Fuzzy unknown observer-based robust adaptive path following control of underactuated surface vehicles subject to multiple unknowns

Wang, Weining; Sun, Zhuo; Yin, Jianchuan; Zou, Zao-Jian; Su, Shun‐Feng

doi:10.1016/j.oceaneng.2019.02.017

Cited by 121 publications

(57 citation statements)

References 25 publications

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“…whereŴ ¼ ½Ŵ 1 ;Ŵ 2 ;Ŵ 3 ;Ŵ 4 ;Ŵ 5 ;Ŵ 6 is the estimation value of the weighted matrix W Ã . To consider unknown upper bounds Ã of approximation error, we propose the adaptive control law as follows 9, according to the control law (20) and adaptive laws (21) and 22, the transforming error e i and tracking error e i can be guaranteed uniformly ultimately bounded and satisfy prescribed performance equation 6, respectively.…”

Section: The Design Of Adaptive Trajectory Tracking Controllermentioning

confidence: 99%

“…whereW ¼Ŵ À W Ã , ¼ À Ã are estimation errors, G w ¼ diag½t w1 ; t w2 ; t w3 ; t w4 ; t w5 ; t w6 . Differentiating V with respect to time and substituting equations (15) and (20) to (22) into it, we obtain…”

Section: The Design Of Adaptive Trajectory Tracking Controllermentioning

confidence: 99%

“…This controller can be called adaptive tracking controller (ATC) and is expressed as equations (35) to (37). (20) to (22)) is denoted as PPATC, the adaptive tracking controller (equations (35) to (37)) is denoted as ATC, and the prescribed performance bounds are denoted as r. The comparisons on actual and desired 3-D trajectories figure is shown in Figure 10. The control input of the OBFN is shown in Figure 11.…”

Section: Parameters Of the Controllermentioning

confidence: 99%

“…This control algorithm basically consisted of approximately known inverse dynamic model output and continuous adaptive PI term is developed to deal with chattering effect. Wang et al 20 addressed a finite-time observer based accurate tracking control scheme for marine vehicle with complex unknowns including unmodeled dynamics and disturbances. For the AUV model uncertainties, the above references developed many trajectory tracking control strategies which achieve satisfactory results.…”

Section: Introductionmentioning

confidence: 99%

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Prescribed performance adaptive fault-tolerant trajectory tracking control for an ocean bottom flying node

Qin

Sun

et al. 2019

International Journal of Advanced Robotic Systems

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The ocean bottom flying node is a novel autonomous underwater vehicle that explores the oil and gas resources in deep water. Thousands of the ocean bottom flying nodes track different predefined trajectories arriving at target points in a small ocean area, respectively. A class of prescribed performance adaptive trajectory tracking control method is investigated for the ocean bottom flying node trajectory tracking problem with ocean current disturbances, model uncertainties as well as thruster faults. Based on a predefined performance function and an error transformation, the ocean bottom flying node trajectory tracking error is restricted to prespecified bounds to ensure a desired transient and steady response. Radial basis function neural network is used to approximate the general uncertainty caused by ocean current disturbances, model uncertainties, and thruster faults. Further, the upper bound of approximation error is estimated by an adaptive law. Using the adaptive laws, we propose a prescribed performance adaptive trajectory tracking controller. The simulation examples on an ocean bottom flying node system show that the proposed control scheme can compensate for the effect of the general uncertainty while obtaining the fast transient process and expected trajectory tracking accuracy.

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Section: The Design Of Adaptive Trajectory Tracking Controllermentioning

confidence: 99%

Section: The Design Of Adaptive Trajectory Tracking Controllermentioning

confidence: 99%

Section: Parameters Of the Controllermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Prescribed performance adaptive fault-tolerant trajectory tracking control for an ocean bottom flying node

Qin

Sun

et al. 2019

International Journal of Advanced Robotic Systems

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“…7 Many intelligent control methods have also been successfully employed, such as fuzzy logic control. [8][9][10] The desired path is usually a straight line or a waypoint path, which consists of piecewise straight lines with the curvature being zero. It is common for USVs to navigate at or nearly at constant velocity for a long distance.…”

Section: Introductionmentioning

confidence: 99%

Robust predictive control for anti-rolling path following of underactuated surface vessels using adaptive Kalman filter

Liu

Zhang

et al. 2019

International Journal of Advanced Robotic Systems

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With the strong time-varying disturbances in wave fields, the large sway motion of underactuated surface vessels can be caused leading to the control performance reduction and large range of roll angle, such that a novel path following control with roll constraints is proposed. Firstly, the affine switching system model is constructed with coupled surge, sway, roll, and yaw. Then, with augmented state adaptive Kalman filter, the estimations of system state and disturbance can be obtained for the feedforward compensation. Considering the existing estimation error between real and estimated states, the state estimation has been adopted directly in the controller design for the performance improvements. With the convex optimization of linear matrix inequalities, the invariant ellipsoid constraint ensures the close-loop system uniformly bounded and stable. Lastly, the simulation results have verified the effectiveness of the designed control approach.

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Finite‐time extended state observer‐based exact tracking control of an unmanned surface vehicle

Wang

Zhu

Qin

et al. 2020

Intl J Robust & Nonlinear

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In the presence of complex unknowns consisting of system dynamics and environmental disturbances, it is rather meaningful to exactly track an unmanned surface vehicle (USV) to the desired trajectory in practical scenarios including routing inspection, marine survey, and guard patrol, etc. In this paper, the exact trajectory tracking problem is solved by establishing a finite‐time extended state observer‐ (FESO) based exact tracking control (FESO‐ETC) scheme. By virtue of nonsmooth analysis, the FESO is firstly devised by only requiring continuous differentiability and is incorporated into the nonsingular fast terminal sliding mode control framework, and thereby further enhancing disturbance rejection and tracking accuracy. Moreover, global finite‐time stability of the entire FESO‐ETC closed‐loop system is derived from rigorously theoretical analysis, and thereby contributing to a model‐free finite‐time control paradigm. Simulation studies and comparisons demonstrate that the proposed FESO‐ETC approach can achieve exact trajectory tracking in the presence of complex unknowns.

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Fuzzy unknown observer-based robust adaptive path following control of underactuated surface vehicles subject to multiple unknowns

Cited by 121 publications

References 25 publications

Prescribed performance adaptive fault-tolerant trajectory tracking control for an ocean bottom flying node

Prescribed performance adaptive fault-tolerant trajectory tracking control for an ocean bottom flying node

Robust predictive control for anti-rolling path following of underactuated surface vessels using adaptive Kalman filter

Finite‐time extended state observer‐based exact tracking control of an unmanned surface vehicle

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