Hovercraft Control With Dynamic Parameters Identification

Cabecinhas, David; Batista, Pedro; Oliveira, Paulo; Silvestre, Carlos

doi:10.1109/tcst.2017.2692733

Cited by 25 publications

(37 citation statements)

References 7 publications

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“…A hovercraft, which is known as an underactuated system and named an air cushion vehicle (ACV), has rotors and a cushion, where inside air pressure enables floating and smooth movement on any surface [26][27][28][29][30][31], such as land, mud, water, sand, and even on ice. The hovercraft is very active and agile; hence, it is applied widely in the coastguard, army, rescue operations, civil engineering, etc.…”

Section: Hovercraft Prototype Modelmentioning

confidence: 99%

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Improved Genetic Algorithm Tuning Controller Design for Autonomous Hovercraft

et al. 2020

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By mimicking the biological evolution process, genetic algorithm (GA) methodology has the advantages of creating and updating new elite parameters for optimization processes, especially in controller design technique. In this paper, a GA improvement that can speed up convergence and save operation time by neglecting chromosome decoding step is proposed to find the optimized fuzzy-proportional-integral-derivative (fuzzy-PID) control parameters. Due to minimizing tracking error of the controller design criterion, the fitness function integral of square error (ISE) was employed to utilize the advantages of the modified GA. The proposed method was then applied to a novel autonomous hovercraft motion model to display the superiority to the standard GA.

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Section: Hovercraft Prototype Modelmentioning

confidence: 99%

“…A hovercraft, also known as an air cushion vehicle (ACV), moves smoothly on any surface [26][27][28][29][30][31] from the ground-land to the mud, water, sand, and even on ice. Because a hovercraft is very active and agile, its models was chosen for the control implementation.…”

Section: Introductionmentioning

confidence: 99%

Improved Genetic Algorithm Tuning Controller Design for Autonomous Hovercraft

et al. 2020

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“…Parameters identifications are also be populated for frequently usage in various engineering such as hovercraft system, robot system, vehicle engines, and Wiener system . However, parameters identifications only be suited to some class of known structured model systems in other works . Although some novel adaptive parameter estimation control schemes were constructed for the unknown robotic system in the work of Na et al, the assumption of persistent excitation condition is necessary to be known beforehand.…”

Section: Introductionmentioning

confidence: 99%

“…[1][2][3] For example, in the work of Yang et al, 4 an intelligence shared control system with brain computer interface was developed to achieve accurate object for robot manipulator system, in which the user's mind is regarded as a commander. Parameters identifications are also be populated for frequently usage in various engineering such as hovercraft system, 5 robot system, 6,7 vehicle engines, 8 and Wiener system. 9 However, parameters identifications only be suited to some class of known structured model systems in other works.…”

Section: Introductionmentioning

confidence: 99%

“…9 However, parameters identifications only be suited to some class of known structured model systems in other works. 5,6,8,9 Although some novel adaptive parameter estimation control schemes were constructed for the unknown robotic system in the work of Na et al, 7 the assumption of persistent excitation condition is necessary to be known beforehand. In many real applications, unknown nonlinearities and unstructured uncertainties in complex dynamical systems are inevitable existed; neural network space (NNs) and fuzzy logic systems (FLS) have been received much more attention since they are the two powerful artificial intelligent instruments to deal with uncertainties or unknown model in nonlinear complex dynamic systems.…”

Section: Introductionmentioning

confidence: 99%

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Neural adaptive global stability control for robot manipulators with time‐varying output constraints

Fan

Kang

Wang

et al. 2019

Intl J Robust & Nonlinear

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Summary In this paper, a novel adaptive control scheme is proposed based on radial basis function neural network (RBFNN). The considered system is deduced by the structure of RBFNN with nonzero time‐varying parameter that installed in the fore‐end and terminal of RBFNN. With this structure and the Taylor expansion of any smooth continuous nonlinear function, a universal approximation of RBFNN is addressed according to the analysis of the character of continuous homogenous function and the Euler's theorem. The approximation accuracies can be adjusted online by the nonzero time‐varying parameter in the device with the degree of continuous homogenous function, which expand the semiglobally stability to global stability over conventional neural controller design approaches. Based on the theory analysis of barrier Lyapunov function, the violation of time‐varying constraints can be subjugated without wrecked. Finally, simulation results are carried out to verify the effectiveness by the design methods.

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Robust practical tracking control of an underactuated hovercraft

Yan

Xie

2021

Asian Journal of Control

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This paper studies the robust practical tracking control problem of an underactuated hovercraft with unknown external disturbances. Controlling such a system is difficult and challenging due to inherent modeling properties such as underactuated nature and nonholonomic constraint. State transformation technique and cascade method, combined with a transverse function, are used to develop a novel control law that globally practically stabilizes the hovercraft to any smooth reference trajectory, either feasible or non-feasible. The Lyapunov theory is applied to the analysis of overall closed-loop stability. Simulation results illustrate the control design.

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Hovercraft Control With Dynamic Parameters Identification

Cited by 25 publications

References 7 publications

Improved Genetic Algorithm Tuning Controller Design for Autonomous Hovercraft

Improved Genetic Algorithm Tuning Controller Design for Autonomous Hovercraft

Neural adaptive global stability control for robot manipulators with time‐varying output constraints

Robust practical tracking control of an underactuated hovercraft

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