## 4 Robotic Deburring Process Parameter Control Method based on Fuzzy Control  
A robotic deburring process parameter control method of the five-DOF robot manipulator for robotic deburring is proposed in this section. This proposed method is adopted in deburring process parameter adjustment control for the stable robotic deburring with a constant cutting speed and a constant cutting force via a designed fuzzy controller. According to metal cutting principle, the cutting parameters include cutting speed, cutting feed and cutting depth. Taking carbide turning tools for carbon steel turning as an example, related researches showed that the biggest impact on tools is the cutting speed, followed by the cutting feed, and lastly the cutting depth [46; 47; 48]. More generally, the rough machining should select cutting parameters for the maximum productivity. Thus, a larger cutting depth (or cutting width) should be selected first, and after the majority of the machining allowance is removed, a suitable cutting feed (or a cutting thickness) and a cutting speed are selected in turn by the cutting condition. Finish machining generally uses a small cutting depth and cutting feed, and then a higher cutting speed to improve the machining accuracy and reduce the surface roughness. In this article, robotic deburring process parameters--robotic spindle speed, robotic feed and robotic layered deburring thickness--are determined by cutting parameters--cutting speed, cutting feed and cutting depth--respectively. Among them, the robotic layered deburring thickness (i.e., cutting depth) planning and the robotic deburring tool location (position and orientation) planning are presented in the proposed robotic deburring tool path planning method in Section 3. In this section, issues to consider here pertain, mostly, to the adjustment control for robot manipulator deburring process parameters, that is robotic spindle speed and robotic feed, through a proposed robotic deburring process parameter control method. Some classical control methods, such as proportional-integral-derivative (PID) control, which have been studied and practiced by broad researches, are very effective solutions for uncomplicated linear time-invariant systems [49; 50; 51]. In addition, modern control theory, such as sliding mode control, based on state variables has also been widely used to solve linear or nonlinear, and time-invariant or time-varying multi-input multi-output (MIMO) systems [52; 53; 54]. Although this kind of classical and modern control theory can overcome some internal disturbances of the control system, nevertheless, it is neither sufficient to ensure the stability of robotic deburring process in a robust enough way in real time, nor able to cope with environmental uncertainties. One goal of this article is to find a way of controlling the robotic deburring contact forces while maintaining constant cutting speed and cutting force of the robot manipulator presented earlier. In particular, this is critical when the interaction between the robot manipulator and deburring workpiece environment is of concern. Because the fuzzy control with the ontological basis of fuzzy logic and fuzzy reasoning has the advantage of requiring neither the knowledge of the model structure nor the model parameters, it is strongly adaptive and highly robust to nonlinearity and variations of process parameters. Also, it can give fast response, effective noise suppression, and a better control effects when the model structure changes greatly. Therefore, related researches and applications based on fuzzy control have been favored by many scholars [55; 56; 57; 58]. In this article, the process of the adjustment control for robot manipulator deburring process parameters (i.e., robotic spindle speed and robotic feed) has the characteristics of nonlinearity, noise and tight coupling between control loops, which cannot be solved sufficiently by classical and modern control methods such as PID-type controllers.