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A stroke engine has a slider-crank mechanism that converts rotational motion from the crank into linear motion of the slider or vice versa. This mechanism consists of three main parts: the crank, the connecting rod, and the slider.
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A slider-crank mechanism converts rotational motion from the crank into linear motion of the slider or vice versa. This mechanism consists of three main parts: the crank, the connecting rod, and the slider. The movement of the slider-crank is an example of general plane motion as the fluctuating angle between the crank and the connecting rod. Consider a segment AB where point A is at the end of the slider and point B is on the diametrically opposite end to point A, on a crack. The variance in...
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Consider a component AB undergoing a linear motion. Along with a linear motion, point B also rotates around point A. To comprehend this complex movement, position vectors for both points A and B are established using a stationary reference frame. The absolute velocity of point B is determined by adding the absolute velocity of point A, the relative velocity of point B in the rotating frame, and the effects caused by the angular velocity within the rotating frame.
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Bearing-Based Formation Tracking Control With Time-Varying Velocity Estimation.

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    This study presents a novel control scheme for multi-agent systems to achieve formation tracking using only relative orientation information. The method effectively estimates unknown velocity amplitudes, ensuring stable formation control.

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    Area of Science:

    • Robotics
    • Control Theory
    • Distributed Systems

    Background:

    • Formation tracking control is crucial for multi-agent systems.
    • Existing methods often require full velocity information, limiting practical applications.

    Purpose of the Study:

    • To address the bearing-based formation tracking control problem for multiple double-integrator agents.
    • To develop a control scheme that uses limited information (orientation) and estimates unknown parameters.

    Main Methods:

    • A velocity-estimation-based control scheme is proposed.
    • Includes an estimator for reference orientation rate and an adaptation law for reference velocity amplitude.
    • Utilizes bearing-based control inputs and auxiliary distance measurements for scaling formation.

    Main Results:

    • Estimation and control errors converge to zero under specific network conditions.
    • The closed-loop system demonstrates semiglobal uniform asymptotic stability.
    • Numerical simulations validate the proposed method's effectiveness.

    Conclusions:

    • The proposed method enables robust bearing-based formation tracking with partial and unknown information.
    • It advances control strategies for multi-agent systems in complex scenarios.
    • The approach ensures stability and accurate formation maneuvers.