Observer-Based Adaptive Fuzzy Control for Intelligent Ship Autopilot with Input Saturation

Zhu, Liyan; Li, Tieshan; Yu, Ran; Wu, Yue; Ning, Jun

doi:10.1007/s40815-020-00880-3

Cited by 12 publications

(2 citation statements)

References 25 publications

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“…Since there are model errors and disturbances in the system, making some available states, causing poor control effect and even instability. The state observer is a dynamic system, which estimates the state variables according to feedback of the input and output errors of the controlled system and a state observer is incorporated to estimate the unmeasured states here, which is always an effective method to deal with unmodeled dynamics (Lin et al, 2020; Zhu et al, 2020).…”

Section: Adaptive Nn Controller Designmentioning

confidence: 99%

Observer-based adaptive neural network control for stabilized platform in rotary steerable system with unknown input dead-zone

Wan

Huang

Wang

et al. 2022

Transactions of the Institute of Measurement and Control

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The core task of the stabilized platform in the rotary steerable system is to control the toolface angle, so that the trajectory of the whole bit can move forward to the set direction. Due to many downhole interference factors, the uncertainties of parameters related to internal friction and interference torque of stabilized platform always exist, which poses great challenges to model establishment and controller design. Moreover, the actuator dead-zone nonlinearity makes the control more complicated. Hence, a dynamic model of stabilized platform considering a variety of nonlinear factors is established, and an observer-based adaptive neural network (NN)-control law is proposed. An NN state observer is developed to cope with the uncertain states composed of unknown friction parametric uncertainties and unmodeled disturbances, the dead-zone inverse is constructed to compensate for a dead-zone, and the dynamic surface control (DSC) strategy is used to solve the “differential explosion,” all signals in the system are proved to be semi-global uniformly ultimately bounded (SGUUB) by the Lyapunov function. Finally, the MATLAB simulation is set up, and the accurate tracking effect of the system is proved by the simulation in the presence of friction, modeling error, and dead-zone nonlinearity. The validity and the superior performance of the proposed control method under the downhole harsh environment and parameter perturbation is verified by the comparison simulation experiments.

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Section: Adaptive Nn Controller Designmentioning

confidence: 99%

Observer-based adaptive neural network control for stabilized platform in rotary steerable system with unknown input dead-zone

Wan

Huang

Wang

et al. 2022

Transactions of the Institute of Measurement and Control

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show abstract

“…This has increased the demand for advanced sensors for ship mechanical state and perceptual state monitoring [2]. Research institutions at home and abroad have conducted technical research on millimeter wave radar, stereo vision imaging, radar target detection, autopilot and other equipment and sensor algorithm fusion [3][4][5][6][7][8]. Literature [9] applies multispectral data to the field of ship target monitoring and combines the detection results with AIS, Provide supplementary information for ship identification.…”

Section: Introductionmentioning

confidence: 99%

Research on Maritime Navigation Perception Requirements of Intelligent Ships

Wang¹,

Gao²,

et al. 2022

J. Phys.: Conf. Ser.

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Aiming at the problem that in the research and development process of the intelligent ship perception system, the fuzzy understanding of the perception demand causes the perception equipment to be inconsistent with the ship’s autonomous collision avoidance needs, based on the application practice of the 1972 “International Maritime Collision Avoidance Regulations” and the good marine craftsmanship of the mariners Based on the comparison and experience summary method, the ship pilot’s perception of navigation obstacles is analyzed, and the requirements for intelligent ship navigation perception at sea are proposed from five aspects: vision, ARPA radar, AIS, human-computer interaction, and electronic chart, it can provide theoretical support for the research of intelligent ship sensing system.

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Grey Wolf Optimization Based Active Disturbance Rejection Control Parameter Tuning for Ship Course

Ren

Chen

Yang

et al. 2022

Int. J. Control Autom. Syst.

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Observer-Based Adaptive Fuzzy Control for Intelligent Ship Autopilot with Input Saturation

Cited by 12 publications

References 25 publications

Observer-based adaptive neural network control for stabilized platform in rotary steerable system with unknown input dead-zone

Observer-based adaptive neural network control for stabilized platform in rotary steerable system with unknown input dead-zone

Research on Maritime Navigation Perception Requirements of Intelligent Ships

Grey Wolf Optimization Based Active Disturbance Rejection Control Parameter Tuning for Ship Course

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