Predictive Control of a Supercavitating Vehicle Based on Time-Delay Characteristics

Han, Yuntao; Xu, Zhen; Guan, Lei

doi:10.1109/access.2020.3046517

Cited by 10 publications

(7 citation statements)

References 29 publications

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“…In order to further verify the effectiveness of the H∞ method, the controller designed in this paper is applied to the planing force model ( 1). The dynamic model can be rewritten as The model is a LPV time-delay model of supercavitating vehicle, and the specific parameters in the model are shown in (Han et al, 2020). The H∞ state feedback controller is constructed, and the simulation verification is carried out.…”

Section: Simulation For Lpv Time-delay Model Of Supercavitating Vehiclementioning

confidence: 99%

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H∞ robust control for underwater supercavitating vehicle with time delay

Zhao

Chen

Jing

et al. 2023

Journal of Vibration and Control

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According to Logvinovich cavity dependent expansion principle, a cavity developed by cavitator has memory effect, which arises cavity deformation at aft part of a supercavitating vehicle and leads time delay of travel state. This delay affects the dynamic behavior through changing hydrodynamic and moment on the control surface, and even induces instability. This paper focuses on the time delay effect of the underwater supercavitating vehicle, and a simplified dynamic model of underwater supercavitating vehicle with delay was established. First, a planing force was simplified in straight level state, then a simplified model of supercavitating vehicle with delay in longitude plane was obtained. Taking depth, pitch angle, vertical speed and pitch rate as state variant, [Formula: see text] state feedback controller was designed by linear matrix inequality (LMI) and Lyapunov stable theory was exploited to prove the asymptotic stability of the system. Simulation results show that, the controlled system is effectiveness for both simplified model and non-simplified model and it can track reference command signal.

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Section: Simulation For Lpv Time-delay Model Of Supercavitating Vehiclementioning

confidence: 99%

“…Mao et al (Mao and Qian, 2009) used Vanek's delayed LPV model, but the coordinate point of Mao's model is at the head of the vehicle. Han et al proposed a predictive control for supercavitating vehicle based on time-delay characteristics, and the dynamic performance of the system was investigated (Han et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

H∞ robust control for underwater supercavitating vehicle with time delay

Zhao

Chen

Jing

et al. 2023

Journal of Vibration and Control

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“…W. Z. et al [9] used a maneuvering supercavity model with a cavitation number correction algorithm, proposing an exact linearizing feedback controller and a linear quadratic regulator for simulating the level flight, climbing, and diving of the vehicle. H. Y. et al [10] established a linear parameter-varying (LPV) time-delay model for a supercavitating vehicle by analyzing the time-delay characteristics of the planing force, and designed a predictive controller based on the model.…”

Section: Introductionmentioning

confidence: 99%

Event-Triggered Supercavitating Vehicle Terminal Sliding Mode Control Based on Non-Recursive Observation

Zhang,

Wang,

Wang

et al. 2024

JMSE

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Supercavitating vehicles present significant issues in controller design due to their multiphase flow-coupling characteristics. This study addresses force analysis and the construction of a 6-degree-of-freedom mathematical model for a supercavitating vehicle. A terminal sliding mode control law is intended to guarantee the quick tracking of the command signal for high-precision attitude control. To drastically lower the frequency of actuation and communication, a mechanism to trigger events is also introduced into the control link. A disturbance observer, which estimates system uncertainty using a non-recursive differentiator, improves the robustness of the system. The Lyapunov approach is used to prove that the system is stable. Numerical simulation results validate that the proposed method enhances control accuracy and robustness. The event-trigger mechanism reduces the execution frequency to 18.59%, effectively reducing the communication burden.

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“…In the aspect of supercavitating vehicle modeling, the dynamic model contains 12 state variables and 6 degrees of freedom. Dzielski and Kurdila [1] proposed a dynamic benchmark model in the dive-plane which is widely adopted in the subsequent research [2][3][4][5][6], but the dynamic model in the reference [1] did not consider the cavity memory effect and the fin efficiency was set to a constant. Such simplifications more or less exist in the subsequent literatures.…”

Section: Introductionmentioning

confidence: 99%

Design of Particle Swarm Optimization Adaptive Sliding Mode Controller Based on an Extended State Observer for the Longitudinal Motion of a Supercavitating Vehicle with Input Saturation

Yang

et al. 2023

Journal of Sensors

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The aim of this paper is to present a novel sliding mode control scheme for the supercavitating vehicle trajectory tracking problem that subjects to external disturbances and actuator saturation with two symmetric elevators and a cavitator as actuators by analytical methods and computer simulations. Firstly, the nonlinear and highly coupled dynamic and kinematic models of a supercavitating vehicle are presented in a comprehensive way by taking the cavity memory effect and time-variant planing force into consideration. The PSO algorithm is employed to optimize the control parameters for achieving better and more practical tracking performance by minimizing the objective function. A second-order extended state observer (ESO) is utilized to estimate the unknown external and state-dependent disturbances and compensates for control inputs. In addition, an antiwindup compensator is adopted to cope with actuator saturation. Finally, the proposed control scheme is employed for complex trajectory tracking of a supercavitating vehicle under various conditions by conducting comparative numerical simulations. Rigorous theoretical analysis and simulation results indicate that the proposed control scheme can achieve satisfactory tracking performance and have a good capability of robustness.

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Predictive Control of a Supercavitating Vehicle Based on Time-Delay Characteristics

Cited by 10 publications

References 29 publications

H∞ robust control for underwater supercavitating vehicle with time delay

H∞ robust control for underwater supercavitating vehicle with time delay

Event-Triggered Supercavitating Vehicle Terminal Sliding Mode Control Based on Non-Recursive Observation

Design of Particle Swarm Optimization Adaptive Sliding Mode Controller Based on an Extended State Observer for the Longitudinal Motion of a Supercavitating Vehicle with Input Saturation

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