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Search Results (3)

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Keywords = coupled motion kinematics and extension dynamics

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22 pages, 2922 KB  
Article
Fuzzy Adaptive PID-Based Tracking Control for Autonomous Underwater Vehicles
by Shicheng Fan, Haoming Wang, Changyi Zuo and Junqiang Han
Actuators 2025, 14(10), 470; https://doi.org/10.3390/act14100470 - 26 Sep 2025
Cited by 1 | Viewed by 880
Abstract
This paper addresses the trajectory tracking control problem of Autonomous Underwater Vehicles (AUVs). A comprehensive mathematical model is first established based on Newtonian mechanics, incorporating both kinematic and dynamic equations. By reasonably neglecting the minor influence of roll motion, a five-degree-of-freedom (5-DOF) underactuated [...] Read more.
This paper addresses the trajectory tracking control problem of Autonomous Underwater Vehicles (AUVs). A comprehensive mathematical model is first established based on Newtonian mechanics, incorporating both kinematic and dynamic equations. By reasonably neglecting the minor influence of roll motion, a five-degree-of-freedom (5-DOF) underactuated AUV model is derived. Considering the strong nonlinearities, high coupling, and time-varying hydrodynamic parameters typical of underwater environments, a fuzzy adaptive PID controller is proposed. This controller combines the adaptability of fuzzy logic with the structural simplicity and reliability of PID control, making it well-suited to the demanding requirements of AUV motion control. Extensive simulation experiments are conducted to evaluate the controller’s performance under various operating conditions. The results show that the fuzzy adaptive PID controller significantly outperforms conventional PID and standalone fuzzy logic controllers in terms of convergence speed and oscillation suppression. Furthermore, a theoretical stability analysis is provided to ensure that the proposed control system remains stable under time-varying fuzzy gain scheduling, confirming its effectiveness and potential for practical application in underwater vehicle control. Full article
(This article belongs to the Section Control Systems)
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19 pages, 7266 KB  
Article
In Vivo Measurement of Wrist Movements during the Dart-Throwing Motion Using Inertial Measurement Units
by Gabriella Fischer, Michael Alexander Wirth, Simone Balocco and Maurizio Calcagni
Sensors 2021, 21(16), 5623; https://doi.org/10.3390/s21165623 - 20 Aug 2021
Cited by 4 | Viewed by 3583
Abstract
Background: This study investigates the dart-throwing motion (DTM) by comparing an inertial measurement unit-based system previously validated for basic motion tasks with an optoelectronic motion capture system. The DTM is interesting as wrist movement during many activities of daily living occur in this [...] Read more.
Background: This study investigates the dart-throwing motion (DTM) by comparing an inertial measurement unit-based system previously validated for basic motion tasks with an optoelectronic motion capture system. The DTM is interesting as wrist movement during many activities of daily living occur in this movement plane, but the complex movement is difficult to assess clinically. Methods: Ten healthy subjects were recorded while performing the DTM with their right wrist using inertial sensors and skin markers. Maximum range of motion obtained by the different systems and the mean absolute difference were calculated. Results: In the flexion–extension plane, both systems calculated a range of motion of 100° with mean absolute differences of 8°, while in the radial–ulnar deviation plane, a mean absolute difference of 17° and range of motion values of 48° for the optoelectronic system and 59° for the inertial measurement units were found. Conclusions: This study shows the challenge of comparing results of different kinematic motion capture systems for complex movements while also highlighting inertial measurement units as promising for future clinical application in dynamic and coupled wrist movements. Possible sources of error and solutions are discussed. Full article
(This article belongs to the Special Issue Advances in Inertial Sensors)
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19 pages, 1628 KB  
Article
Tracking of Maneuvering Complex Extended Object with Coupled Motion Kinematics and Extension Dynamics Using Range Extent Measurements
by Lifan Sun, Baofeng Ji, Jian Lan, Zishu He and Jiexin Pu
Sensors 2017, 17(10), 2184; https://doi.org/10.3390/s17102184 - 22 Sep 2017
Cited by 2 | Viewed by 4778
Abstract
The key to successful maneuvering complex extended object tracking (MCEOT) using range extent measurements provided by high resolution sensors lies in accurate and effective modeling of both the extension dynamics and the centroid kinematics. During object maneuvers, the extension dynamics of an object [...] Read more.
The key to successful maneuvering complex extended object tracking (MCEOT) using range extent measurements provided by high resolution sensors lies in accurate and effective modeling of both the extension dynamics and the centroid kinematics. During object maneuvers, the extension dynamics of an object with a complex shape is highly coupled with the centroid kinematics. However, this difficult but important problem is rarely considered and solved explicitly. In view of this, this paper proposes a general approach to modeling a maneuvering complex extended object based on Minkowski sum, so that the coupled turn maneuvers in both the centroid states and extensions can be described accurately. The new model has a concise and unified form, in which the complex extension dynamics can be simply and jointly characterized by multiple simple sub-objects’ extension dynamics based on Minkowski sum. The proposed maneuvering model fits range extent measurements very well due to its favorable properties. Based on this model, an MCEOT algorithm dealing with motion and extension maneuvers is also derived. Two different cases of the turn maneuvers with known/unknown turn rates are specifically considered. The proposed algorithm which jointly estimates the kinematic state and the object extension can also be easily implemented. Simulation results demonstrate the effectiveness of the proposed modeling and tracking approaches. Full article
(This article belongs to the Special Issue Advances in Multi-Sensor Information Fusion: Theory and Applications 2017)
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