The paper proposes a theorem to assert the arbitrarily good robustness of the fully actuated mechanical system controlled by the adaptive feedback linearization controller. The fully actuated system to be controlled is considerately perturbed by input disturbances and contains constant uncertain parameters in its Euler-Lagrange forced model. | Journal of Science and Technology 54 (2) (2016) 276-285 DOI: ABOUT THE ROBUSTNESS OF ADAPTIVE FEEDBACK LINEARIZATION CONTROLLER FOR INPUT PERTURBED UNCERTAIN FULLY-ACTUATED SYSTEMS Nguyen Van Chi1, *, Nguyen Hien Trung1, Nguyen Doan Phuoc2, 1 Thai Nguyen University of Technology, 3/2 Street Tich Luong, Thai Nguyen 2 Hanoi University of Science and Technology, 1 Dai Co Viet Street, Hanoi * Email: ngchi@ Received: 21 May 2015; Accepted for publication: 25 November 2015 ABSTRACT The paper proposes a theorem to assert the arbitrarily good robustness of the fully actuated mechanical system controlled by the adaptive feedback linearization controller. The fully actuated system to be controlled is considerately perturbed by input disturbances and contains constant uncertain parameters in its Euler-Lagrange forced model. It is shown in this paper that independent of input disturbances of the adaptive feedback linearization controller with appropriately chosen parameters will drive the output of controlled systems to the desired trajectory for any arbitrary precision. The adaptive controller is applied to the two-link planar elbow arm robot with unknown mass of the end-effector of second link and input torque noises caused by the viscous friction forces and Coulomb friction terms. Simulation results show that the arbitrary precision of the tracking errors always is guaranteed. Keywords: feedback linearization, robust adaptive feedback control, uncertain systems, EulerLagrange forced model. 1. INTRODUCTION The uncertainness of fully actuated mechanical systems, which is commonly described by an Euler-Lagrange forced model as follows [1]: (1) M (q ,θ )qɺɺ + C (q , qɺ ,θ )qɺ + g (q ,θ ) = u is understood that the q - dimensional vector and θ of model parameters are constant but unknown, which is however linear dependent on the system in the sense of: M (q ,θ )qɺɺ + C (q , qɺ ,θ )qɺ + g (q ,θ ) = F0 (q , qɺ , qɺɺ) + F (q , qɺ , .
