Auto-tuning of sliding mode control parameters using fuzzy logic

Sliding mode control guarantees robustness in the presence of modeling uncertainties and external disturbances. However, this can be obtained at the cost of high control activity that may lead to chattering. As one way to alleviate this problem, a boundary layer around sliding surface is typically used. In this case, the selection of control bandwidth and boundary layer thickness is a crucial problem for a trade-off between tracking error and chattering. The parameter tuning is usually done by a trial-and-error method in practice, causing significant effort and time. An auto-tuning method based on fuzzy rules is proposed. In this method, tracking error and chattering are monitored by performance indices and a controller tunes the design parameters intelligently in order to compromise both indices. To demonstrate the efficiency of the proposed method, a mass-spring translation system and a robotic control system are simulated and tested. It is shown that the proposed algorithm is effective in facilitating parameter tuning for sliding mode controllers