Command Filtered Backstepping Design in MOOS-IvP Helm Framework for Trajectory Tracking of USVs Vladimir Djapic 2 and Dula Nad 1,2 1 University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, Croatia. 2 Work performed while at NATO Undersea Research Centre (NURC), La Spezia, Italy. 2 NATO Undersea Research Centre (NURC), La Spezia, Italy. Abstract— This article describes design and simulation im- plementation of a nonlinear controller for an underactuated surface vehicle. The controller is designed using a command fil- tered backstepping (CFBS) approach. Theoretical background for controller design is given in the first part of this article. This nonlinear controller can be used for accurate tracking of a complex trajectory, for example a circular trajectory. Second part of the article focuses on implementation in the MOOS-IvP framework. This framework allows for flexibility in control and mission planning. Guidance is covered by the MOOS- IvP implementation of the controller while the COTS autopilot handles low-level control. The control performance is verified in simulation which confirms arbitrarily small tracking error. This paper presents simulation results where external disturbances, such currents, are also simulated and compensated for. I. I NTRODUCTION Different approaches for motion control of autonomous vehicles (land, air, surface, and underwater robots) have been analyzed in recent past [11], [2]. The literature, generally, distinguishes among two different motion control problems: 1) path following - where the robot is required to converge to and follow a path where only spatial convergence is necessary without any temporal requirement, and 2) path/trajectory tracking - where the robot is required to track a time parametrized reference with temporal requirement. Recently, the concept of path maneuvering was introduced in order to combine the properties of trajectory tracking and path following [2]. This problem is solved for the fully actuated systems and solutions can be found in the nonlinear control textbooks, such as in [8], pages 540-544. Even though fully actuated systems are able to independently control the motion of all their DOFs simultaneously they are impractical for vehicles moving at speeds above 1.5 - 2 m s since they would usually expend an unnecessary amount of energy for control action [2]. The authors in [2] have addressed the subject of straight-line high speed target tracking for unmanned surface vehicles (USVs) while here, in addition to straight-line tracking, we show the tracking of the arbitrary, smooth, complex trajectories with a USV. Thus, we focus on trajectory tracking which forces the system to follow a given point as it moves along an operator (or sensor) defined trajectory. The controller generates yaw rate and velocity commands. The velocity and yaw rate controller generates the force and torque commands to achieve the yaw rate and velocity commands. Unmanned Surface Vehicles (USVs) are being consid- ered for the following missions: Mine Countermeasures (MCM), Anti-Submarine Warfare (ASW), and Maritime Se- curity (MS). NURC’s USV Mandarina is currently used by the MCM and Port Protection Programs [10]. For some searching applications it is a requirement for a vehicle to accurately follow a specific trajectory, make accurate turns and continue to follow the next specified trajectory. Many of these missions require the vehicle to function in complex Nada cluttered environments. The researchers at the Mobile Robotics Research Group at Oxford University, the Computer Science and Artificial Intelligence Lab and Dept. of Mechanical Eng. at MIT, and the Naval Undersea Warfare Center in Newport Rhode Island (NUWC-NPT) have developed the MOOS-IvP Autonomy Architecture [9], [1]. MOOS stands for “Mission Oriented Operating Suite”, and IvP stands for “Interval Program- ming”. This architecture consists of an open-source dis- tributed autonomy architecture and an approach to behavior based control of autonomous vehicles that allows reactive control in complex environments with multiple constraints. Low-level control tasks such as navigation, depth keeping and vehicle safety are assigned to the AUV main vehicle computer, all high-level control inputs are derived from a separate vehicle payload computer running the MIT MOOS- IvP system. Our goal is to use the existing MOOS open- source features and its ability to dynamically react to its environment in order to increase the functional autonomy of the existing autonomous vehicles. One such an example is described in Section IX where an output from a sonar sensor is used to direct the robot to change its trajectory as the new mission plan is developed onboard the vehicle in response to the sensor data. In addition, this architecture enabled us to implement an advanced nonlinear controller based on CFBS onboard of the NURC’s Mandarina USV. The program executing mission planning and control algorithms for stable trajectory tracking is interfaced with the COTS autopilot SPECTRE made by H-Scientific Ltd. The paper is organized as follows. Section II introduces the problem of trajectory tracking control for a USV. Section II defines the USV dynamics. Section III outlines the control law signals. Sections IV, V, VI, and VII present a detailed 2010 American Control Conference Marriott Waterfront, Baltimore, MD, USA June 30-July 02, 2010 FrB15.3 978-1-4244-7427-1/10/$26.00 ©2010 AACC 5997