Treffer: Time-varying gain extended state observer-based adaptive optimal control for disturbed unmanned helicopter.

In this paper, the robust adaptive optimal tracking control problem is addressed for the disturbed unmanned helicopter based on the time-varying gain extended state observer (TVGESO) and adaptive dynamic programming (ADP) methods. Firstly, a novel TVGESO is developed to tackle the unknown disturbance, which can overcome the drawback of initial peaking phenomenon in the traditional linear ESO method. Meanwhile, compared with the nonlinear ESO, the proposed TVGESO possesses easier and rigorous stability analysis process. Subsequently, the optimal tracking control issue for the original unmanned helicopter system is transformed into an optimization stabilization problem. By means of the ADP and neural network techniques, the feedforward controller and optimal feedback controller are skillfully designed. Compared with the conventional backstepping approach, the designed anti-disturbance optimal controller can make the unmanned helicopter accomplish the tracking task with less energy. Finally, simulation comparisons demonstrate the validity of the developed control scheme. • The proposed TVGESO can avoid the initial peaking phenomenon and make the system have better transient performance. • The proposed TVGESO has easier and rigorous stability proof process. • The designed ADP-based optimal tracking control approach can make the unmanned helicopter achieve the task with a specified performance index. [ABSTRACT FROM AUTHOR]