BSMRC optimization strategy of quadrotor based on improved particle swarm optimization algorithm
Aiming at the problem that the engineering application of backstepping sliding mode robust controller(BSMRC)of quadrotor UAV is limited due to the difficulty of parameter turning,a BSMRC parameter optimization strategy based on IPSO algorithm is designed.A nonlinear model of UAV with unknown disturbance is established and a BSMRC that compensates for the unknown disturbance is designed,and the system stability is proved by the second method of Lyapunov.The classic PSO algorithm is improved from the two aspects of inertia weight and learning factor,and its convergence speed is improved.On this basis,the BSMRC parameters are automatically adjusted.The simulation shows that IPSO can make the BSMRC parameters quickly converge to the optimal solution.Through modular programming and automatic code generation technology,the optimal BSMRC algorithm is deployed to the Pixhawk flight controller for flight experiments.The results show the effectiveness of the IPSO optimization strategy,reflecting the strong robustness and immunity of BSMRC.This optimization strategy solves the problem of low efficiency of UAV BSMRC parameter tuning,and uses Model-Based Design(MBD)technology to improve the development efficiency of UAV control system.
quadrotor UAVBSMRCattitude controlIPSO algorithmLyapunov methodparameter optimization and tuningMBD
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