Content area
This study presents the modeling and control of the unmanned surface vehicle (USV) SABALO. Two models were built, one based on a transfer function matrix and another based on state variables, and from these models, two control strategies were developed. The first strategy is based on independent Proportional-Integral/Proportional-Derivative (PI/PD) controllers complemented by a decoupling system, and the second strategy is based on state variable feedback. The two control strategies were evaluated and contrasted. Results demonstrated that the decoupler effectively eliminated variable interaction, enhancing stability in straight trajectories and directional changes. Meanwhile, state feedback control demonstrated markedly faster response times and superior precision, accompanied by higher energy consumption. The study concludes that both strategies are effective, but their suitability depends on the mission. The decoupler could be ideal for energy-efficient, long-duration operations, while state feedback could be appropriate for dynamic environments requiring rapid maneuvers.
Details
Robust control;
Deep learning;
Adaptability;
Parameter identification;
Decoupling;
Surface vehicles;
Energy efficiency;
Feedback;
Unmanned vehicles;
Control systems;
Systems stability;
State feedback;
Proportional derivative;
Energy consumption;
Transfer functions;
Efficiency;
Vehicles;
Machine learning;
Artificial intelligence;
Proportional integral;
Neural networks;
State variable;
Methods;
Surveillance;
Feedback control;
Parameter estimation
; Soto-Diaz Roosvel 2
; Gutierrez-Martinez, Carlos Andres 1
; Jimenez-Vargas, Jose Fernando 3
; Jiménez-Cabas, Javier 4
; Escorcía-Gutierrez, Jose 4
1 Escuela Naval de Cadetes “Almirante Padilla” (ENAP), Cartagena de Indias 130001, Colombia; [email protected] (A.L.-A.); [email protected] (C.A.G.-M.)
2 Biomedical Engineering Program, Universidad Simón Bolívar, Barranquilla 080002, Colombia
3 Department of Electrical and Electronic Engineering, Universidad de Los Andes, Bogotá 111711, Colombia; [email protected]
4 Department of Computational Science and Electronics, Universidad de la Costa (CUC), Barranquilla 080002, Colombia; [email protected]