Wufan Wang

Robust constraint backstepping control for high-performance aircraft with account of unsteady aerodynamic effects

This paper presents a robust constraint backstepping control scheme for high performance aircraft attitude tracking in the presence of physical constraints, model uncertainties and unsteady effects. The six-degree-of-freedom aircraft model with unsteady aerodynamics is first established, of which the characteristics are investigated through open-loop analysis. Based on the immersion and invariance approach, a state observer is developed to estimate the unmeasurable unsteady aerodynamic states. The unsteady effects are then compensated in the controller design where the bounds of estimate errors and model uncertainties are used to increase robustness. In addition, a command filter is introduced to impose physical constraints on states and control inputs and overcome the ‘explosion of terms’ problem. An auxiliary system of which the states are applied to the controller design is constructed as well to evaluate the constraint effects. Furthermore, stability of the closed-loop system and convergence of the tracking error are proven by Lyapunov stability theorem. Finally, several numerical simulations are performed to verify the effectiveness and robustness of the proposed control scheme.

Automatic PID tuning via differential evolution for quadrotor UAVs trajectory tracking

In this paper, a two-stage automatic proportional-integral-derivative (PID) tuning scheme based on the differential evolution (DE) algorithm is developed for the trajectory tracking control of quadrotor unmanned aerial vehicles (UAVs). Nonlinear dynamics model of the quadrotor is established, based on which the tuning scheme is conducted. In the first stage, the inner loop attitude PD controllers are tuned separately with respect to the roll, pitch and yaw channel to achieve a fast transient response. In the second stage, the outer loop position PID controllers are tuned upon the optimal attitude controllers to achieve a smooth and precise trajectory tracking performance. In order to deal with coupled dynamics between the x/y channel and the altitude channel, time domain performance indexes of x/y and altitude channels are both incorporated in the cost function to be minimized. An adaptive mutation operator is utilized in the DE algorithm to maintain the population diversity in the early phase of the algorithm and accelerate convergence in the later phase. Several maneuverings including take-off, smooth translation, circular and spiral climb motions are carried out to evaluate the effectiveness of the proposed scheme.

Flight controller design and demonstration of a thrust-vectored tailsitter

This paper discusses the design and control methods of a thrust-vectored tailsitter that combines the advantages of both fixed wing and rotary wing systems. Separable takeoff bracket and controllable forward landing are implemented to reduce the flight weight and mitigate the effects of crosswinds. A six-degrees-of-freedom model especially for this tailsitter is then proposed to describe the dynamics of the whole system. Attitude representation based on horizontal /vertical Euler angles is presented to avoid the problem of singularity. Attitude and altitude controllers that switch between horizontal and vertical modes are used. In these controllers linear/constant acceleration approximation and filtered feed-forward acceleration algorithm are implemented. Effectiveness and reliability of the proposed control methods are demonstrated and evaluated by experimental results of the whole flight envelope.

Optimal state estimation for sampled-data systems with randomly sampled and delayed measurements

The optimal state estimation problem for sampled-data systems with randomly sampled and delayed measurements is addressed in this paper. An optimal filter is presented first for the sampled-data system with randomly sampled and delay-free measurements from multiple sensors. The filter, which has been proved to be optimal in the sense of minimum estimation variance, updates the state estimation once new measurements are available. The result is applicable to a wide range of sampling cases of which the corresponding state estimation procedures are formulated separately. Discrete-time equivalent of the filter is also derived rigorously which makes it feasible for computer implementation. Furthermore, we extend the optimal filter and develop a sliding time window estimator through the measurement reorganization technique to deal with the situation of delayed measurements. Monte-Carlo simulations are carried out to demonstrate the effectiveness of the proposed approach.