UDE based backstepping design for ship autopilot

Das, Swarup; Bhatt, Aditi; Talole, S. E.

doi:10.1109/iic.2015.7150778

Cited by 11 publications

(3 citation statements)

References 27 publications

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“…A UDE-based backstepping controller for autopiloted ships was proposed in Ref. 24, by making full use of the merit of cascade structures, but the actuator is assumed to be ideal in this study.…”

Section: Introductionmentioning

confidence: 99%

Cascade-modified uncertainty and disturbance estimator–based control of quadrotors for accurate attitude tracking under exogenous disturbance

Qin¹,

Wang²,

Liu³

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part G:

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This paper presents a cascade-modified uncertainty and disturbance estimator (CMUDE)–based controller. The attitude-tracking performance of a quadrotor would be greatly degraded due to two factors: (1) a nonideal actuator and (2) an exogenous disturbance. Based on these factors, an actuator model is accurately identified using a thrust test platform. Then, a cascade-structured CMUDE controller is designed through the backstepping method, so the disturbances from different channels can be separately dealt with. The idea of the uncertainty and disturbance estimator (UDE) is then applied to dynamically compensate for not only the exogenous disturbance but also the time delay in the actuator dynamics. Benefitting from that, the problem of mismatched disturbances is solved by defining virtual control inputs; furthermore, the nonlinear term in the attitude kinematics is included in the model uncertainty to be canceled instead of being ignored. When tracking attitude commands, the exogenous disturbance and model uncertainty along with the time delay of the actuator are estimated and compensated for by the proposed controller, so the performance of the disturbance rejection is significantly improved while maintaining a quick response to the rapidly changing commands. To verify that, the proposed controller is implemented on a quadrotor platform to carry out exhaustive experiments and compared with the mainstream cascade PID (CPID) controller, the classic UDE-based controller, and the latest modified-UDE (MUDE)–based controller. The results show that our control strategy achieves a better disturbance rejection and more accurate tracking performance than other controllers.

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Section: Introductionmentioning

confidence: 99%

Cascade-modified uncertainty and disturbance estimator–based control of quadrotors for accurate attitude tracking under exogenous disturbance

Qin¹,

Wang²,

Liu³

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part G:

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show abstract

“…The solutions to this problem mainly include back-stepping, sliding mode control (SMC) and H ∞ control and so on (Wang et al, 2017). As a feasible and typical nonlinear control method, the back-stepping method (Das et al, 2015; Dong et al, 2011) can consider the uncertainty of parameters through the recursive design procedure, and is a powerful way to deal with the uncertainty. In Witkowska et al (2007), the authors design the nonlinear control rules for course control system by using the back-stepping method.…”

Section: Introductionmentioning

confidence: 99%

Robust H∞ control for nonlinear course system of unmanned surface vessel with polytopic uncertainty based on sum of squares

Huang

Zhenyi

Huang

et al. 2020

Transactions of the Institute of Measurement and Control

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In this paper, the nonlinear robust [Formula: see text] control is investigated for nonlinear course control systems of unmanned surface vessel (USV) with uncertain parameters and external disturbance. Firstly, we suppose that the part or all of the system parameters are unknown but within some ranges, due to the effect of different conditions such as the loading of ship. Then, the course system is modeled as a polynomial one with time invariant polytopic uncertainty. With the aid of parameter dependent Lyapunov function method and positive polynomial theory, the sufficient conditions are given for stability and stabilization with [Formula: see text] performance. These conditions are formulated in terms of parameter-dependent nonlinear matrix inequalities which can be verified by semidefinite programming relaxations based on the sum of squares technique. Finally, simulation results show the effectiveness of the approach.

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“…In addition, the controller parameters are required adjustments in varying conditions, which are time consuming and may not achieve accurate control performance. To solve the issues and obtain better performance, various advanced control strategies have been proposed for the steering control of the ship in recent years, such as adaptive steering control strategy [6][7][8], steering control strategy based on fuzzy logic algorithm [9,10], steering controller based on Backstepping controller design method [11][12][13], and adaptive backstepping method [14,15].…”

Section: Introductionmentioning

confidence: 99%

Ship Steering Control Based on Quantum Neural Network

Guan

Zhou

et al. 2019

Complexity

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During the mission at sea, the ship steering control to yaw motions of the intelligent autonomous surface vessel (IASV) is a very challenging task. In this paper, a quantum neural network (QNN) which takes the advantages of learning capabilities and fast learning rate is proposed to act as the foundation feedback control hierarchy module of the IASV planning and control strategy. The numeric simulations had shown that the QNN steering controller could improve the learning rate performance significantly comparing with the conventional neural networks. Furthermore, the numeric and practical steering control experiment of the IASV BAICHUAN has shown a good control performance similar to the conventional PID steering controller and it confirms the feasibility of the QNN steering controller of IASV planning and control engineering applications in the future.

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UDE based backstepping design for ship autopilot

Cited by 11 publications

References 27 publications

Cascade-modified uncertainty and disturbance estimator–based control of quadrotors for accurate attitude tracking under exogenous disturbance

Cascade-modified uncertainty and disturbance estimator–based control of quadrotors for accurate attitude tracking under exogenous disturbance

Robust H∞ control for nonlinear course system of unmanned surface vessel with polytopic uncertainty based on sum of squares

Ship Steering Control Based on Quantum Neural Network

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