Adaptive fuzzy control for a marine vessel with time‐varying constraints

Kong, Linghuan; He, Wei; Yang, Chenguang; Li, Guang; Zhang, Zhengqiang

doi:10.1049/iet-cta.2017.0757

Cited by 42 publications

(20 citation statements)

References 49 publications

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“…Thus, if no state constraint requirements exist, this formula can be substituted into the quadratic term for the TABLF (30). In this case, the analysis method is the same as in the case where there are no error constraints.…”

Section: Robust Trajectory Tracking Via Output Feedbackmentioning

confidence: 99%

Robust trajectory tracking control of a marine surface vessel using asymmetric error constraints and output feedback

Chen

Tian

Liu

2020

Intl J Robust & Nonlinear

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This article investigates the problem of robust trajectory tracking for a marine surface vessel in the presence of asymmetrical error time-varying constraints and output feedback. To deal with system uncertainties, adaptive neural networks (NNs) are used to approximate unknown dynamics model parameters and external disturbances. To obtain unmeasured velocities, a predictive observer based on output feedback is developed to estimate unknown velocities. A tan-type asymmetric barrier Lyapunov function is used to deal with asymmetric error time-varying constraints. The high-frequency robust adaptive law is used to compensate for parameter estimation errors. The kinematic controller is designed based on the barrier Lyapunov function method, and the kinetics controller is designed base on an observer, an adaptive NN and a robust high-frequency control. All signals of the closed-loop systems are proved to be semiglobally uniformly and ultimately bounded via Lyapunov analysis, and the asymmetrical error constraints are not violated. Simulations are performed, and synthetic comparison is used to verify the feasibility and robustness of the proposed control law.

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Section: Robust Trajectory Tracking Via Output Feedbackmentioning

confidence: 99%

Robust trajectory tracking control of a marine surface vessel using asymmetric error constraints and output feedback

Chen

Tian

Liu

2020

Intl J Robust & Nonlinear

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“…Besides, the approximation-based control methods can also attenuate the effects of uncertainties. In such technique, the unknown vessel dynamics are identified by using appropriate neural networks (NNs) [12]- [14] or fuzzy logic systems (FLS) [15], [16], etc. In [17], the strong approximation capacity of neural network was integrated with backstepping control to design an adaptive robust tracking controller for an underactuated vessel, and the vessel can track the desired trajectory with good robust performance.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Neural-Based Finite-Time Trajectory Tracking Control for Underactuated Marine Surface Vessels With Position Error Constraint

Wang

2019

IEEE Access

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This paper addresses the trajectory tracking control problem of an underactuated marine surface vessel with position error constraint, finite-time convergence requirement, model uncertainties, and external disturbances. A barrier Lyapunov function is incorporated with the backstepping control scheme to handle the position error constraint. The command filters and auxiliary systems are designed to avoid the tedious analytical computation of the virtual control laws. Furthermore, an adaptive radial basis function neural network is adopted to provide the estimation of the unknown hydrodynamic damping term, and a disturbance observer is designed to compensate for the lumped disturbances including the neural approximation errors and external ocean disturbances. We show that under the proposed control scheme, the tracking errors of the vessel can converge to a small neighborhood around 0 within finite time, while the constraint on the vessel position is never violated during the maneuver, and all closed-loop signals are proved to be bounded. Finally, a numerical simulation is provided to illustrate the effectiveness and superiority of the proposed control scheme. INDEX TERMS Marine surface vessel, finite-time control, trajectory tracking, barrier Lyapunov function.

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“…In order to tackle the nonlinearities of control signals and guarantee a safe operation, the study in [13] (Tu F, Ge 2 Mathematical Problems in Engineering S S, Choo Y S et al, 2017) presented an adaptive neural constrained control with nonlinear adaptive filter based on BLF for DP of an accommodation ship in deep water. To tackle the constraint problems, the study in [14] (Kong L, He W, Yang C et al, 2018) utilized an asymmetric time-varying BLF to the design of adaptive fuzzy neural network control, proved that closed-loop system was stable by Lyapunov stability theory, and verified the effectiveness of proposed control by comparative simulations. Combining the BLF with backstepping technique is one method of the application of BLF to tackle the problem of state constraint in control areas.…”

Section: Introductionmentioning

confidence: 99%

Backstepping Control Using Barrier Lyapunov Function for Dynamic Positioning Control System with Passive Observer

Xia

Xue

Sun

et al. 2019

Mathematical Problems in Engineering

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This paper presents a backstepping controller using barrier Lyapunov function (BLF) for dynamic positioning (DP) system. For safety reasons, the position and heading of DP ship are to be maintained in certain range. Thus, in this paper, a control law based on BLF and backstepping technique is proposed to limit the position and heading. The closed-loop system is proved stable in the sense of Lyapunov stability theories. In addition, since the velocities of ship are not measurable and the wave frequency (WF) motion is unavailable, a passive observer is adopted to estimate the velocities and the effect of WF motion. The simulation results show that the proposed controller can limit the position and heading of the vessel in a predefined range and verify the performance of the proposed controller and the passive observer.

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Adaptive fuzzy control for a marine vessel with time‐varying constraints

Cited by 42 publications

References 49 publications

Robust trajectory tracking control of a marine surface vessel using asymmetric error constraints and output feedback

Robust trajectory tracking control of a marine surface vessel using asymmetric error constraints and output feedback

Adaptive Neural-Based Finite-Time Trajectory Tracking Control for Underactuated Marine Surface Vessels With Position Error Constraint

Backstepping Control Using Barrier Lyapunov Function for Dynamic Positioning Control System with Passive Observer

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