Robust Nonlinear Observer And Observer‐Backstepping Control Design For Surface Ships

Xia, Guoqing; Shao, Xingchao; Zhao, Ang

doi:10.1002/asjc.1021

Cited by 20 publications

(12 citation statements)

References 9 publications

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“…To get a faster convergence rate and a higher tracking accuracy for trajectory tracking control for AUVs, the control scheme design procedure was complicated. At the same time, Xia et al (2015) developed a nonlinear robust passive observer for surface ships in surge, sway and yaw. To verify the efficiency of the observer, backstepping and Lyapunov redesign techniques were utilised.…”

Section: Introductionmentioning

confidence: 99%

Improved Concise Backstepping Control of Course Keeping for Ships Using Nonlinear Feedback Technique

et al. 2017

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Course keeping for ships is vital for automatic navigation in marine transportation. To improve the control effect and reduce the energy output of the controller, this article proposes an improved concise backstepping controller based on a Lyapunov candidate function by introducing a nonlinear function of course error to replace the course error itself in the feedback loop. The procedure of nonlinear controller design has been reduced from two steps to one step using information from controlled plant to construct the Lyapunov candidate function. Compared with the pure backstepping control, the proposed improved algorithm reserves the nonlinear item of the system, and possesses a strong disturbance rejection ability and robustness to the mathematical model uncertainty. The algorithm given here has advantages of simplified construction method, satisfactory control effect, robustness and energy saving.

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Section: Introductionmentioning

confidence: 99%

Improved Concise Backstepping Control of Course Keeping for Ships Using Nonlinear Feedback Technique

et al. 2017

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“…The establishment of a ship's motion model is very important for effective motion control. In terms of ship motion models, most studies build a model based on three degrees of freedom (3-DOF), or add roll control to build a 4-DOF model, very few of which are 6-DOF models [42][43][44][45], as shown in Figure 3. The model categories used are usually based on the hydrodynamic model and responsive model.…”

Section: Classification Of Motion Control For Massmentioning

confidence: 99%

State-of-the-Art Research on Motion Control of Maritime Autonomous Surface Ships

Wang

Liu

et al. 2019

JMSE

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At present, with the development of waterborne transport vehicles, research on ship faces a new round of challenges in terms of intelligence and autonomy. The concept of maritime autonomous surface ships (MASS) has been put forward by the International Maritime Organization in 2017, in which MASS become the new focus of the waterborne transportation industry. This paper elaborates on the state-of-the-art research on motion control of MASS. Firstly, the characteristics and current research status of unmanned surface vessels in MASS and conventional ships are summarized, and the system composition of MASS is analyzed. In order to better realize the self-adaptability of the MASS motion control, the theory and algorithm of ship motion control-related systems are emphatically analyzed under the condition of classifying ship motion control. Especially, the application of intelligent algorithms in the ship control field is summarized and analyzed. Finally, this paper summarizes the challenges faced by MASS in the model establishment, motion control algorithms, and real ship experiments, and proposes the composition of MASS motion control system based on variable autonomous control strategy. Future researches on the accuracy and diversity of developments and applications to MASS motion control are suggested.

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“…Therefore, it is necessary to investigate distributed control problem in the absence of velocity measurements. Some output feedback controllers were proposed without using velocity measurement in [3]- [5]. Reference [3] proposed the passive nonlinear observer for MSV, where the velocity and…”

Section: Introductionmentioning

confidence: 99%

Neuroadaptive Distributed Output Feedback Tracking Control for Multiple Marine Surface Vessels With Input and Output Constraints

et al. 2019

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In this paper, a neuroadaptive distributed output feedback formation tracking control scheme for multiple marine surface vessels with model uncertainties, unknown environmental disturbances and input and output constraints is proposed. A neural network based observer is developed to reconstruct the unmeasured velocity and approach the model uncertainties. To handle the input constraint, an auxiliary dynamic system is introduced. The tracking error transformation and the barrier Lyapunov function are used to tackle with the output constraint. Subsequently, by using the estimated velocity of neighboring vessels, neuroadaptive distributed output feedback controllers are developed. Furthermore, to avoid directly taking the time derivation of virtual control law and generate smooth reference signals, linear tracking differentiators are employed. Finally, it is shown that all the signals in the closed-loop system are bounded via Lyapunov analysis. Simulations are carried out to verify the proposed control scheme. INDEX TERMS Barrier Lyapunov function, distributed control, input constraint, marine surface vessels, output constraint, output feedback control.

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Robust Nonlinear Observer And Observer‐Backstepping Control Design For Surface Ships

Cited by 20 publications

References 9 publications

Improved Concise Backstepping Control of Course Keeping for Ships Using Nonlinear Feedback Technique

Improved Concise Backstepping Control of Course Keeping for Ships Using Nonlinear Feedback Technique

State-of-the-Art Research on Motion Control of Maritime Autonomous Surface Ships

Neuroadaptive Distributed Output Feedback Tracking Control for Multiple Marine Surface Vessels With Input and Output Constraints

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