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Related Concept Videos

Mechanical Systems01:22

Mechanical Systems

339
Mechanical systems are analogous to to electrical networks where springs and masses play similar roles to inductors and capacitors, respectively. A viscous damper in mechanical systems functions similarly to a resistor in electrical networks, dissipating energy. The forces acting on a mass in such systems include an applied force in the direction of motion, counteracted by forces from the spring, a viscous damper, and the mass's acceleration. This interplay of forces is mathematically...
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Three-Dimensional Force System:Problem Solving01:30

Three-Dimensional Force System:Problem Solving

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A three-dimensional force system refers to a scenario in which three forces act simultaneously in three different directions. This type of problem is commonly encountered in physics and engineering, where it is necessary to calculate the resultant force on the system, which can then be used to predict or analyze the behavior of the object or structure under consideration.
To solve a three-dimensional force system, first resolve each force into its respective scalar components. Do this using...
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Linear Approximation in Time Domain01:21

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Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
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Two-Dimensional Force System: Problem Solving01:29

Two-Dimensional Force System: Problem Solving

801
Solving problems related to two-dimensional force systems is an essential aspect of mechanics and engineering. By applying the principles of vector analysis and force equilibrium, one can determine the effect of multiple forces acting on an object in a two-dimensional space.
The first step to solving a two-dimensional force system problem is to draw a free-body diagram of the object under consideration. This diagram helps identify all the external forces acting on the object, including their...
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Second Order systems I01:20

Second Order systems I

275
A servo system exemplifies a second-order system, featuring a proportional controller and load elements that ensure the output position aligns with the input position. The relationship between these components is described by a second-order differential equation. Applying the Laplace transform under zero initial conditions yields the transfer function, showing how inputs are converted to outputs in the system.
By reinterpreting the system, one can derive the closed-loop transfer function, which...
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PD Controller: Design01:26

PD Controller: Design

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In automotive engineering, car suspension systems often employ Proportional Derivative (PD) controllers to enhance performance. PD controllers are utilized to adjust the damping force in response to road conditions. A controller, acting as an amplifier with a constant gain, demonstrates proportional control, with output directly mirroring input.
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Automatic Laser-based Geometry Capture for Finite Element Analysis of Weld Beads
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Data-driven geometric system identification for shape-underactuated dissipative systems.

Brian Bittner1,2, Ross L Hatton3, Shai Revzen1,4

  • 1Robotics Institute, University of Michigan, Ann Arbor, United States of America.

Bioinspiration & Biomimetics
|November 19, 2021
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Summary
This summary is machine-generated.

This study introduces a new modeling approach for shape-underactuated dissipative systems (SUDS), simplifying motion optimization for systems like micro-swimmers and soft robots. The method enhances model identification efficiency, reducing trials needed for robotics and organismal motion studies.

Keywords:
dissipative systemssoft roboticssystem identificationviscous swimmers

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Area of Science:

  • Robotics
  • Geometric Mechanics
  • System Dynamics

Background:

  • Modeling system dynamics is challenging when component properties are unmeasurable.
  • Dissipative systems offer unique opportunities for easier model identification and motion optimization.
  • Existing geometric mechanics tools are extended to shape-underactuated dissipative systems (SUDS).

Purpose of the Study:

  • To extend geometric system identification tools to shape-underactuated dissipative systems (SUDS).
  • To demonstrate the applicability of SUDS models to various animal and soft robot motions.
  • To develop a method for efficient system identification and motion optimization in dissipative systems.

Main Methods:

  • Geometric mechanics for dynamics reduction.
  • System identification tailored for shape-underactuated dissipative systems (SUDS).
  • Conversion of shape velocity actuation inputs to torque inputs for modeling.

Main Results:

  • SUDS models effectively predict motion for simulated viscous swimming platforms.
  • Shape velocity actuation can be directly converted to torque inputs for modeling.
  • Model complexity scales linearly with passive shape coordinates, reducing identification trials and overfitting.

Conclusions:

  • The developed SUDS modeling approach simplifies identification and optimization for dissipative systems.
  • This method is applicable to diverse systems, including micro-swimmers, granular locomotors, and soft robots.
  • The sample efficiency of the method is valuable for robotics, control, optimization, and studying organismal motion.