Adaptive robust sliding mode control of autonomous underwater glider with input constraints for persistent virtual mooring

Zhou, Hexiong; Wei, Zhaoyu; Zeng, Zheng; Yu, Caoyang; Yao, Baoquan; Lian, Lian

doi:10.1016/j.apor.2019.102027

Cited by 54 publications

(18 citation statements)

References 39 publications

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“…The major advantage of gliders over other drones is their low cost and high durability [3]; they have therefore become a powerful and widely used tool in the seas and oceans. According to studies on the development of research activities in the field of underwater gliders, topics such as feasibility of designing and developing an underwater gliders for various missions in maritime units, design of exterior body, implementation of automated control systems, design of propulsion systems [8][9][10], as well as diving and heaving, extracting and recording sea-level data, identifying and monitoring the operations environment [11], performing rescue operations and tracking systems are always a concern [4][5][6][7][8]. Heretofore many researchers have investigated the parameters affecting the dynamics of glider motions, some of which are listed below [9][10][11].…”

Section: A Bodymentioning

confidence: 99%

Experimental analysis on hydrodynamic coefficients of an underwater glider with spherical nose for dynamic modeling and motion simulation

et al. 2021

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In this paper, we present a study of an underwater glider with a cylindrical body, a conical end shape and a spherical nose with NACA0009 airfoil wings. In the experimental section, we investigate the hydrodynamic coefficients of drag and lift as well as the torque on the glider then analyze the launch velocity, launch angles, angular velocity, and displacement range as the main parameters for evaluating of motion dynamics. In the numerical section, we investigate the optimal performance of the glider using the meta-heuristic optimization method in order to find the path and range of motion of the moving mass and control of the sea glider, which is very important for navigation scope. To be specific, body and wings hydrodynamic coefficients are obtained in the velocity range of [0.2, 1] $$m/s$$ m / s ; According to the results, the drag coefficient increases with increasing velocity, while the lift coefficient increases up to velocity of $$0.8 m/s$$ 0.8 m / s , then decreases at velocity of $$1 m/s$$ 1 m / s . Also, the wing drag coefficient decreases with increasing velocity, while the wing lift coefficient increases with increasing velocity. In the next step, in order to calculate an optimum ratio between obtained depth and horizontal distance, the designed algorithm investigate the glider launch angle and finally, the 10 degrees launch angle is chosen as the optimum angle. Subsequently, the analysis performed on mass center displacement range shows that the oscillation interval $$[- 0.045, 0.085]$$ [ - 0.045 , 0.085 ] $$m$$ m is an optimum displacement domain.

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Section: A Bodymentioning

confidence: 99%

Experimental analysis on hydrodynamic coefficients of an underwater glider with spherical nose for dynamic modeling and motion simulation

et al. 2021

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“…Such assumption concerning thrust force limit is made often, for example, in the literature. 17,28 Assumption 2. The following inequality is assumed…”

Section: Controllermentioning

confidence: 99%

“…[2][3][4]6,8,[10][11][12]14,15 Various types of sliding mode control (SMC) algorithms were considered, among others, in the literature. 6,8,11,13,[15][16][17] However, different tracking strategies are successfully applied, for example, based on backstepping technique, 18 gain scheduling control theory, 19 bio-inspired neurodynamics approach, 20 so-called RISE algorithm 10 or control approach using an observer, 21 adaptive recurrent neurofuzzy control, 22 neural network control, 23 and an output feedback control, which use a vehicle model. 24 In the current literature, more other control algorithms can be found, for example, combination of fuzzy logic, genetic algorithm, and SMC, 25 model predictive control, 26 a method in which the port-Hamiltonian theory is applied, 5 combination of recurrent neural network and receding horizon optimization, 27 combination of SMC and backstepping, 14 and backstepping active disturbance rejection control.…”

Section: Introductionmentioning

confidence: 99%

Use of a nonlinear controller with dynamic couplings in gains for simulation test of an underwater vehicle model

Herman

2021

International Journal of Advanced Robotic Systems

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The article considers a method of examining the influence of dynamic couplings contained in the underwater vehicle model on the movement of this vehicle. The method uses the inertia matrix decomposition and a velocity transformation if the fully actuated vehicle is described in the earth-frame representation. Based on transformed equations of motion, a controller including dynamic couplings in the gain matrices is designed. In the proposed method, the control algorithm is used for the test vehicle dynamics model taking into account disturbances. The approach is useful for simulating the model of an underwater vehicle and improving it, thus avoiding unnecessary experiments or planning them better. The procedure is shown for a full model of an underwater vehicle, and its usefulness is verified by simulation.

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“…In Yang et al (2016), based on recurrent hermit neural networks, a nonlinear robust adaptive sliding mode controller was developed for the longitudinal motion tracking control of ROV. In Zhou et al (2020), considering the motion tracking control problem, an adaptive robust sliding mode controller was designed for the autonomous underwater glider with the uncertainty and unknown time-varying disturbance. In Wang et al (2020), a neuroadaptive sliding mode controller was proposed for the leader-follower formation control of multiple underwater vehicles with model uncertainties and external disturbances.…”

Section: Introductionmentioning

confidence: 99%

Observer-based adaptive neural sliding mode trajectory tracking control for remotely operated vehicles with thruster constraints

Chu

Chen²,

Zhu

et al. 2021

Transactions of the Institute of Measurement and Control

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For a class of remotely operated vehicle (ROV) systems with thruster constraints, immeasurable states, and unknown nonlinearities, the trajectory tracking control problem was discussed in this paper. The unknown nonlinear functions were approximated by radial basis function (RBF) neural networks. An adaptive state observer based on neural networks was designed and the immeasurable states were estimated. Considering the problem of thruster saturation constraints, an auxiliary system for saturation compensation was designed and a saturation factor was constructed by the auxiliary system state. By applying the backstepping design method, an adaptive neural sliding mode trajectory tracking controller was developed, in which the saturation factor is contained in adaptive laws. It was proved that the uniformly ultimately bounded (UUB) of trajectory tracking errors can be obtained. Finally, the effectiveness of the proposed trajectory tracking control approach was checked by simulations.

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Adaptive robust sliding mode control of autonomous underwater glider with input constraints for persistent virtual mooring

Cited by 54 publications

References 39 publications

Experimental analysis on hydrodynamic coefficients of an underwater glider with spherical nose for dynamic modeling and motion simulation

Experimental analysis on hydrodynamic coefficients of an underwater glider with spherical nose for dynamic modeling and motion simulation

Use of a nonlinear controller with dynamic couplings in gains for simulation test of an underwater vehicle model

Observer-based adaptive neural sliding mode trajectory tracking control for remotely operated vehicles with thruster constraints

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