A grey prediction fuzzy controller for constant cutting force in turning

Constant force control is gradually becoming an important technique in the modern manufacturing process. Especially, constant cutting force control is a useful approach in increasing the metal removal rate and the tool life for turning systems. However, turning systems generally have non-linear with uncertainty dynamic characteristics. Designing a model-based controller for constant cutting force control is difficult because an accurate mathematical model in the turning system is hard to establish. Hence, this study employed a model-free fuzzy controller to control the turning system in order to achieve constant cutting force control. Nevertheless, the design of the traditional fuzzy controller (TFC) presents difficulties in finding control rules and selecting an appropriate membership function. To solve this problem, a grey-theory algorithm was introduced into the TFC to predict the next output error of the system and the error change, rather than the current output error of the system and the current error change, as input variables of the TFC. This design of the grey prediction fuzzy controller (GPFC) cannot only simplify the TFC design, but also achieves the desired result in TFC implementation. To confirm the applicability of the proposed intelligent controllers, this work retrofitted an old lathe for a turning system to evaluate the feasibility of constant cutting force control. The GPFC has better control performance in constant cutting force control than does the TFC, as verified in experimental results.