Modelling and simulation for underwater hovering control based on ballast tank

Chen, Ying; Xu, Guohua; Wang, Guanxue; Liu, Gang; Zhang, Wei

doi:10.1109/usys.2016.7893919

Cited by 3 publications

(5 citation statements)

References 9 publications

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“…Lemma 2. For the prediction Equation (18), if the adaption rate T s is chosen to satisfy (20), and if there exists a time τ such that the truncation function ||x τ || ∞ is bounded, then the prediction error || xτ || ∞ can be systematically reduced both in transient and steady states by reducing the adaption rate T s .…”

Section: Stability Analysismentioning

confidence: 99%

“…The model reference adaptive control (MRAC) [18] can identify unknown parameters in the system and disturbance online [19]. According to the identified parameters, the control law is adjusted to eliminate the disturbance of the external environment to the controlled object [20,21], so that the output of the closed-loop system of the controlled model can follow the output of the ideal reference model, and the anti-disturbance ability of the system is improved [22]. In addition, Sedghi et al proposed an adaptive robust control method for the AUV with saturated inputs and uncertainties [23].…”

Section: Introductionmentioning

confidence: 99%

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Research on L1 Adaptive Control of Autonomous Underwater Vehicles with X-Rudder

Yuan,

She,

Zhang

et al. 2023

JMSE

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This study focuses on addressing the the coupling problem of the vertical and horizontal plane of an autonomous underwater vehicle (AUV) with an X-rudder. To guarantee the steering performance of the AUV, a depth and course control algorithm based on an L1 adaptive control algorithm (L1AC) is proposed. Firstly, the linear quadratic regulator (LQR) is designed on the basis of an AUV vertical and horizontal linear model, and the system has optimal control quality for both of the nominal vertical and horizontal models. Secondly, the nonlinear state predictor, disturbance estimator, and adaptive controller are designed separately, which is used for the compensation of the uncertainty and disturbance of the AUV dynamic. Finally, the rudder angle allocation algorithm is designed to realize the rudder angle command of the cross rudder to the X-rudder. The simulation and experiment results show that the adaptive control algorithm proposed in this paper can effectively control AUV to complete high-performance course and depth control. Based on the experiments, the prospects and shortcomings of the L1AC, LQR and MRAC algorithm in AUV control are compared and analyzed.

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Section: Stability Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Research on L1 Adaptive Control of Autonomous Underwater Vehicles with X-Rudder

Yuan,

She,

Zhang

et al. 2023

JMSE

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“…However, for large underwater vehicles such as manned submarines, the traditional hover control system is completed by hydraulic pumps and ballast tanks, and auxiliary thrusters is redundant, inevitably resulting in radiated noise. Ballast water tank specially designed for hovering, mainly located near the center of mass along the length of the submarine, see [13]. In addition, there are other novel methods of submarine hover depth control.…”

Section: Introductionmentioning

confidence: 99%

“…The paper [12] discusses fault-tolerant control of a hovering underwater vehicle with four horizontal thrusters and two vertical thrusters. Besides, meaningful explorations have been carried out on AUV hover depth control, including hover motion modeling and simulation ( [13], [14], [15], [16]), test platform construction ( [17], [18]), high-performance control algorithm( [7], [8]), etc.…”

Section: Introductionmentioning

confidence: 99%

Research on the Heading Control of Underwater Vehicle Under Hover Condition

et al. 2020

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A guidance and control algorithm for the heading control of a large underwater vehicle in hover state is proposed. The complexity of the flow field makes it difficult to build an accurate mathematical model for heading control under hover condition. Furthermore, the turning motion in the hover state causes additional vertical hydrodynamic and pitching moments which may affect the control performance of depth and pitching, and even bring safety problems. An H ∞ synthesis method is proposed, in which guidance weighting function is designed for the heading control constraints, sensitivity weighting function for the tracking performance requirements, and uncertainty weighting function for modeling error. Firstly, the hydrodynamic characteristics and constraints of hover and steering are analyzed, and the mathematical model is established. Secondly, based on the analysis of the affection of steering motion on depth and trim state, a control strategy is proposed to suppress interference by setting steering speed and limiting acceleration, which improves the safety of the control algorithm. And then, a H ∞ robust control algorithm based on three kinds of weighting function is designed. Finally, the method is simulated by using submarine model and validated by underwater vehicle experiment.The research in this paper has potential application value for safety and low noise performance for the control of large underwater platform and manned submarines.

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“…For the rest of parameters,p atm denotes atmospheric pressure, z f and x f are the coordinates of flood port, readers may also referred to the study by Chen et al 25 to get more specific deduction. For regular shape ballast tank, solve the following derivative equations to obtain the current water column height…”

mentioning

confidence: 99%

Hovering control of submarine based on L1 adaptive theory via ballast tanks

Chen

Wang

et al. 2017

International Journal of Advanced Robotic Systems

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This article proposed a novel method for submarine hovering control implement by ballast tanks based on L1 adaptive theory. The ballast tanks are able to provide submerge/emerge force by let in/out ballast tank water, and therefore adjust submarine position and altitude when low-speed maneuver largely limits rudder effect. After formulate and analysis models of ballast tanks as well as submarine dynamic, control scheme is determined as cascaded controller system. L1 adaptive theory is adopted for outer loop control, to deal with the nonlinearity and uncertainties of model, as well as environmental disturbance in hovering condition for the first time. Robustness of control system is tested through simulations based on Simscape. Large impact force is exerted on submarine to simulate missile launching and test restoring ability of ballast tanks control. Simulation results demonstrated that the submarine is able to maneuver and response precisely, despite of sudden impact.

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Modelling and simulation for underwater hovering control based on ballast tank

Cited by 3 publications

References 9 publications

Research on L1 Adaptive Control of Autonomous Underwater Vehicles with X-Rudder

Research on L1 Adaptive Control of Autonomous Underwater Vehicles with X-Rudder

Research on the Heading Control of Underwater Vehicle Under Hover Condition

Hovering control of submarine based on L1 adaptive theory via ballast tanks

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