Robust control of an underactuated AUV

Cutipa-Luque, Juan C.; Donha, Décio Crisol; Dantas, João Lucas Dozzi; Oliveira, Lucas Machado de; Barros, Ettore A. de

doi:10.3182/20120919-3-it-2046.00024

Cited by 8 publications

(9 citation statements)

References 5 publications

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“… The fourth stage presents the

{{\rm{ {\mathcal H} }}}_{\infty }

mixed sensitivity control approach for the linearized LTI system according to the two‐port diagram presented in the last stage. In modern control theory, a usual approach to characterize the two‐port closed‐loop performance objectives is the measurement of transfer matrices, relating exogenous inputs and controlled variables (exogenous outputs), using different matrix norms [5]. These norms indicate how large the gain of the system is under certain classes of input signals.…”

Section: Methodsmentioning

confidence: 99%

Robust control design on Scilab: Hybrid remotely operated vehicle

Roque‐Quispe,

Alvarez‐Quispe,

Yanyachi

et al. 2023

Comp Applic In Engineering

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The goal of this work is to demonstrate the advanced features of Scilab/Xcos software in the process of designing robust controllers and to validate them numerically by a multivariable system with high coupled dynamics; it is a hybrid remotely operated vehicle (HROV). The methodology presents five steps which are the nonlinear model representation, the model linearization, the building of augmented plants, the synthesis of robust controllers through the optimization algorithms, and the plotting of the results. Linear models can be obtained straightforwardly at many operation points. The robust controllers are synthesized using the mixed sensitivity approach and tested in Scilab script and in the Xcos block diagram interface. The surge and yaw rate vehicle dynamics are controlled by a centralized controller; obtaining a good settling time, of less than 14 s, without overshooting and mitigating the coupling dynamics. Moreover, the good shaping in sensitivity and complementary sensitivity indicates robustness in performance and stability for the HROV. The proposed methodology includes time and frequency domain analysis, among other advanced features, to overcome the need for commercial software.

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“… The fourth stage presents the

{{\rm{ {\mathcal H} }}}_{\infty }

Section: Methodsmentioning

confidence: 99%

Robust control design on Scilab: Hybrid remotely operated vehicle

Roque‐Quispe,

Alvarez‐Quispe,

Yanyachi

et al. 2023

Comp Applic In Engineering

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“…A closed loop matrix T zw is measured using H ∞ norm to guarantee good performance and stability [19], [6]:…”

Section: Edson-j Robust Controlmentioning

confidence: 99%

“…The H ∞ mixed sensitivity approach was formally used in former work to control an autonomous underwater vehicle [6]. In this paper, the authors uses the same approach applied to the EDSON-J USV where the input pre-filter and weighting matrices R, W i , W d and W n are identity matrices of I 2×2 .…”

Section: Edson-j Robust Controlmentioning

confidence: 99%

“…There are many robust control strategies applied to these unmanned maritime vehicles. An H ∞ robust mixed sensitivity approach is applied to an autonomous underwater vehicle in [6], an H 2 robust control approach is applied to an autonomous underwater vehicle (AUV) characterized by output disturbances and time delay in [7], a nonlinear robust control is applied to other unmanned maritime vehicle for hull ship inspection in [8], and another modified robust control algorithm for an USV is proposed in [9].…”

Section: Introductionmentioning

confidence: 99%

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Robust Control and Fuzzy Logic Guidance for an Unmanned Surface Vehicle

Huayna-Aguilar

Cutipa-Luque²,

Yanyachi³

2020

IJACSA

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This work deals with guidance and control of an unmanned surface vehicle which has the mission to monitor autonomously the water quality condition in Peruvian sea onshore. The vehicle is a catamaran class with two slender bodies propelled by two electric thrusts in differential and common modes in order to maneuver in surge and in yaw directions. A multivariable control approach is proposed in order to control these two variables and a fuzzy logic-based guidance tracks predefined trajectories at the sea surface. The conjunction between robust control and guidance algorithms is validated numerically and the results show good stability and performance despite the presence of disturbance, noise sensors and model uncertainties.

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“…A diving-control design, based on Lyapunov theory and backstepping techniques, is proposed to control an AUV in [5]. In [2], a robust H ∞ control approach, based on a two-degrees-of-freedom controller, was developed for the control of AUV. Recently, a nonlinear control scheme based on the energy-shaping (ES) principle and state error port-controlled Hamiltonian (PCH) systems has been proposed in [8].…”

Section: Introductionmentioning

confidence: 99%

Decoupled Control of a Twin Hull-Based Unmanned Surface Vehicle Using a Linear Parameter Varying Approach

Chnib

Sename

Ferrante

et al. 2022

Lecture Notes in Mechanical Engineering

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This paper presents a decoupled control of a twin hull-based Unmanned Surface Vehicle EDSON-J, using the H ∞ approach for Linear Parameter Varying (LPV) polytopic systems. This method was adapted in order to guarantee robust stability and performance regarding the important non-linearities and the uncertainties on the hydrodynamics parameters. After the presentation of the nonlinear model and the decoupled model of the USV considered for the study, an LPV model was built, regarding the mass of the vehicle as unique varying parameter. Then the methodology of the control law applied is exposed and simulation results are presented. A comparison with the LTI/H ∞ approach will show the interest of the method in terms of performance.

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Robust control of an underactuated AUV

Cited by 8 publications

References 5 publications

Robust control design on Scilab: Hybrid remotely operated vehicle

Robust control design on Scilab: Hybrid remotely operated vehicle

Robust Control and Fuzzy Logic Guidance for an Unmanned Surface Vehicle

Decoupled Control of a Twin Hull-Based Unmanned Surface Vehicle Using a Linear Parameter Varying Approach

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