The objective of this study is to develop free model
sliding mode controllers (SMC) in discrete-time domain for
robot manipulators. First, an appropriate discrete sliding mode
controller (DSMC) with stability proof is designed. A neurofuzzy discrete sliding mode (NFDSMC) is developed to remove
the drawbacks of DSMC. In the NFDSMC, a two-layer neural
network used to approximate the equivalent control law. In
order to evaluate the switching law, a fuzzy system is used.
Neural network weights are updated adaptively with backpropagation (BP) algorithm using the sliding manifold.
Simulation results illustrate performances of these controllers in
the control of the three link SCARA robot. Moreover, the
sampling time effects on the sliding surface convergence are
discussed.