Unmanned Surface Vehicle (USV) is an unmanned ship that is controlled through a remote control system (manual) or automatic control system (autopilot), move due to the thrust force from thruster machine and can turning due to the deflection angle of rudder. The USV path planning system becomes an important task so that the ship can make the global trajectory with the minimum travel distance according to the desired navigation while at the same able to avoid various obstacles from local dangerous situations that have the potential for collisions. To be able to do dynamic USV path planning, the Genetic Algorithm method with a sliding curve guidance system and PID MRAC controller is used. The use of this method gives smooth ship track performance with shortest distance in a 400x400 square meter map with static and dynamic obstacles. In a dynamic environment, the path replanning process that takes place in 0,98 seconds is able to find a new path that does not collide the obstacles. For the purposes of algorithm validation, the simulation is performed using MATLAB software with real ship parameters of 6 meters length USV.

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The Autopilot system for Unmanned Surface Vehicle (USV) can be applied by Sliding Mode Control which is a high frequency switching based control method and has discontinuous control action causing chattering on the system. Therefore, the Sliding Mode Control with natural control signal using a PID controller structure is applied to the USV. By using Sliding Mode Control, USV is expected to move accurately from the expected waypoint without any chattering on the system. The stability of the whole loop of system regulation is ensured using the Lyapunov stability function. The simulation results for autopilot system validate that the control parameters fit the time constant controller design specification and have zero steady-state errors. Further, autopilot system with waypoint navigation relatively generates small Mean Square Error (MSE) of waypoint.