Nonlinear Model Based Coordinated Adaptive Robust Control of Electro-Hydraulic Robotic Manipulators: Methods and Comparative Studies

Abstract

Compared to conventional robot manipulators driven by electrical motors, hydraulic robot arms have richer nonlinear dynamics and stronger couplings among various joints (or hydraulic cylinders). This paper focuses on the physical model based coordinated adaptive robust control (ARC) strategies that explicitly take into account the strong coupling among various hydraulic cylinders (or joints). In our recent studies, two such methods were proposed to avoid the need of acceleration feedback in doing ARC backstepping designs. The first method uses an observer to recover the state needed for the ARC backstepping design. The second method utilizes the property that the adjoint matrix and the determinant of the inertial matrix can be linearly parametrized by certain suitably selected parameters and employ certain over-parametrizing techniques. Theoretically, both the resulting ARC controllers guarantee a prescribed output tracking transient performance and final tracking accuracy while achieving asymptotic output tracking in the presence of parametric uncertainties only. This paper focuses on the comparative studies of these two methods under various practical constraints. Extensive simulation results which are based on a three degree-of-freedom (DOF) hydraulic robot arm are presented to illustrate the advantages and drawbacks of each method.