This article mainly studies the trajectory tracking control for quadrotor unmanned aerial vehicle with unknown time-varying disturbances including parametric uncertainties, model errors, and external disturbances such as wind effects. Conventional backstepping control schemes usually cannot guarantee the performance when it faces the time-varying disturbances. Improved schemes, such as integral backstepping, can only compensate the disturbances in a relatively slow way. By introducing disturbance observer technology into the design of controller, a composite generalized proportional integral observer–based robust control design method is developed. First, by utilizing the generalized proportional integral observer, the lumped time-varying disturbances of unmanned aerial vehicle are estimated. Secondly, combining the value of disturbance estimation and feedforward controller by using backstepping control technology together, a composite controller has been developed, which can be called as backstepping control + generalized proportional integral observer. The proposed control method has a better capability of disturbance rejection and is easy to implement. Simulation and experimental results illustrate the good robustness and tracking performance of the proposed scheme.
In many industrial practices, it needs a permanent magnet synchronous motor to provide enough torque, such as autonomous vehicle driving. In the operation of a permanent magnet synchronous motor, the nonlinearly parameterized-uncertainties degrade control performances, causing the instability of motor speed and output torques. Based on the analysis of temperature effects and friction torque model, a composite controller is proposed in this paper which considers model uncertainties and external disturbances. An adaptive controller involving an online time-varying scaling gain is employed to eliminate the influence of nonlinearly parameterized-uncertainties. In addition, an extended state observer (ESO) is used to estimate the disturbance in the control system in which the estimated value is used to compensate for the feed-forward. Numerical simulation and experiment are performed and the results show that the proposed method may alleviate the performance degradation due to nonlinearly parameterized-uncertainties and disturbances. Simultaneously, it may improve the stability and anti-disturbance capacities of the system.
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