under the same and different following relationships.