Research On Automatic Flight Control Of Small-Scale Unmanned Helicopter

A small-scale unmanned helicopter has many specific flight modes, such as hovering, vertical take-off and landing, flying at a low altitude, and so on. Owing to its flexibility, helicopters are widely utilized in both military and civil fields. However, some difficulties in autonomous flight, which are caused by the complexity of helicopters, limit its rapid development. Especially, in contrast with the developed countries, studies on the unmanned helicopter starts late in China. Therefore, Chinese scientists have devoted much effort to enhance its autonomous flight performance. Considering the important effect of control strategies on flight performance, the dissertation proposes several high performance control algorithms for the nonlinearity, coupling, model uncertainty characteristics and disturbance of the small-scale unmanned helicopter system. Specifically, the major contribution of this work can be summarized as follows.Firstly, a hierarchical flight controller with exponential convergent performance is designed for small-scale unmanned helicopters to deal with the coupling of the attitude dynamics and translation dynamics. The traditionally hierarchical flight controller generally ignores the attitude response process, and assumes that the attitude quickly reaches the set point developed by the translation controller, which usually reduces the control performance. In view of the above problem, the dissertation analyzes the couple process of attitude response, and describes the attitude error by the quaternion to avoid singularity. Based on the description, an attitude nonlinear controller is proposed. In addition, the translation controller is designed by utilizing the backstepping method. The Lyapunov method is employed to prove the stability of the proposed approach. Numerical simulations are included to verify its control performance.Secondly, considering the main and aileron rotor flapping dynamics, an adaptive attitude and altitude controller is designed using the backstepping method. To achieve a satisfactory flight performance, it is important to tune suitable control gains for different flight missions in which the helicopter carries different loads. However, the tuning process is usually complicated for helicopter users. Therefore, we firstly make the unknown parameters meet the linear parametric conditions by the equivalent transformation of the attitude dynamics model. Subsequently, by analyzing the rotor flapping dynamics, an adaptive control algorithm is designed for the mass and inertia matrix unknown parameters from different loads. Lyapunov theory and Brabalat’s lemma are further utilized to prove that all the closed-loop system errors converge to zero asymptotically. Simulation results show that the designed controller still maintains good control results in the presence of the system parameters variation.Thirdly, a discrete-time model predictive attitude channel controller with the time-varying softening factor is proposed for the persistent disturbances that enter the system from the measurement components. In order to reduce the static error, we transform attitude channel transfer functions into the state space functions imbedded the integral. Then we carefully analyze the response speed and adjusting time of the attitude channels, and propose the time-varying softening factor to suppress the persistent disturbances effect on the reference trajectory. Moreover, considering the limited operation range of the helicopter rudder, the discrete-time model predictive attitude channel controllers are designed for both limited and unlimited control inputs. The stability of the close-loop system is proven by considering the fact that all the eigenvalues lie inside the unit circle. The designed controllers are then employed in a small-scale helicopter system, and the results show that it enhances the speed of the control system response, and decreases the influence of model uncertainty and persistent disturbances remarkably.Finally, the dissertation proposes a discrete-time model predictive attitude channel controller based on the non-minimal phase state space model. In the model predictive control system with the persistent measurement disturbances, the performance of state observer is reduced. Owing to this problem, we develop the non-minimal phase state space model for the attitude channels of a small-scale helicopter, whose states consist of the attitude channel control input and output data. Then based on the non-minimal phase state space attitude channels model, the discrete-time model predictive attitude channel controllers are designed for both constrained and unconstrained control inputs. The linear system theory proves the tracking performance and anti-jamming ability of the controllers. Practical flight experiments illustrate the satisfactory performance of the proposed controllers.