TY - GEN
T1 - Design of Radial Basis Function Network and State-Dependent LQT for Path Planning and Tracking of Autonomous Underwater Vehicle (AUV) to Intercept A Moving Target
AU - Huda, Thorikul
AU - Amalia, Rahma Nur
AU - Astrowulan, Katjuk
AU - Sulisetyono, Aries
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/12
Y1 - 2018/12
N2 - The autonomous underwater vehicle (AUV) has been implemented in various fields, such as to monitor deep and long-distance sea conditions, underwater mapping, long time surveys, neutralization of seabed mines, and military applications. In the military field, one of the AUV applications is a torpedo. A torpedo has a mission to go to a given target, frequently a moving target. To meet this objective, the torpedo must have a detection system to find out the target position. However, it is impossible to be implemented because of the limited space and energy available in a torpedo. Therefore, it requires a reliable system to predict a moving target, to form the path to hit the target, avoid obstacles in the path, and the controller that can follow the path determined by the path planning algorithm. Therefore, this study developed various scenarios to simulate the conditions. The results show that the radial base function network can form a path that is free from obstacles and able to form a path that can intercept a moving target while the state-dependent LQT algorithm is able to perform a path tracking properly so that the AUV can reach a predetermined target. With the speed of 1.4 m/s, the AUV could intercept a moving target with the speed of 0.2 m/s and the face angle of -1.7 radians at t = 75.1 seconds. In another scenario, the AUV intercepted a moving target with the speed of 0.5 m/s and the face angle of -1.18 radians at t = 73.2 seconds.
AB - The autonomous underwater vehicle (AUV) has been implemented in various fields, such as to monitor deep and long-distance sea conditions, underwater mapping, long time surveys, neutralization of seabed mines, and military applications. In the military field, one of the AUV applications is a torpedo. A torpedo has a mission to go to a given target, frequently a moving target. To meet this objective, the torpedo must have a detection system to find out the target position. However, it is impossible to be implemented because of the limited space and energy available in a torpedo. Therefore, it requires a reliable system to predict a moving target, to form the path to hit the target, avoid obstacles in the path, and the controller that can follow the path determined by the path planning algorithm. Therefore, this study developed various scenarios to simulate the conditions. The results show that the radial base function network can form a path that is free from obstacles and able to form a path that can intercept a moving target while the state-dependent LQT algorithm is able to perform a path tracking properly so that the AUV can reach a predetermined target. With the speed of 1.4 m/s, the AUV could intercept a moving target with the speed of 0.2 m/s and the face angle of -1.7 radians at t = 75.1 seconds. In another scenario, the AUV intercepted a moving target with the speed of 0.5 m/s and the face angle of -1.18 radians at t = 73.2 seconds.
KW - AUV
KW - Path Planning
KW - Path Tracking
UR - http://www.scopus.com/inward/record.url?scp=85085247389&partnerID=8YFLogxK
U2 - 10.1109/BICAME45512.2018.1570497166
DO - 10.1109/BICAME45512.2018.1570497166
M3 - Conference contribution
AN - SCOPUS:85085247389
T3 - 2018 2nd Borneo International Conference on Applied Mathematics and Engineering, BICAME 2018
SP - 343
EP - 348
BT - 2018 2nd Borneo International Conference on Applied Mathematics and Engineering, BICAME 2018
A2 - Wibowo, Ferry Wahyu
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd Borneo International Conference on Applied Mathematics and Engineering, BICAME 2018
Y2 - 10 December 2018
ER -