Research On Adaptive Trajectory Planning And Trajectory Tracing Control

Adaptive trajectory planning system is a support for UAV to realize independent flying and also one of the research trends in the field of UAV trajectory planning. As one of the key technologies in UAV, trajectory tracking control is very important to dynamic performance of UAV. High quality control system determines modern UAV with high performance to flying safely and completing complex tasks. In view of the above two questions, this paper respectively makes studies.First of all, build models to terrain and threats in the UAV flying aera. Due to the maneuver performance of UAV being restricted by biggest climbing angle and turning curvature, smooth the gradient and curvature of the terrain by the technology of terrain smoothing, which makes UAV fly randomly on the safe surface. On the basis of anlysis to characteristics of the existing optimization algorithms, the paper presents the cultural algorithm based on particle swarm optimization algorithm (PSO) and immune genetic algorithm. The algorithm makes full use of the double evolution mechanism of standard cultural algorithm.It's population space evolves with PSO which has fast convergence speed in order to ensure the convergence speed of the cultural framework. Belief space evolves with immune genetic algorithm which has perfect global searching ability.And the characteristic of global searching can guide the cultural algorithm towards the global optimal solution. As online path replanning has high demands for real-time characteristic, the paper puts forward a algorithm which mixes the immune clonal selection algorithm into particle swarm algorithm. The fast convergence property of PSO can ensure the convergence speed of the fusion algorithm. The local searching ability of clonal selection algorithm and the diversity characteristic of concentration mechanism can overcome the disadvantage of local optimum of PSO.Then put forward different target functions and design different b-spline tajectory fitting strategy for offline/online path planning.Then verify respectively offline/online path planner presented in this paper in Matlab.And the simulation results show that the proposed algorithms are effective and have good performance.in trajectory planning.In order to study trajectory tracking control, build mathematical model of UAV and linearize the model in longitudinal channel and lateral channel by using the small disturbance linearization principle. Design respectively trajectory tracking control law for longitudinal channel and lateral channel. Incremental PID algorithm is selected as the control method.Simulate changes of pitch angle and yaw angle of UAV. Set up hardware control circuit based on FPGA to simulate the process of trajectory tracking control. The experimental results reach the design purposes and verify the trajectory tracking control method presented in the paper.