25 research outputs found

    A fractional order predictive control for trajectory tracking of the AR.Drone quadrotor

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    A fractional-order model predictive control with extended prediction self-adaptive control (FOMPC-EPSAC) strategy is proposed for the AR.Drone quadrotor system. The objective is to achieve an optimal trajectory tracking control for an AR.Drone quadrotor by using a fractional order integral cost function in the conventional MPC-EPSAC algorithm. In addition, a particle swarm optimization (PSO) algorithm is applied to find the optimal weighting matrices, which depend on the terms (α, β) of the fractional order cost function. Some simulation results show the superiority of FOMPC-EPSAC over conventional MPC-EPSAC with respect to trajectory tracking and robustness under wind disturbances
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