The high-performance drilling (HPD) process has a significant impact on production in many industries, such as the automotive, die/mold and aerospace industries. However, cutting conditions for drilling are generally chosen from a machining-data handbook, requiring operator experience and skill. In order to improve drilling efficiency while preserving tool life, the current study focuses on the design and implementation of a simple, optimal fuzzy-control system for drilling force. The main topic of this study is the design and implementation of a networked fuzzy controller. The control system consists of a two-input (force error and change of error), single-output (feed-rate increment) fuzzy controller with nine control rules, the sup-product compositional operator for the compositional rule of inference, and the center of area as the defuzzification method. The control algorithm is connected to the process through a multipoint interface (MPI) bus, a proprietary programming, and communication interface for peer-to-peer networking that resembles the PROFIBUS protocol. The output (i.e., feed-rate) signal is transmitted through the MPI; therefore, network-induced delay is unavoidable. The optimal tuning of the fuzzy controller using a maximum known delay is based on the integral time absolute error (ITAE) criterion. The goal is to obtain the optimal tuning parameters for the input scaling factors while minimizing the ITAE performance index. In this study, a step in the force reference signal is considered a disturbance, and the goal is to assess how well the system follows set-point changes using the ITAE criterion. The optimization is performed using the Nelder–Mead simplex (direct search) method. The main advantage of the approach presented herein is the design of a simple fuzzy controller using a known maximum allowable delay to deal with uncertainties and nonlinearities in the drilling process and delays in the network-based application. The results demonstrate that the proposed control strategy provides an excellent transient response without overshoot and a slightly higher drilling time than the CNC working alone (uncontrolled). A major issue in high performance drilling is the increase in cutting force and torque that occurs as the drill depth increases. Therefore, the fuzzy-control system reduces the influence of these factors, thus eliminating the risk of rapid drill wear and catastrophic drill breakage.
Optimal Tuning of FOPID-Like Fuzzy Controller for High-Performance Fractional-Order Systems