Fuzzy logic based tuning of sliding mode controller for robot trajectory control

Abstract

Sliding control guarantees system performance in the presence of modeling uncertainties and parameter inaccuracies. However this is obtained at the price of high control activity that may exacerbate chattering. As one way to alleviate this problem a continuation method using a boundary layer around switching is usually used. In this case selecting the control bandwidth and boundary layer thickness is a crucial problem for the trade-off between sliding performance and chattering. The parameter tuning is usually done by trial-and-errors in practice causing significant effort and time. An auto-tuning method based on fuzzy rules is suggested. To this end, the tracking error index and chattering index are defined first and then the fuzzy rules are designed to compromise the error and chattering indices. To demonstrate the efficiency of the proposed method a robotic control system is simulated and tested. It is shown that the proposed algorithm is effective to facilitate the parameter tuning for sliding mode controllers.