An Approach to Reduce Computational Load: Precalculating Gain Matrices for an LQR Controller of a Four-Axis Manipulator Using State Space Kinematics

Alistair Keiller

An Approach to Reduce Computational Load: Precalculating Gain Matrices for an LQR Controller of a Four-Axis Manipulator Using State Space Kinematics

Robotics 2023-12-25 v1 Systems and Control Systems and Control

Authors: Alistair Keiller

Abstract

When designing a power or CPU constrained device where a four-axis robotic arm is required and access to the Robot Operating System (ROS) is not an option, finding an efficient state space controller for a four-axis arm can be an obstacle. In this paper, I explore a method to optimize the computing power required for a computer algebra system (CAS) to compute linear quadratic regulator (LQR) matrices by precomputing the gain matrix for different states. Example C++ code is provided on Github, along with ideas for further exploration.

Keywords

computational load reduction gain matrix precalculation LQR controller four-axis manipulator state space kinematics robotic arm control

Cite

@article{arxiv.2312.14525,
  title  = {An Approach to Reduce Computational Load: Precalculating Gain Matrices for an LQR Controller of a Four-Axis Manipulator Using State Space Kinematics},
  author = {Alistair Keiller},
  journal= {arXiv preprint arXiv:2312.14525},
  year   = {2023}
}

Comments

The corresponding code is available here: https://github.com/AlistairKeiller/RobotIK 7 pages, 5 figures

An Approach to Reduce Computational Load: Precalculating Gain Matrices for an LQR Controller of a Four-Axis Manipulator Using State Space Kinematics

Abstract

Keywords

Cite

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