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Impulse-based control of joints and muscles
Rachel Weinstein1, Eran Guendelman, Ronald Fedkiw
1Department of Computer Science, Stanford University and Industrial Light & Magic, San Francisco, CA 94129, USA. rachellw@graphics.stanford.edu
IEEE Transactions on Visualization and Computer Graphics
|November 13, 2007
Summary
This study introduces a new proportional derivative (PD) control method that analytically solves control equations for isolated joints. This approach decouples joint stiffness from control, ensuring desired targets are met regardless of stiffness.
Area of Science:
- Robotics and Control Systems
- Mechanical Engineering
- Applied Mathematics
Background:
- Traditional proportional derivative (PD) control methods face challenges with coupled dynamics, external forces, and joint stiffness.
- Existing approaches often struggle to achieve precise control without interference from complex system interactions.
Purpose of the Study:
- To develop a novel analytical approach for proportional derivative (PD) control.
- To decouple joint stiffness from control, ensuring target achievement irrespective of joint properties.
- To demonstrate the method's efficacy in complex systems, including muscle actuators.
Main Methods:
- Exploiting the analytical solvability of PD control equations for single degrees of freedom.
- Implementing an inverse dynamics formulation within the time integration process.
- Incorporating global feedback to ensure per-joint predictions are achieved.
Main Results:
- The analytical solution reveals the isolated behavior of PD controllers.
- The proposed method effectively decouples joint stiffness from control outcomes.
- Demonstrated successful application in simple and complex scenarios, including line segment muscle actuators.
Conclusions:
- The novel analytical PD control approach offers precise control by isolating joint dynamics.
- Decoupling stiffness from control simplifies system design and enhances robustness.
- This method provides a foundation for advanced control strategies in robotics and biomechanics.
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