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When analyzing one-dimensional motion with constant acceleration, the problem-solving strategy involves identifying the known quantities and choosing the appropriate kinematic equations to solve for the unknowns. Either one or two kinematic equations are needed to solve for the unknowns, depending on the known and unknown quantities. Generally, the number of equations required is the same as the number of unknown quantities in the given example. Two-body pursuit problems always require two...
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When an object moves with constant acceleration, the velocity of the object changes at a constant rate throughout the motion. The kinematic equations of motions are derived for such cases where the acceleration of the object is constant. The first kinematic equation gives an insight into the relationship between velocity, acceleration, and time. We can see, for example:
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The first two kinematic equations have time as a variable, but the third kinematic equation is independent of time. This equation expresses final velocity as a function of the acceleration and distance over which it acts. The fourth kinematic equation does not have an acceleration term and provides the final position of the object at time t in terms of the initial and final velocities. This equation is useful when the value of the constant acceleration is unknown.
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The second kinematic equation expresses the final position of an object in terms of its initial position, the distance traveled with the initial constant velocity, and the distance traveled due to a change in velocity. Similar to the first kinematic equation, this equation is also only valid when the acceleration is constant throughout the motion of an object.
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Modeling and Robust Control of a 5 DOF Model for Rowing Motion by Inverse Dynamics Method.

Amin Aref Adib1, Seyyed Arash Haghpanah1

  • 1School of Mechanical Engineering, Shiraz University, Shiraz, Iran.

Journal of Biomedical Physics & Engineering
|October 23, 2023
PubMed
Summary

This study developed a robust control system for simulating human rowing motion, ensuring joint torques remain within physiological limits for improved athletic performance and robotic design.

Keywords:
BiomechanicsMotionsNonlinear DynamicsRobust ControlRowing

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Area of Science:

  • Biomechanics
  • Robotics
  • Sports Science

Background:

  • Competitive sailing demands precise coordination and efficient force application.
  • Joint torques generated by muscles are critical for effective body movement and performance.

Purpose of the Study:

  • To simulate human rowing motion using a 5-DOF model.
  • To develop a control law for joint torques to accurately track desired movement paths.

Main Methods:

  • Employed an inverse dynamics control approach based on the Lagrange method.
  • Utilized a Proportional-Integral-Derivative (PID) control scheme for robust tracking of experimental joint angles.

Main Results:

  • Simulation demonstrated the effectiveness of the proposed inverse dynamics control method.
  • Achieved low joint settling times (under 3.75s per cycle) and torques within physiological ranges.

Conclusions:

  • The developed model accurately analyzes human movement in rowing.
  • Findings support applications in biomechanical engineering, robotic arm design for rowing, and improving athletic technique.