Grasshopper Optimization Algorithm-based Adaptive Control of Extruder Pendulum System in 3D Printer

Abstract

Additive manufacturing technology has increased the use of three-dimensional (3D) printers in many sectors, especially in engineering and medicine. Today, 3D printers, which are widely used in the fields of manufacturing and prototyping, can produce models that are modeled in a computer environment or scanned in three dimensions very quickly and efficiently compared to traditional production methods. Models with complex geometries, which require the use of filaments of more than one type and color, which are difficult to produce with traditional methods, can be printed with 3D printers with an extruder pendulum system. The accuracy of the printed models is directly related to the effective control of the extruder pendulum system in the 3D printer. In this study, the position control of the extruder pendulum system, which allows to print models with filaments of different types and colors, is carried out with an optimization-based adaptive controller. The parameters of the adaptive Proportional-Integral-Derivative (PID) controller used in the study are estimated by Grasshopper Optimization Algorithm (GOA), which has a high convergence rate and low parameter complexity compared to other optimization algorithms. The performance of the proposed GOA-based adaptive PID controller is verified with the help of Integral of Time multiplied Squared Error (ITSE), one of the performance metrics. The performance of the GOA-based adaptive PID controller proposed for the control of the extruder pendulum system is compared with the Ziegler-Nichols (ZN) and Genetic Algorithm (GA) based PID controller performances. In determining the performance of the controllers used in the study, the settling time, overshoot and rise time design criteria in the step response of the system are considered. The proposed controller is embedded in the controller card on the 3D printer with the extruder pendulum system and 3D models are printed. The experimental results show that the proposed GOA-based adaptive controller improves the design criteria such as closed-loop settling time, overshoot and rise time. In addition, it is seen that the total error, especially the surface error, is minimized in 3D models printed with the proposed controller.