| Title: | Ammar H.H., Azar A.T., Tembi T.D., Tony K., Sosa A. (2018) Design and Implementation of Fuzzy PID Controller into Multi Agent Smart Library System Prototype. In: Hassanien A., Tolba M., Elhoseny M., Mostafa M. (eds) The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2018). AMLTA 2018. Advances in Intelligent Systems and Computing, vol 723, pp. 127-137 Springer, Cham |
| Authors: | Not Available |
| Year: | 2018 |
| Keywords: | Not Available |
| Journal: | Advances in Intelligent Systems and Computing |
| Volume: | 723 |
| Issue: | Not Available |
| Pages: | 127-137 |
| Publisher: | Springer |
| Local/International: | International |
| Paper Link: | |
| Full paper | Not Available |
| Supplementary materials | Not Available |
| Abstract: |
This paper compares the performance of four different controllers implemented on two multi agent robots to stabilize its motion from one station to another during delivery tasks. The controllers are; multi-position controller, PID controller, fuzzy logic controller and fuzzy-PID controller. The aim of this paper is to control the mobile robot robustly to arrive its target destination. The robots and station coordinates are recognized using machine vision system and all programming is carried out in LabVIEW. The paper compares the transient response and steady state error of each of controller and experimental results show that the Fuzzy-PID controller produced the best performance and good trajectory of robot from its current position to its target position. It had a better convergence rate when compared with other controllers like PID and Fuzzy logic controllers. This paper compares the performance of four different controllers implemented on two multi agent robots to stabilize its motion from one station to another during delivery tasks. The controllers are; multi-position controller, PID controller, fuzzy logic controller and fuzzy-PID controller. The aim of this paper is to control the mobile robot robustly to arrive its target destination. The robots and station coordinates are recognized using machine vision system and all programming is carried out in LabVIEW. The paper compares the transient response and steady state error of each of controller and experimental results show that the Fuzzy-PID controller produced the best performance and good trajectory of robot from its current position to its target position. It had a better convergence rate when compared with other controllers like PID and Fuzzy logic controllers. |
