2014
DOI: 10.1109/tcst.2013.2271505
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Trajectory Tracking of Underactuated Surface Vessels: A Linear Algebra Approach

Abstract: This brief presents the design of a controller that allows an underactuated vessel to track a reference trajectory in the x − y plane. A trajectory tracking controller designed originally for robotic systems is applied for underactuated surface ships. Such a model is represented by numerical methods and, from this approach, the control actions for an optimal operation of the system are obtained. Its main advantage is that the condition for the tracking error tends to zero, and the calculation of control action… Show more

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Cited by 115 publications
(71 citation statements)
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References 18 publications
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“…An adaptive supervisory control algorithm that combines a switching method with an iterative Lyapunov technique is proposed in [24]; a stable adaptive neural network controller combined with a backstepping technique and Lyapunov theory is designed in [25]; a state feedback adaptive backstepping fuzzy logic controller is addressed in [27]; a hybrid sliding-mode control strategy based on a bioinspired model is developed in [24]; a suboptimal robust control methodology is presented in [30]; and a hybrid control algorithm based on neural network and dynamic surface control is presented in both [28] and [33]. Moreover, some linear algebra and other methodologies are formulated in [34][35][36][37][38][39][40][41][42]. Based on searching for conditions under which a system of linear equations has an exact solution, linear algebra methodologies are proposed in both [34] and [35].…”
Section: Introductionmentioning
confidence: 99%
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“…An adaptive supervisory control algorithm that combines a switching method with an iterative Lyapunov technique is proposed in [24]; a stable adaptive neural network controller combined with a backstepping technique and Lyapunov theory is designed in [25]; a state feedback adaptive backstepping fuzzy logic controller is addressed in [27]; a hybrid sliding-mode control strategy based on a bioinspired model is developed in [24]; a suboptimal robust control methodology is presented in [30]; and a hybrid control algorithm based on neural network and dynamic surface control is presented in both [28] and [33]. Moreover, some linear algebra and other methodologies are formulated in [34][35][36][37][38][39][40][41][42]. Based on searching for conditions under which a system of linear equations has an exact solution, linear algebra methodologies are proposed in both [34] and [35].…”
Section: Introductionmentioning
confidence: 99%
“…Moreover, some linear algebra and other methodologies are formulated in [34][35][36][37][38][39][40][41][42]. Based on searching for conditions under which a system of linear equations has an exact solution, linear algebra methodologies are proposed in both [34] and [35]. A global k-exponential convergence tracking controller is designed in [37]; an output feedback controller combined with a state feedback controller and a reducedorder observer is presented in [39]; a novel finite-time switching trajectory-tracking controller is developed in [41]; and a nonlinear predictive control technique is proposed in [42] for trajectory-tracking control of an USV with state and input constraints.…”
Section: Introductionmentioning
confidence: 99%
“…In [10], the neural network feedback-feedforward compensator is used to for estimation of the uncertainty nonlinear parts of the system where a single layer neural network is used to obtain the adaptive signal online. A trajectory tracking controller design for an underactuated surface ship has been given in [11]. The control system design is based on a linear algebra method and numerical method.…”
Section: Introductionmentioning
confidence: 99%
“…The controller is usually designed to achieve the two tasks. The first task is a tracking controller designed to make the controlled plan follow a reference trajectory [14,21]. The second task is an anti-swing controller [2,23].…”
Section: Introductionmentioning
confidence: 99%