Formation Transformation Based on Improved Genetic Algorithm and Distributed Model Predictive Control

Author:

Chen Guanyu1,Zhao Congwei1,Gong Huajun1,Zhang Shuai1,Wang Xinhua1

Affiliation:

1. College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

Abstract

In order to solve the problem of multiple aircraft formation transformation to a designated formation, a distributed formation transformation algorithm that decomposes the formation transformation problem into target-matching problems and trajectory-planning problems was studied. According to the actual formation transformation requirements, the target allocation index was proposed, and the improved genetic algorithm which is 23% better than other algorithms was used to achieve target matching. The adaptive cross-mutation probability was designed, and the population was propagated without duplicates by the hash algorithm. The multi-objective algorithm of distributed model predictive control was used to design smooth and conflict-free trajectories for the UAVs in formation transformation, and the trajectory-planning problem was transformed into a quadratic programming problem under inequality constraints. Finally, point-to-point collision-free offline trajectory planning was realized by simulation.

Publisher

MDPI AG

Subject

Artificial Intelligence,Computer Science Applications,Aerospace Engineering,Information Systems,Control and Systems Engineering

Reference21 articles.

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3. Rawlings, J.B., Mayne, D.Q., and Diehl, M. (2017). Model Predictive Control: Theory, Computation, and Design, Nob Hill Publishing.

4. Centralized control-based formation of multiple unmanned aerial vehicles;Liu;J. Huazhong Univ. Sci. Technol. Nat. Sci. Ed.,2015

5. Distributed model predictive control for multi-agent flocking via neighbor screening optimization;Zhou;Int. J. Robust Nonlinear Control,2017

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