Adaptive Robust Control for Servo Mechanisms With Partially Unknown States via Dynamic Surface Control Approach

In order to achieve high performance control for servo mechanisms with electrical dynamics and unmeasurable states, an observer-based adaptive robust controller (ARC) is developed via dynamic surface control (DSC) technique. To represent electrical dynamics, a third-order model is used to describe the servo mechanism. However, the third-order model brings some difficulties to observer construction and recursive controller design. To solve this problem, we first transform the model into a particular form suitable for observer design, and then construct a parameterized observer to estimate the unmeasurable states. The state estimation is based on the output and its derivatives, which can be acquired by an output differential observer. Subsequently, an observer-based ARC can be developed through DSC technique, with which the problem of "explosion of complexity" caused by backstepping method in the traditional ARC design can be overcome. A stability analysis is given, showing that our control law can guarantee uniformly ultimate boundedness of the solution of the closed-loop system, and make the tracking error arbitrarily small. This scheme is implemented on a precision two-axis turntable. Experimental results are presented to illustrate the effectiveness and the achievable control performance of the proposed scheme.