Adaptive Robust Control for Mirror-Stabilized Platform With Input Saturation

Abstract

The line-of-sight (LOS) kinematics and dynamics of a mirror-stabilized platform are derived using the virtual mass stabilization method. Accounting for the coupled and nonlinear kinematics and dynamics, the uncertainty of external disturbances, and the actuator input saturation in the mirror-stabilized platform, a modified adaptive robust control (ARC) scheme is proposed based on the command filtered method and the extended state observer (ESO). The command-filtered approach is used to ensure the stability and tracking performance of the adaptive control system under the input saturation. In the proposed scheme, the ESO is designed to observe the modeling error and unknown external disturbances. The stability of the control system is proved using the Lyapunov method. Simulation results and experimental results proved that the proposed control scheme can effectively reduce the occurrence of input saturation, attenuate the effect of unknown disturbances, and improve the position tracking accuracy.

Anti-Disturbance Neural-Sliding Mode Control for Inertially Stabilized Platform With Actuator Saturation

“…Several control schemes with actuator saturation have been proposed at the controller design stage. In [32], the command filtered approach was used to ensure both stability and tracking performance of the mirror-stabilized system under input saturation. A bounded virtual control law combined with a linear saturation function was proposed and the global stability of the ISP system can be guaranteed in the presence of input saturation if both controller and anti-windup compensator are simultaneously computed [33].…”