A constrained error-based MPC for path following of quadrotor with stability analysis
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This paper proposes a linear constrained model predictive control (MPC) to solve the path following problem for quadrotor unmanned aerial vehicles. In the controller, an augmented model is employed to completely eliminate the tracking error due to external disturbances imposed on the quadrotor. The proposed controller is capable of improving the trade-off between feasibility and performance of the system. By approximating the control input sequence in MPC with Laguerre function, the computational burden significantly decreases and the closed-loop performance improves. In addition, a prescribed stability procedure is applied to guarantee the asymptotic stability of the quadrotor error dynamics. Besides, the proposed method improves the numerical ill-conditioning problem in solving MPC, by modifying the position of the closed-loop system poles to lie inside the unit circle. In the simulation results, two scenarios for the quadrotor tracking problem are considered. The results demonstrate the capability and the effectiveness of the proposed control strategy in disturbance rejection, fast trajectory tracking and the quadrotor stability, while a desired performance is achieved.
KeywordsConstrained model predictive control Laguerre function Prescribed stability Quadrotor dynamics
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Conflict of interest
The authors declare that they have no conflict of interest.
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