Incorporating input saturation for underactuated surface vessel trajectory tracking control

Siramdasu, Yaswanth; Fahimi, Farbod

doi:10.1109/acc.2012.6314790

Cited by 8 publications

(3 citation statements)

References 20 publications

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“…Movahhed et al [20] used two sliding surfaces to determine the two propeller forces based on Lyapunov direct method and sliding mode scheme, where the parameter update laws were used to estimate uncertainties. Siramdasu and Fahimi [21] proposed a nonlinear model predictive controller (NMPC) for trajectory tracking of underactuated surface vessels, where NMPC is applied to calculate the future control inputs based on the present state variable by optimizing a cost function.…”

Section: Introductionmentioning

confidence: 99%

Trajectory tracking of underactuated surface vessels based on neural network and hierarchical sliding mode

2014

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Adaptive robust controllers are proposed for trajectory tracking and stabilization of underactuated surface vessels simultaneously in this paper. Hierarchical sliding mode is employed to deal with the underactuation of the model, and neural network is used as a tool for approximating unknown nonlinear function in the system; in this way, the robustness of the proposed controller is strengthened, and the chattering problem of sliding mode technique is relieved. The nonlinear damping terms of ship's model are considered which are neglected in many studies, and the time-varying disturbances are taken into account to test the robustness of the designed controllers. Stability is guaranteed by Lyapunov theorem, and the proof is given. Numerical simulations are implemented to demonstrate the effectiveness and the robustness of the designed controllers.

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Section: Introductionmentioning

confidence: 99%

Trajectory tracking of underactuated surface vessels based on neural network and hierarchical sliding mode

2014

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“…There have been a number of studies on the control of ships, boats, and USVs [10], using the sliding mode method, [11], integrator backstepping method [12], [13] and adaptive control [13], [14]. It is worth pointing out that several researchers recently attempted to use the model predictive control (MPC) method for the control of USVs and underwater robots [15]- [20]. Applying model predictive control technology for USVs is a promising choice as the combination of model dynamics and cost function minimization allows for minimal tuning of controller gains.…”

Section: Introductionmentioning

confidence: 99%

Design, Modeling, and Nonlinear Model Predictive Tracking Control of a Novel Autonomous Surface Vehicle

Wang

Mateos

Park

et al. 2018

2018 IEEE International Conference on Robotics and Automation (ICRA)

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In this paper, we present the design, modeling, and real-time nonlinear model predictive control (NMPC) of an autonomous robotic boat. The robot is easy to manufacture, highly maneuverable, and capable of accurate trajectory tracking in both indoor and outdoor environments. In particular, a cross type four-thruster configuration is proposed for the robotic boat to produce efficient holonomic motions. The robot prototype is rapidly 3D-printed and then sealed by adhering several layers of fiberglass. To achieve accurate tracking control, we formulate an NMPC strategy for the four-controlinput boat with control input constraints, where the nonlinear dynamic model includes a Coriolis and centripetal matrix, the hydrodynamic added mass, and damping. By integrating "GPS" modules and an inertial measurement unit (IMU) into the robot, we demonstrate accurate trajectory tracking of the robotic boat along preplanned paths in both a swimming pool and a natural river. Furthermore, the code generation strategy employed in our paper yields a two order of magnitude improvement in the run time of the NMPC algorithm compared to similar systems. The robot is designed to form the basis for surface swarm robotics testbeds, on which collective algorithms for surface transportation and self-assembly of dynamic floating infrastructures can be assessed.

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“…A global tracking control method for underactuated ships with input and velocity constraints was developed based on backstepping and dynamic surface control in . In , a nonlinear model predictive controller for trajectory tracking of surface vessels was presented.…”

Section: Introductionmentioning

confidence: 99%

Stabilization And Tracking Of Underactuated Surface Vessels In Random Waves With Fin Based On Adaptive Hierarchical Sliding Mode Technique

Liu¹,

Zou²,

Hou³

2014

Asian Journal of Control

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Trajectory tracking and roll stabilization are both vital practices in ship motion control. Trajectory tracking is a kind of low-frequency control, while roll stabilization by means of fins is a kind of high-frequency control. However, they have been studied separately previously; most tracking control of underactuated surface vessels in the previous studies do not account for roll stabilization by means of fins. In reality, however, they are an integral system. In this paper, a simple control strategy is proposed to achieve trajectory tracking and fin roll stabilization simultaneously. Four degrees of freedom derived from a six degrees of freedom mathematical model of a surface vessel is considered, including surge, sway, roll and yaw. Surge force, roll moment and yaw moment are considered as control inputs, while position, yaw angle and roll angle are controlled. The number of control inputs is fewer than the outputs to be controlled. Therefore, we are dealing with an underactuated problem. An adaptive hierarchical sliding mode control technique is employed to deal with the underactuation. Stabilization of underactuated surface vessels is studied as a special case. Random waves are applied to test the robustness of the designed controllers. Lyapunov stability theory is used to show the stability of closed-loop system. The simulation results verify the effectiveness of the proposed strategy.

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Incorporating input saturation for underactuated surface vessel trajectory tracking control

Cited by 8 publications

References 20 publications

Trajectory tracking of underactuated surface vessels based on neural network and hierarchical sliding mode

Trajectory tracking of underactuated surface vessels based on neural network and hierarchical sliding mode

Design, Modeling, and Nonlinear Model Predictive Tracking Control of a Novel Autonomous Surface Vehicle

Stabilization And Tracking Of Underactuated Surface Vessels In Random Waves With Fin Based On Adaptive Hierarchical Sliding Mode Technique

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