Time-Varying Nonsingular Terminal Sliding Mode control of Autonomous Surface Vehicle with predefined convergence time

Souissi, Sami; Boukattaya, Mohamed

doi:10.1016/j.oceaneng.2022.112264

Cited by 15 publications

(9 citation statements)

References 34 publications

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“…A Fast Terminal Sliding Mode Control (FTSMC) approach for quadrotor Unmanned Aerial Vehicles (UAV) [21] was proposed to deal with the high disturbances and actuator faults during navigation, in which hyperbolic tangent functions are utilized in the adaptive control law to reduce the chattering effect. Souissi and Boukattaya [22] proposed a global Non-singular Terminal Sliding Mode (NTSM) controller that enables the system to converge in finite time and avoid the problem of singular values. An adaptive Non-singular Fast Terminal Sliding Mode Control (NFTSM) was designed and an appropriate parameter-tuning adaptation law was derived to tackle the disturbances [23], in which the time-derivative of fractional power terms is not needed in the controller and thereby the singularity problem typically associated with TSMC is avoided.…”

Section: Introductionmentioning

confidence: 99%

The Non-Singular Terminal Sliding Mode Control of Underactuated Unmanned Surface Vessels Using Biologically Inspired Neural Network

Xu,

Li,

Xin

et al. 2024

JMSE

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Underactuated Unmanned Surface Vessels (USVs) are widely used in civil and military fields due to their small size and high flexibility, and trajectory tracking control is a critical research area for underactuated USVs. This paper proposes a trajectory tracking control strategy using the Biologically Inspired Neural Network (BINN) for USVs to improve tracking speed and accuracy. A virtual control law is designed to obtain the required virtual velocity for trajectory tracking control, in which the velocity error is calibrated to ensure that the position error converges to zero. To observe and compensate for unknown and complex environmental disturbances such as wind, waves, and currents, a nonlinear extended state observer (NESO) is designed. Then, a controller based on Non-singular Terminal Sliding Mode (NTSM) is designed to resolve the problems of singular value and controller chattering and to improve the controller response speed. A BINN is introduced to simplify the process of differentiation, reduce the input values of the initial state, and solve the problem of thruster input saturation. Finally, the Lyapunov stability theory is utilized to analyze the stability of the proposed algorithm. The simulation results show that the proposed algorithm has a higher trajectory tracking accuracy and speed than traditional methods.

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Section: Introductionmentioning

confidence: 99%

The Non-Singular Terminal Sliding Mode Control of Underactuated Unmanned Surface Vessels Using Biologically Inspired Neural Network

Xu,

Li,

Xin

et al. 2024

JMSE

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“…The virtue of this method is that it can ensure that the system trajectory converges to a predefined boundary within a predefined time and the boundary is not affected by disturbances. In [23], by constructing a time-varying non-singular terminal sliding mode manifold, the trajectory tracking of USVs was realized within a predefined time. In addition, to realize the constraints on the transient and steady-state tracking performance of the controlled system while taking into account the predefined-time stability, a predefined-time prescribed performance control technology was developed [24].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Sliding Mode Control for Unmanned Surface Vehicles with Predefined-Time Tracking Performances

Tao

Yan

2023

JMSE

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This paper is concerned with the trajectory tracking control of unmanned surface vehicles (USVs) subject to input quantization, actuator faults and dead zones. In scenarios with dense marine facilities, there are constraints on the tracking performance and convergence time of USVs. First, the designed control signal is quantized by a hysteresis quantizer to reduce the transmission rate. Second, to guarantee the transient and steady-state tracking performance of the USV, a prescribed performance control technology with a predefined settling time is employed. Third, a predefined-time adaptive sliding mode control (SMC) method is designed by integrating the auxiliary function and the barrier function. Moreover, the lumped uncertainties caused by quantization, actuator faults, and dead zones are simultaneously processed using control gain based on barrier function. The proposed control method guarantees that the tracking error and sliding variable converge to the corresponding predefined bounds within a predefined time. The predefined bounds are independent of the upper bound on the lumped uncertainty. The stability of the controlled system is proven via the Lyapunov theorem. Finally, the effectiveness of the designed controller is verified by numerical simulations.

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“…With these properties, sliding mode control (SMC) is widely used in various applications, like the chemical industry [7][8][9][10], process control [11][12][13], power system [14] and biomedical processing [15]. Recently, some modified SMCs such as fixed-time terminal SMC (TSMC) [16][17][18] and predefined-time TSMC [19], are used in robotics control.…”

Section: Introductionmentioning

confidence: 99%

Sliding mode controller design for unstable processes with dead time with a case study on continuous stirred tank reactor

Ali,

Anwar

2023

Eng. Res. Express

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Unstable processes are difficult to control because one or more poles lie on right-hand side of the s-plane. The control becomes further complicated by the presence of dead time in such systems. In this study, sliding mode control (SMC) design is proposed for the control of unstable processes with dead time. To apply the SMC, a second order plus dead time (SOPDT) model of the unstable process is used and proportional-integral-derivative-derivative (PIDD) type sliding surface is considered. The parameters of continuous and discontinuous control laws are obtained using differential evolution (DE) optimization technique. The optimal control problem is solved by satisfying a new weighted bi-objective function constituting the performance index integral absolute error (IAE) and control input total variation (TV). The proposed control scheme has been extended satisfactorily to control the unstable integrating and higher order unstable processes with dead time by approximating them into unstable SOPDT model. The efficacy of the suggested scheme has been evaluated on several benchmark unstable industrial chemical processes including continuous stirred tank reactor (CSTR). Further, this scheme has been compared with recently reported works and the obtained results clearly demonstrate the effectiveness of the suggested controller.

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Time-Varying Nonsingular Terminal Sliding Mode control of Autonomous Surface Vehicle with predefined convergence time

Cited by 15 publications

References 34 publications

The Non-Singular Terminal Sliding Mode Control of Underactuated Unmanned Surface Vessels Using Biologically Inspired Neural Network

The Non-Singular Terminal Sliding Mode Control of Underactuated Unmanned Surface Vessels Using Biologically Inspired Neural Network

Adaptive Sliding Mode Control for Unmanned Surface Vehicles with Predefined-Time Tracking Performances

Sliding mode controller design for unstable processes with dead time with a case study on continuous stirred tank reactor

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