Adaptive fuzzy sliding mode control for robust trajectory tracking control of an autonomous underwater vehicle

Londhe, P. S.; Patre, B. M.

doi:10.1007/s11370-018-0263-z

Cited by 52 publications

(21 citation statements)

References 39 publications

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“…Based on (31)(32), it is known that the control performance largely depends on the value of the gain matrix, A. Its submatrices A ν , A m , H 2 and H c are defined as shown in (38)(39)(40)(41).…”

Section: B Fuzzy Algorithmmentioning

confidence: 99%

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Modeling and Fuzzy Decoupling Control of an Underwater Vehicle-Manipulator System

Han

Wei

et al. 2020

IEEE Access

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This paper presents the detailed modeling and simulation of the dynamic coupling between an autonomous underwater vehicle (AUV) and a manipulator. The modeling processes are described with the incorporation of the most dominating hydrodynamic effects such as added mass, lift and drag forces. The hydrodynamic coefficients are derived using strip theory and are adjusted according to dynamical similarity. A fuzzy decoupling controller (FDC) is proposed for an autonomous underwater vehicle-manipulator system (UVMS) which consists of two subsystems, an underwater vehicle and a manipulator. The proposed controller uses a fuzzy algorithm (FA) to adaptively tune the gain matrix of the error function (EF). The EF is described by the integral sliding surface function. This technique allows the off-diagonal elements developed for decoupling the system to be incorporated in the gain matrix. Tracing the FA and EF back to the principle of feedback linearization, one further obtains evidence about the decoupling and stability of the system. Moreover, a desired trajectory with the consideration of the dynamic coupling of the AUV is designed to reduce the thruster forces and manipulator's torques. This technique provides high performance in terms of tracking error norms and expended energy norms. A major contribution of this study is that it adopts the off-diagonal elements to exploit the dynamic coupling between the degrees of freedom of the subsystem and the dynamic coupling between the two subsystems. Simulation results demonstrate the effectiveness and robustness of the proposed technique in the presence of parameter uncertainties and external disturbances. INDEX TERMS AUV, dynamic coupling, decoupling control, fuzzy algorithm, hydrodynamic effect, underwater manipulator.

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Section: B Fuzzy Algorithmmentioning

confidence: 99%

“…Comparing (28)(29) and (31)(32), the above mentioned control inputs lead to the following error dynamics of the UVMS.…”

Section: Stability Analysismentioning

confidence: 99%

Modeling and Fuzzy Decoupling Control of an Underwater Vehicle-Manipulator System

Han

Wei

et al. 2020

IEEE Access

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“…In order to eliminate current interference, many outstanding control methods have been adapted for ROVs' control, such as PID control [6,7], adaptive control [8][9][10], back-step control [11,12], and sliding mode control (SMC) [13][14][15][16]. In addition, fuzzy logic control [13,17,18] and neural network control [7,19,20] are often used in combination with other control methods.…”

Section: Introductionmentioning

confidence: 99%

Double-Loop Sliding Mode Controller with An Ocean Current Observer for the Trajectory Tracking of ROV

Wang

Sun³

et al. 2021

JMSE

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To solve the trajectory tracking problem of insufficient response and the large tracking error of remotely operated vehicles (ROVs) under the interference of large ocean currents, this paper proposes a double-loop sliding mode controller with an ocean current observer. The designed controller consisted of an outer-loop controller (the position controller) and an inner-loop controller (the velocity controller): the outer controller was designed by the position error, and a reference velocity was created for the inner loop to achieve accurate positioning and attitude tracking. The reference control input was treated as a new target to design the inner-loop controller, enabling the ROV to achieve accurate reference velocity tracking. Based on the theoretical idea of active disturbance rejection control, a kinematic equation-based ocean current observer was designed to estimate and compensate for large unknown currents to ensure accurate trajectory tracking performance under large currents. The simulation results proved that the double-loop sliding-mode control scheme with an ocean current observer always showed good tracking performance, demonstrating the excellent control performance and high robustness of the scheme. Compared with the high-complexity control schemes such as neural network-based PID control or fuzzy sliding mode control, it effectively improves the robustness to ocean current disturbances without increasing the computational effort excessively, and is more practical in ROV systems with limited computational power.

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“…In terms of fuzzy control, many methods are designed to reduce the complexity of the system [28]- [35], and literature [36] proposed the dynamic feedback compensator to solve the asymptotic tracking problem. Literature [37] proposed an adaptive fuzzy sliding mode control (AFSMC) scheme. The chattering problem in tracking control is eliminated, and the steady-state error in tracking control is reduced.…”

Section: Introductionmentioning

confidence: 99%

Manipulator Trajectory Tracking of Fuzzy Control Based on Spatial Extended State Observer

et al. 2020

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This paper mainly studies the trajectory tracking control problem of the manipulator of TianGong-2 when capturing floating objects in the experimental cabin. Microgravity environment will lead to the existing control system of space robot can not produce good control effect. Different gravity environments change the design requirements of space robots, and the ground test cannot meet these space requirements. In this paper, a fuzzy control strategy based on a spatial extended state observer(FC-SESO) is proposed to solve these inconsistent problems. First, a spatial extended state observer is designed to estimate the influence of disturbance on the system. In order to estimate the disturbance quickly and accurately, a disturbance model including gust is established. Second, in order to ensure the rapid convergence of the desired trajectory, the fuzzy control law is derived. Based on Lyapunov stability theory, the stability of the control system based on the spatial extended state observer is proven. Finally, the proposed system is simulated and captured on the Tiangong-2 manipulator platform to verify the effectiveness of the control algorithm. INDEX TERMS Fuzzy control, microgravity, spatial extended state observer, trajectory tracking control.

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Adaptive fuzzy sliding mode control for robust trajectory tracking control of an autonomous underwater vehicle

Cited by 52 publications

References 39 publications

Modeling and Fuzzy Decoupling Control of an Underwater Vehicle-Manipulator System

Modeling and Fuzzy Decoupling Control of an Underwater Vehicle-Manipulator System

Double-Loop Sliding Mode Controller with An Ocean Current Observer for the Trajectory Tracking of ROV

Manipulator Trajectory Tracking of Fuzzy Control Based on Spatial Extended State Observer

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