In a general DIARC framework [13], the emphasis is always on the guaranteed transient performance and accurate trajectory tracking in the presence of uncertain nonlinearity and parametric uncertainties along with accurate parameter estimation for secondary purpose such as system health monitoring and prognosis. Need for accurate parameter estimation calls for the use of Least Square Estimation (LSE) type of algorithms for such a seamless integration of good tracking performance and accurate parameter estimation. This paper presents a physical model based integrated direct/indirect adaptive robust control (DIARC) strategy for a hydraulically actuated 3-DOF robotic arm. To avoid the need of acceleration feedback for DIARC back-stepping design, the property, that the adjoint matrix and the determinant of the inertial matrix could be linearly parameterized by certain suitably selected parameters is utilized. Unlike gradient-type parameter estimation law, which used overparamterization, there is no multiple estimation of the single parameter. Theoretically, the resulting controller is able to take into account not only the effect of parametric uncertainties coming from the payload and various hydraulic parameters but also the effect of uncertain nonlinearities. Furthermore, the proposed DIARC controller guarantees a prescribed output tracking transient performance and final tracking accuracy while achieving asymptotic output tracking in the presence of parametric uncertainties only. Simulation results based on a three degree-of-freedom (DOF) hydraulic robot arm (a scaled down version of an industrial back-hoe/excavator arm) are presented to illustrate the proposed control algorithm.
A novel robust adaptive control algorithm with finite-time online parameter estimation of a humanoid robot arm