FAT-based adaptive sliding control for flexible arms: Theory and experiments

An adaptive sliding controller is proposed in this paper for flexible arms containing time-varying uncertainties with unknown bounds based on function approximation technique (FAT). The uncertainties are firstly represented by finite linear combinations of orthonormal basis with some unknown constant weighting vectors. Output error dynamics can thus be derived as a stable first-order filter driven by parameter error vectors. Appropriate update laws for the weighting vectors are selected using the Lyapunov method so that asymptotic convergence of the output error can be proved as long as a sufficient number of basis functions are used. Effects of the approximation error on system performance are also investigated in this paper. Both computer simulation and experimental results confirm the feasibility of the proposed control strategy.