Adaptive tracking control of unmanned underwater vehicles with compensation for external perturbations and uncertainties using Port-Hamiltonian theory

Jia, Zehua; Qiao, Lei; Zhang, Guoqing

doi:10.1016/j.oceaneng.2020.107402

Cited by 30 publications

(7 citation statements)

References 19 publications

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“…Although the adaptation law has been formulated using a regressor based technique, which utilizes the desired state, the proposed control scheme provides consistent estimations of the hydrodynamic uncertainties in different conditions. To extend the applications of the theoretical Port-Hamiltonian concept, a UUV tracking control problem has been formulated using this theory in Jia et al (2020). From the signal processing point of view, the proposed scheme can be easily implemented on real UUVs.…”

Section: Model-based Schemesmentioning

confidence: 99%

A survey on tracking control of unmanned underwater vehicles: Experiments-based approach

Tijjani

Chemori

Creuze

2022

Annual Reviews in Control

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Section: Model-based Schemesmentioning

confidence: 99%

A survey on tracking control of unmanned underwater vehicles: Experiments-based approach

Tijjani

Chemori

Creuze

2022

Annual Reviews in Control

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“…These challenges drive the necessity for robust control systems. Various robust underwater vehicle control methods such as nonlinear model-based control [5][6][7][8], sliding mode control [4,9,10], and passivity-based control [11][12][13] have been developed to account for uncertain discrepancies in the system's control model parameters or measured state. There are also variants of these control methods with adaptive terms for increased robustness to uncertainties and system variations [14][15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Addressing Actuator Saturation during Fault Compensation in Model-Based Underwater Vehicle Control

Macatangay,

Hoseinnezhad,

Fowler

et al. 2023

Electronics

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Robust control systems are a necessity for autonomous underwater vehicle (AUV) systems due to the challenges they face during operation. Many AUV control-design methods have been developed for different actuator configurations, with robustness against model parameter uncertainties, environmental disturbances, and system faults. Actuator faults can reduce the physical capabilities of a system, which can be compensated for through control re-allocation. However, the increased control allocation to the remaining actuators may cause actuator saturation and reduce controller performance. In this work, we present a depth-pitch model-based nonlinear control law that directly considers actuator saturation, and a fault-tolerant control allocation method for a hybrid AUV actuator configuration. Two types of actuator faults are considered for an underwater vehicle with a hybrid actuator configuration. The proposed controller is implemented in a simulated system, and its trajectory tracking performance is compared with a baseline system without fault or saturation tolerance. To determine the utility of the proposed saturation and fault tolerance control methods, the tracking performance in these simulations is quantified in terms of the settling time, post-fault peak values, and root mean square of the depth and pitch errors.

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“…For realizing true unmanned driving, it is necessary to dynamically adjust the parameters of the controller (Cervantes-Rojas et al, 2020) to suit the speed, load changes, and external disturbances of different winds and waves of the USV. The adaptive control system can continuously detect changes in system parameters or operating indicators, thereby changing the control parameters or the role of control, and making the system run in an optimal or close to an optimal working state (Jia et al, 2020). The system parameters of the USV course response model are uncertain and time-varying (Chu et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

A Sigmoid-plane adaptive control algorithm for unmanned surface vessel considering marine environment interference

Luo

Guo

et al. 2022

Transactions of the Institute of Measurement and Control

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This article presents an application of a Sigmoid-plane (S-plane) adaptive control algorithm to an automatic steering system in the presence of uncertain parametric of the unmanned surface vessel (USV) and the unknown disturbance of the marine environment. Due to technical difficulties such as sensor noise, the marine environment disturbance is assumed to be unmeasured. To overcome this problem, an S-plane control is designed to resist marine environment disturbances by the improved adaptive term. Based on the gradient method, the USV heading model reference adaptive controller of the USV is designed, so that the USV has a certain ability to resist model parameter changes. Considering the uncertainty of marine environment interference, a model-reference-based S-plane adaptive controller for the USV is designed. After the reference of the USV course model, the S-plane adaptive control approach is employed to reduce the effect of the marine environment. It is proved that the USV course control system is stable, despite the adverse bad sea conditions. Finally, the course control simulation experiment for the USV with the unknown marine environmental interference is carried out. To demonstrate the benefits of the S-plane adaptive controller, the results are presented in comparison with a Lyapunov method controller. The results show that the S-plane adaptive controller is robust to the changed model parameter and external disturbances.

show abstract

Adaptive tracking control of unmanned underwater vehicles with compensation for external perturbations and uncertainties using Port-Hamiltonian theory

Cited by 30 publications

References 19 publications

A survey on tracking control of unmanned underwater vehicles: Experiments-based approach

A survey on tracking control of unmanned underwater vehicles: Experiments-based approach

Addressing Actuator Saturation during Fault Compensation in Model-Based Underwater Vehicle Control

A Sigmoid-plane adaptive control algorithm for unmanned surface vessel considering marine environment interference

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