Aiming at the problem of formation control, a hybrid hierarchical distributed formation structure based on the virtual leader, centralized, and distributed structure is proposed and named active agent AA. Based on the established formation structure, a time-varying formation consensus control model and the changed model with no collision condition, which combined the formation flight problem with the collision avoidance problem are constructed, simplified the structure of the controller, then theoretically analyzed the consensus conditions of non-AA agents, and AA agent, respectively, obtained the necessary conditions of consistent convergence, and finally, simulated a formation with one virtual leader and four followers; the simulation results show that the control law designed in this study achieved the velocity consensus of non-AA agents and the location consensus of the AA agent; it also shows that the hybrid hierarchical distributed formation structure proposed in this study is reasonable, effective, and achievable.
Aiming at the multiconstraint complex problem of path planning, a hybrid algorithm with fast convergence and fast obstacle avoidance is proposed. According to the actual aircraft, a multiconstrained path cost model with seven components is constructed and defined the parameters and penalty factors of each part. To improve the sensitivity of each part of the trace planning cost function, according to the inconsistency of the cost index unit and measurement range, the expert scoring method is used to configure and normalize the index with weight. Make full advantage of the ACO algorithm and the artificial potential field algorithm to form the ACA hybrid algorithm, a pheromone heuristic function improvement method is proposed, and a control factor is introduced. The proposed model and planning algorithm are simulated based on the MATLAB platform environment, and it is shown by simulations that the hybrid algorithm has obvious advantages in terms of motion trajectory smoothness, number of iterations, and minimum path cost .It well solved the practical application problem of fast path planning convergence and fast avoiding obstacles in the complex environment.
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