Adaptive Backstepping Terminal Sliding Mode Control Method Based on Recurrent Neural Networks for Autonomous Underwater Vehicle

Yang, Chao; Yao, Feng; Zhang, Mingjun

doi:10.1186/s10033-018-0307-5

Cited by 18 publications

(9 citation statements)

References 28 publications

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“…P 0 and Q are the positive definite matrices, so that A T P 0 + P 0 A = −Q. In Equations (18a) and (20), the discontinuous switching term sign(s) in Equation (14) is replaced by K 1 s + K 2 |s| α sig(s) [27] to reduce the chattering of control voltage. Based on the above control law, the control system block diagram of the proposed controller in this article is shown in Figure 1.…”

Section: Adaptive Sliding Mode Pid Control Law and Error-boundary Conmentioning

confidence: 99%

Adaptive Sliding Mode PID Control for Underwater Manipulator Based on Legendre Polynomial Function Approximation and Its Experimental Evaluation

et al. 2020

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The joint control problem of the underwater manipulator is addressed in this paper, under the influence of uncertainty factors such as model uncertainty, external disturbance, and manipulator joint lag. In general, for the uncertainty factors, it is usually approximated online, but it is difficult to select a reasonable value for the approximation error boundary, too conservative estimated values would cause chattering problem easily. And the influence of joint lag on the manipulator control should be considered in actual work. Unlike most previous control method, in this paper, the function approximation technique (FAT), which uses the Legendre polynomial, is adopted to approximate the uncertainty factors online. Then, based on the proportion integral differential (PID) sliding manifold with the integral and differential of tracking error, a sliding model PID controller is designed to speed up the response and reduce the effects of joint lag. For the error boundary, the adaptive law is proposed, and it will reduce chattering of the control quantity under the steady state of the system. It was proved that the joint error of the control system is uniformly asymptotic convergence through the stability analysis. Finally, the effectiveness of the proposed approach is demonstrated with pool comparison experiments of the underwater manipulator installed in the autonomous underwater vehicles (AUVs).Appl. Sci. 2020, 10, 1728 2 of 15 developed and equipped on multipurpose intervention-AUV [4]. An underwater electric manipulator (MARIS 7080, 7 DOF manipulator) was equipped on semi-autonomous underwater vehicle for the intervention mission (SAUVIM) [5].In UVMS, the underwater manipulator is a key component, and its joint control accuracy directly determines the operating accuracy of the UVMS. At present, underwater manipulators are mostly control objects with joint redundancy, and the accuracy mainly depends on the control performance of joints [6]. However, due to the nonlinear, time-variation of dynamic properties and other factors (i.e., external disturbances such as ocean current disturbance) [7,8], the system dynamic model has uncertainties, which will affect the joint control of the manipulator based on the dynamic model. Besides, for most hydraulic manipulators, the joint control performance is also affected by joint lag [6,9,10], which means that the joint lag will affect the control accuracy of manipulator joint. In conclusion, under the influence of the above factors, it has great research significance and practical value to develop the joint control technology of underwater manipulators for improving the accuracy and efficiency of underwater operation.Currently, many methods have achieved high control accuracy, which uses the online approximation to deal with the uncertainty factors, and determine the controller and adaptive law of parameter through stability analysis [11,12]. Among them, in view of the nonlinear and uncertain identification ability [11][12][13][14][15][16], neural network and fuzzy control has b...

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Section: Adaptive Sliding Mode Pid Control Law and Error-boundary Conmentioning

confidence: 99%

Adaptive Sliding Mode PID Control for Underwater Manipulator Based on Legendre Polynomial Function Approximation and Its Experimental Evaluation

et al. 2020

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“…Anderlini et al [29] investigated an ROV with the consequent changes system dynamics when carried an object, an adaptive model predictive control scheme was proposed and its performance was compared with PID and sliding mode control. Many different control strategies for UVMS to track task trajectories were designed and carried out in recent years, such as adaptive backstepping control [30][31], model predictive control [32], sliding mode impedance control [33], and so on. Furthermore, vision based dexterous manipulation is also a useful form for underwater operations [34][35][36].…”

Section: •3•mentioning

confidence: 99%

Dynamics Simulation of Grasping Process of Underwater Vehicle-Manipulator System

Chang

Zhang

Zheng

et al. 2020

Preprint

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Underwater vehicle-manipulator system (UVMS) can be applied to fulfill different complex underwater tasks such as grasping, drilling, sampling, etc. It is widely used in the field of oceanographic research, marine exploration, military and commercial applications. In this paper, the dynamic simulation of UVMS is presented in the process of grasping an object. Firstly, the dynamic model of UVMS, which considers the change of the load of manipulator when the end effector of manipulator grasps the object, is developed. To compare different control conditions, the numerical simulation of grasping processes without/with vehicle attitude control are carried out. The results show that the coupling dynamics between the vehicle and the manipulator in the grasping process are clearly illustrated. The tracking position error of end effector without vehicle control is large and UVMS cannot complete the grasping task under this condition. Vehicle control can compensate the motion of vehicle due to the coupling effect caused by the motion of manipulator. This study will contribute to underwater operation mission for UVMS with floating base.

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“…The current issue and full text archive of this journal is available on Emerald Insight at: https://www.emerald.com/insight/0143-991X.htm Industrial Robot: the international journal of robotics research and application 50/6 (2023) 900-916 Emerald Publishing Limited [ISSN 0143-991X] [DOI 10.1108/IR-01-2023-0008] and overshoot for the underactuated system (Youssef et al, 2022). At present, the methods used for the overall control of robots mainly include model predictive control (MPC) (Camacho and Alba, 2013), neural network (Yang et al, 2018) and robust adaptive control (Lin et al, 2021). The underwater motion of amphibious robots is often accompanied by severe response lag, and MPC can react in advance to the upcoming abrupt change.…”

Section: Introductionmentioning

confidence: 99%

CPG-MPC controller for wheel-fin-flipper integrated amphibious robot

Qiao,

Wei,

et al. 2023

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Purpose The purpose of this paper is to introduce a motion control method for WFF-AmphiRobot, which can effectively realize the flexible motion of the robot on land, underwater and in the transition zone between land and water. Design/methodology/approach Based on the dynamics model, the authors selected the appropriate state variables to construct the state space model of the robot and estimated the feedback state of the robot through the maximum a posteriori probability estimation. The nonlinear predictive model controller of the robot is constructed by local linearization of the model to perform closed-loop control on the overall motion of the robot. For the control problem of the terminal trajectory, using the neural rhythmic movement theory in bionics to construct a robot central pattern generator (CPG) for real-time generation of terminal trajectory. Findings In this paper, the motion state of WFF-AmphiRobot is estimated, and a model-based overall motion controller for the robot and an end-effector controller based on neural rhythm control are constructed. The effectiveness of the controller and motion control algorithm is verified by simulation and physical prototype motion experiments on land and underwater, and the robot can ideally complete the desired behavior. Originality/value The paper designed a controller for WFF-AmphiRobot. First, when constructing the robot state estimator in this paper, the robot dynamics model is introduced as the a priori estimation model, and the error compensation of the a priori model is performed by the method of maximum a posteriori probability estimation, which improves the accuracy of the state estimator. Second, for the underwater oscillation motion characteristics of the flipper, the Hopf oscillator is used as the basis, and the flipper fluctuation equation is modified and improved by the CPG signal is adapted to the flipper oscillation demand. The controller effectively controls the position error and heading angle error within the desired range during the movement of the WFF-AmphiRobot.

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Adaptive Backstepping Terminal Sliding Mode Control Method Based on Recurrent Neural Networks for Autonomous Underwater Vehicle

Cited by 18 publications

References 28 publications

Adaptive Sliding Mode PID Control for Underwater Manipulator Based on Legendre Polynomial Function Approximation and Its Experimental Evaluation

Adaptive Sliding Mode PID Control for Underwater Manipulator Based on Legendre Polynomial Function Approximation and Its Experimental Evaluation

Dynamics Simulation of Grasping Process of Underwater Vehicle-Manipulator System

CPG-MPC controller for wheel-fin-flipper integrated amphibious robot

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