types.linearization.StateJacobian

types.linearization.StateJacobian

State Jacobian ∂f/∂x.

Matrix of partial derivatives of dynamics with respect to state.

Continuous: Ac = ∂f/∂x where f is drift Discrete: Ad = ∂f/∂x where f is next-state function

Shape: (nx, nx)

Examples

>>> Ac: StateJacobian = system.state_jacobian(x_eq, u_eq)
>>> # For pendulum: Ac = [[0, 1], [-g/L*cos(θ), -b]]

# types.linearization.StateJacobian { #cdesym.types.linearization.StateJacobian }

`types.linearization.StateJacobian`

State Jacobian ∂f/∂x.

Matrix of partial derivatives of dynamics with respect to state.

Continuous: Ac = ∂f/∂x where f is drift
Discrete: Ad = ∂f/∂x where f is next-state function

Shape: (nx, nx)

## Examples {.doc-section .doc-section-examples}

```python
>>> Ac: StateJacobian = system.state_jacobian(x_eq, u_eq)
>>> # For pendulum: Ac = [[0, 1], [-g/L*cos(θ), -b]]
```