Neural Network–Based Efficient Hybrid Control Scheme for the Tracking Control of Autonomous Underwater Vehicles

Rani, Manju; Kumar, Naveen; Dahiya, Anita

doi:10.1201/9781003355960-2

Cited by 1 publication

(2 citation statements)

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“…Therefore, the Assumptions 1-2 are reasonable. Similar assumption is also given in [5,6,18,21,26,51,52,53].…”

Section: Definitionmentioning

confidence: 67%

“…USVs sailing in the sea require to interact with uncertainties and complex environment disturbances induced by wind, waves, and currents, which greatly increase the design difficulty of controller and remarkably affect the control performance [2,3]. For the USVs control, one of the key issues is how to handle multiple uncertainties and unknown disturbances, and researchers ⋆ This work was supported by Key project of Heilongjiang Natural Science Foundation (NO.ZD2022F001) have made a tremendous endeavors and proposed many related methods such as fuzzy control [4], neural network (NN) control [5], disturbance attenuation control [6], adaptive control [7], reinforcement learning [8], sliding mode control (SMC) [9], etc. Among them, the advantages of SMC are good robustness and transient response.…”

Section: Introductionmentioning

confidence: 99%

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Observer-based practical predefined-time control for unmanned surface vehicles with guaranteed performance: A novel integral sliding mode approach

Cai,

Zhao,

Feng

et al. 2024

Preprint

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This paper investigates practical predefined-time trajectory tracking control problem with guaranteed performance for unmanned surface vehicles (USVs) suffering from dynamic uncertainties and unknown disturbances. A observer-based practical predefined-time integral sliding mode control scheme is proposed. Salient features are as follows. First, by devising a practical predefined-time extended state observer, lumped disturbances arising from uncertainties and external disturbances can be exactly identified within the expected predefined-time, in conjunction with the fuzzy logic systems, and thereby improving the disturbance rejection property of USVs. Then, a nonsingular predefined-time integral sliding mode (NPTISM) surface is proposed using a class of time-dependent scaling function, and the NPTISM surface has only the sliding phase, while the reaching phase is eliminated. Besides, a novel-type prescribed performance function is introduced into the controller to characterize transient and steady-state performances, simultaneously. A rigorous stability analysis guarantees that practical predefined-time stability of the system, and the upper bound of settling time can be precisely set by only a single parameter in advance. Finally, the simulation results and comparisons are carried out to validate the proposal.

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“…Therefore, the Assumptions 1-2 are reasonable. Similar assumption is also given in [5,6,18,21,26,51,52,53].…”

Section: Definitionmentioning

confidence: 67%

Section: Introductionmentioning

confidence: 99%

Observer-based practical predefined-time control for unmanned surface vehicles with guaranteed performance: A novel integral sliding mode approach

Cai,

Zhao,

Feng

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

Neural Network–Based Efficient Hybrid Control Scheme for the Tracking Control of Autonomous Underwater Vehicles

Cited by 1 publication

References 0 publications

Observer-based practical predefined-time control for unmanned surface vehicles with guaranteed performance: A novel integral sliding mode approach

Observer-based practical predefined-time control for unmanned surface vehicles with guaranteed performance: A novel integral sliding mode approach

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