TY - GEN
T1 - A fuzzy self-adaptive PID tracking control of autonomous surface vehicle
AU - Majid, M. H.A.
AU - Arshad, M. R.
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2016/5/31
Y1 - 2016/5/31
N2 - Proportional Integral Derivative (PID) controller is a conventional controller, which is widely used in industrial control system. In this paper, a PID control system is used for path tracking of an autonomous surface vehicle (ASV). The PID controller is selected because it is easy to implement as an embedded controller and practically easy to understand compared to other control methods. However, to improve the response of the PID controller, a fuzzy inference system (FIS) is used to tune the controller parameters based on a set of control rules. Three parallel fuzzy self-adaptive PID controllers is used to track the desired position and angular orientation of the ASV along the surge, sway and yaw directions. Through kinematic modeling of the ASV, the desired model for tracking the desired path could be obtained. Simulation results show that the Fuzzy-PID controller performs better compared to the ordinary PID controller in term of improving settling time and reducing overshoot of the control signal.
AB - Proportional Integral Derivative (PID) controller is a conventional controller, which is widely used in industrial control system. In this paper, a PID control system is used for path tracking of an autonomous surface vehicle (ASV). The PID controller is selected because it is easy to implement as an embedded controller and practically easy to understand compared to other control methods. However, to improve the response of the PID controller, a fuzzy inference system (FIS) is used to tune the controller parameters based on a set of control rules. Three parallel fuzzy self-adaptive PID controllers is used to track the desired position and angular orientation of the ASV along the surge, sway and yaw directions. Through kinematic modeling of the ASV, the desired model for tracking the desired path could be obtained. Simulation results show that the Fuzzy-PID controller performs better compared to the ordinary PID controller in term of improving settling time and reducing overshoot of the control signal.
KW - adaptive control
KW - autonomous surface vehicle
KW - fuzzy inference system
KW - fuzzy PID
KW - tracking control
UR - http://www.scopus.com/inward/record.url?scp=84978924574&partnerID=8YFLogxK
U2 - 10.1109/ICCSCE.2015.7482229
DO - 10.1109/ICCSCE.2015.7482229
M3 - Conference Proceeding
AN - SCOPUS:84978924574
T3 - Proceedings - 5th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2015
SP - 458
EP - 463
BT - Proceedings - 5th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2015
Y2 - 27 November 2015 through 29 November 2015
ER -