Linear reduction of backstepping algorithm based on nonlinear decoration for ship course-keeping control system

Zhang, Xianku; Zhang, Qiang; Ren, Hongxiang; Guang-ping, Yang

doi:10.1016/j.oceaneng.2017.10.017

Cited by 62 publications

(32 citation statements)

References 12 publications

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“…However, to obtain the robustness and design flexibility, nonlinear backstepping designs were strongly related to the cancellation of all nonlinearities, which was important in industrial control system for the cancellation requires precise model, which was difficult to obtain in practice [1]. The problems of cancellation of the nonlinearities and high controller output energy were basically solved by using a ship course-keeping controller which combined nonlinear feedback algorithm [16] or nonlinear decoration algorithm [17] and backstepping algorithm. It was noted that the output performance of the control system can not be significantly changed by the nonlinear feedback control, but it could achieve equivalent or even better control effects with smaller amounts of energy [18].…”

Section: Introductionmentioning

confidence: 99%

Nonlinear Improved Concise Backstepping Control of Course Keeping for Ships

Zhang

2019

IEEE Access

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The backstepping control is a kind of nonlinear controller design algorithm. To simplify the nonlinear controller design process, decrease the number of undetermined parameters, improve the robustness, and reduce the energy consumption of the course-keeping controller for ships, an improved concise design method is proposed by introducing an arctan nonlinear function passed through by course error signal under the backstepping design framework, while the design process of the controller is simplified to only one step. The simulation results indicate that, compared with the backstepping-based controller, the maximum response performance (quantified by the mean absolute error) under the proposed controller increases by 57.8%, the maximum energy cost performance (quantified by the mean integral absolute) reduces by 28.6% and the maximum smoothness performance (quantified by the mean total variation) reduces by 44.3% with the strong ability of disturbances rejection. The algorithm given in the note has advantages of the simple design process, strong robustness, and low energy consumption. INDEX TERMS Ships, course-keeping control, nonlinear feedback, backstepping, arctan function.

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Section: Introductionmentioning

confidence: 99%

Nonlinear Improved Concise Backstepping Control of Course Keeping for Ships

Zhang

2019

IEEE Access

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“…In accordance with closed-loop gain shaping algorithm (CGSA) [12][13][14][15][16][17], a concise robust PID controller is presented as follows.…”

Section: Control Parameters Determinationmentioning

confidence: 99%

Concise Robust Control of Marine Engine Speed Based on Backstepping and Its Fuzzy Comprehension

Wang

2019

Complexity

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In this paper, a concise robust control law based on Backstepping for marine engine speed regulation is presented with the uniform asymptotic stability of the closed-loop system proved by Lyapunov synthesis, and the control parameters have obvious physical meaning. Furthermore, parameter determination method is given by virtue of closed-loop gain shaping algorithm. To overcome the perturbation due to load or interference change, variable universe fuzzy inference is introduced to optimize the control system on-line. Compared with the existing research literature, the design method and performance of the controller are more in line with the ocean engineering practice. The results of the simulations of the proposed controller are presented and compared.

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“…The associate editor coordinating the review of this manuscript and approving it for publication was Lifeng Ma. for course control maneuvers due to the nonlinearity and inertia. Nonlinear models [4], [5] are the most widely used model in the field of ship motion control, in which Norrbin model is the typical nonlinear model in course controller design. The paper [6] proposes a novel course control strategy based on Norrbin model for USV, which can make up for the inherent defect of USV vulnerability to the external environment.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Course Control-Based Trajectory Linearization Control for Uncertain Unmanned Surface Vehicle Under Rudder Saturation

et al. 2019

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In the presence of the uncertain system dynamics, unknown time-varying disturbances and rudder saturation, this paper develops a novel robust adaptive course control scheme for unmanned surface vehicle (USV). Considering the characteristics of the rudder servo system, a double loop course controller of the practical and concise is proposed by the enhanced trajectory linearization control (TLC) technology. The key features of the developed controller are that, first, the neural networks are employed to online approximate unmodeled dynamics, and adaptive techniques are adopted to deal with completely unknown external disturbances; second, auxiliary systems that are governed by smooth switching functions, are developed in an unprecedented manner to compensate for the saturation constraints on actuators. The main innovation can be summarized as that the TLC technology is applied to the USV motion control field as a new control algorithm, and the enhanced technology based on traditional TLC not only reduces the number of adjustment parameters but also has simple structure and high robustness. Furthermore, a low frequency learning method improves the applicability of the algorithm. The stability analysis is established using the Lyapunov theory. Simulation results and comparison verify the effectiveness of the proposed strategy.

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Linear reduction of backstepping algorithm based on nonlinear decoration for ship course-keeping control system

Cited by 62 publications

References 12 publications

Nonlinear Improved Concise Backstepping Control of Course Keeping for Ships

Nonlinear Improved Concise Backstepping Control of Course Keeping for Ships

Concise Robust Control of Marine Engine Speed Based on Backstepping and Its Fuzzy Comprehension

Adaptive Course Control-Based Trajectory Linearization Control for Uncertain Unmanned Surface Vehicle Under Rudder Saturation

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