Supertwisting and terminal sliding mode control of course keeping for ships by using particle swarm optimization

Islam, Muhammad Muzammal; Siffat, Syed Ahmad; Ahmad, Iftikhar; Liaquat, Muwahida

doi:10.1016/j.oceaneng.2022.112942

Cited by 9 publications

(4 citation statements)

References 28 publications

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“…Improved traditional controllers are considered an effective approach to realize the course-keeping of ships. Some common methods include improved sliding mode controllers [18][19][20][21], improved PID controllers [20,[22][23][24], improved backstepping controllers [9,[25][26][27], and improved bipolar sigmoid functions [28,29]. These methods mainly improve traditional controllers by introducing adaptive control, synergetic control, control formula improvement, and parameter optimization.…”

Section: Introductionmentioning

confidence: 99%

PSO-Based Predictive PID-Backstepping Controller Design for the Course-Keeping of Ships

Lin,

Zheng,

Han

et al. 2024

JMSE

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Ship course-keeping control is of great significance to both navigation efficiency and safety. Nevertheless, the complex navigational conditions, unknown time-varying environmental disturbances, and complex dynamic characteristics of ships pose great difficulties for ship course-keeping. Thus, a PSO-based predictive PID-backstepping (P-PB) controller is proposed in this paper to realize the efficient and rapid course-keeping of ships. The proposed controller takes the ship’s target course, current course, yawing speed, as well as predictive motion parameters into consideration. In the design of the proposed controller, the PID controller is improved by introducing predictive control. Then, the improved controller is combined with a backstepping controller to balance the efficiency and stability of the control. Subsequently, the parameters in the proposed course-keeping controller are optimized by utilizing Particle Swarm Optimization (PSO), which can adaptively adjust the value of parameters in various scenarios, and thus further increase its efficiency. Finally, the improved controller is validated by carrying out simulation tests in various scenarios. The results show that it improves the course-keeping error and time-response specification by 4.19% and 9.71% on average, respectively, which can efficiently achieve the course-keeping of ships under various scenarios.

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Section: Introductionmentioning

confidence: 99%

PSO-Based Predictive PID-Backstepping Controller Design for the Course-Keeping of Ships

Lin,

Zheng,

Han

et al. 2024

JMSE

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“…Meanwhile, the linear term α 1 e(k − 1) serves to expedite the convergence of the system state when it nears equilibrium. From (11), we arrive at…”

Section: Model-free Adaptive Sliding Mode Control Lawmentioning

confidence: 99%

“…Theorem 2. Considering the parameter adaptive law ( 7) and ( 8), the fast terminal sliding surface (11) and ( 13), along with the control input (20) using ( 18) and (19) for the dynamic linearization model ( 5), if the switching gain λ s is selected to meet the following condition…”

Section: System Stability Analysismentioning

confidence: 99%

“…There are four main types of mathematical models for USV course control, such as Nomoto [1], Norribin [2,3], MMG [4] and Fossen [5]. Based on these mathematical models, many methods have been applied to solve the course control, achieving desirable theoretical results, mainly including PID control [6], ADRC [7], dynamic surface control [8,9], sliding mode control [10,11], intelligent control [12,13] and other methods. However, apart from PID, most of the other methods mentioned above have not been verified on actual USV.…”

Section: Introductionmentioning

confidence: 99%

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Model-Free Adaptive Sliding Mode Control Method for Unmanned Surface Vehicle Course Control

Liu,

Ye,

Yang

2023

JMSE

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A novel data-driven-based adaptive sliding-mode control scheme is proposed for unmanned surface vehicle course control in the presence of disturbances. The proposed method utilizes the model-free adaptive control (MFAC) theory. On account of the unknown dynamics of the USV course system, the control scheme is only established by online input and output information of the system. Based on a model-free adaptive control scheme, the system disturbance estimation technique is applied to compensate for the disturbances in the established compact form dynamic linearization data model. The controller is designed and combined with the sliding mode method, and a second-order switching surface with a fast terminal sliding function is employed to achieve finite-time convergence. Furthermore, an analysis of the stability of the control system is provided. Finally, MATLAB simulations are implemented to verify the validity and robustness of the proposed control scheme by comparing it with PID and typical model-free adaptive sliding mode control.

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The control method for ship tracking when navigating through narrow and curved sections

Liu,

Huang,

et al. 2024

Applied Ocean Research

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Supertwisting and terminal sliding mode control of course keeping for ships by using particle swarm optimization

Cited by 9 publications

References 28 publications

PSO-Based Predictive PID-Backstepping Controller Design for the Course-Keeping of Ships

PSO-Based Predictive PID-Backstepping Controller Design for the Course-Keeping of Ships

Model-Free Adaptive Sliding Mode Control Method for Unmanned Surface Vehicle Course Control

The control method for ship tracking when navigating through narrow and curved sections

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