Manipulator Adaptive Control

Python package containing adaptive controllers for use on robotic manipulators.

Controllers

Radial Basis Function Neural Network (RBFNN) Controller

Given manipulator dynamics of the form: $$M(q) \ddot{q} + C(q, \dot{q}) \dot{q} = \tau - g(q) $$ where $M(q)$ is the mass matrix, $C(q, \dot{q})$ is the Coriolis matrix, $g(q)$ is the gravity vector, and $\tau$ is the control input.

A radial basis function neural network (RBFNN) controller can be used to approximate the dynamics of the manipulator. The radial basis function neural network controller is given by:

$$f(x) = \Theta^T \Phi(x) + \epsilon(x)$$

where $\Theta$ is the weight vector, $\Phi(x)$ is the radial basis function, and $\epsilon(x)$ is the approximation error.

The control law is given by:

$$ \tau = \hat{\Theta}^T \Phi(x) - K_D s $$

and the RBFNN weight update law is given by:

$$ \dot{\hat{\Theta}} = -\Gamma \Phi(x) s^T $$

More details are provided in the paper TODO.

Installation

To install the package, clone the repository and install editable version via pip:

git clone <url>
cd manipulator-adaptive-control
pip install requirements.txt

Examples

Examples of how to use the package can be found in the examples directory.

BibTeX

If you use this package, please cite it using the following:

TODO