Application of linearization via state feedback to heading control for Autonomous Underwater Vehicle

Cheng, Xiang-qin; Yan, Zheping; Bian, Xinqian; Zhang, Jiajia

doi:10.1109/icma.2008.4798802

Cited by 10 publications

(6 citation statements)

References 2 publications

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“…In [29], the authors developed a FL controller for an UV with a linear Proportional-Derivative compensator for stabilization. The authors in [30,31] implemented heading controllers using a closed-loop gain shaping algorithm and a fault tolerant heading control system using the method of input-output FL, respectively. The main principle with FL is the transformation of the nonlinear dynamics of the system into a linear system:trueη¨=an trueν˙=ab to which traditional control methods (e.g., Linear Quadratic Regulator, pole-placement) can be applied [27].…”

Section: Control System Designmentioning

confidence: 99%

Nonlinear Attitude Control of a Spherical Underwater Vehicle

Fernández

Milosevic

Domínguez

et al. 2019

Sensors

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In this work, we present the design, implementation, and testing of an attitude control system based on State Feedback Linearization (FL) of a prototype spherical underwater vehicle. The vehicle is characterized by a manifold design thruster configuration for both locomotion and maneuvering, as well as on a novel pendulum-based passive pitch control mechanism. First, the mechanical design and onboard electronics set up of the spherically shaped hull are introduced. Afterward, a high-fidelity dynamic model of the system is derived for a 6 degree-of-freedom (DOF) underwater vehicle, followed by several experiments that have been performed in a controlled environment to compare the performance of the proposed control method to that of a baseline Proportional-Integral-Derivative (PID) controller. Experimental results demonstrate that while both controllers were able to perform the specified maneuvers, the FL controller outperforms the PID in terms of precision and time response.

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Section: Control System Designmentioning

confidence: 99%

Nonlinear Attitude Control of a Spherical Underwater Vehicle

Fernández

Milosevic

Domínguez

et al. 2019

Sensors

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“…In underwater vehicle autopilot design, the existing literature ranges from the application of PID and classical control [3] techniques to the application of modern techniques such as H-infinite [4], sliding model control [5][6][7][8][9][10], fuzzy control [11][12][13][14], neural networks [15], output feedback [16], linearization via state feedback [17], adaptive control [18], predictive control [19,20], and backstepping control [21,22]. These control methods provide good results in the cited references but are-in most cases-restricted to a certain operational condition.…”

Section: Introductionmentioning

confidence: 99%

Iterative Self-Tuning Minimum Variance Control of a Nonlinear Autonomous Underwater Vehicle Maneuvering Model

2021

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This paper addresses the problem of control design for a nonlinear maneuvering model of an autonomous underwater vehicle. The control algorithm is based on an iteration technique that approximates the original nonlinear model by a sequence of linear time-varying equations equivalent to the original nonlinear problem and a self-tuning control method so that the controller is designed at each time point on the interval for trajectory tracking and heading angle control. This work makes use of self-tuning minimum variance principles. The benefit of this approach is that the nonlinearities and couplings of the system are preserved, unlike in the cases of control design based on linearized systems, reducing in this manner the uncertainty in the model and increasing the robustness of the controller. The simulations here presented use a torpedo-shaped underwater vehicle model and show the good performance of the controller and accurate tracking for certain maneuvering cases.

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“…But it was just designed to deal with the negative effect caused by model uncertainty. Cheng designed a robust controller for the heading control of AUV is designed based on closed-loop gain shaping algorithm, however its performance is not so good when the velocity is changed [4].…”

Section: Introductionmentioning

confidence: 99%

Auto Disturbance Rejection Control System of Diving for an Underactuated AUV

Zhang

et al. 2011

2011 Fourth International Joint Conference on Computational Sciences and Optimization

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The diving control problem of an underactuated autonomous underwater vehicle (AUV) was addressed in this paper. In order to deal with the uncertainties and nonlinear dynamics, an auto-disturbance-rejection controller(ADRC) was introduced to guarantee the robustness and stability during diving. The simulation results demonstrated that this proposed controller was effective to eliminate the disturbances caused by vehicle's nonlinear and model uncertainty. Further more, the feasibility and practicability of the proposed method is verified by an experiment for the diving control in Lake.

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Application of linearization via state feedback to heading control for Autonomous Underwater Vehicle

Cited by 10 publications

References 2 publications

Nonlinear Attitude Control of a Spherical Underwater Vehicle

Nonlinear Attitude Control of a Spherical Underwater Vehicle

Iterative Self-Tuning Minimum Variance Control of a Nonlinear Autonomous Underwater Vehicle Maneuvering Model

Auto Disturbance Rejection Control System of Diving for an Underactuated AUV

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