Struct distributed_control::dynamics::LtiDynamics

pub struct LtiDynamics<T: LinalgScalar> {
    pub a_mat: Array2<T>,
    pub b_mat: Array2<T>,
    pub c_mat: Array2<T>,
    pub d_mat: Array2<T>,
}

Implement linear, time-invariant (LTI) dynamics. I.e., $\dot{x} = A x + B u$.

Example

use ndarray::array;
use distributed_control::dynamics::{Dynamics, LtiDynamics};

let dynamics = LtiDynamics::new(array![[0., 1.], [0., 0.]], array![[0.], [1.]]);
assert_eq!(dynamics.dynamics(0., &array![1., 2.], &array![3.]), array![2., 3.]);
assert_eq!(dynamics.n_input(), 1);
assert_eq!(dynamics.n_state(), 2);

Fields

a_mat: Array2<T>

b_mat: Array2<T>

c_mat: Array2<T>

d_mat: Array2<T>

Implementations

impl<T: LinalgScalar> LtiDynamics<T>

pub fn new(a_mat: Array2<T>, b_mat: Array2<T>) -> LtiDynamics<T>

Create an LTI system from an $A$ matrix (a_mat) and a $B$ matrix (b_mat)

Trait Implementations

impl<T: Debug + LinalgScalar> Debug for LtiDynamics<T>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl<T: LinalgScalar> Dynamics<T> for LtiDynamics<T>

fn n_input(&self) -> usize

Get the dimension of the input $u$.

fn n_state(&self) -> usize

Get the dimension of the state $x$.

fn n_output(&self) -> usize

Get the dimension of the output $y$.

fn dynamics(&self, _t: T, x: &Array1<T>, u: &Array1<T>) -> Array1<T>

Calculate the dynamics, i.e., $\dot{x} = f(t, x, u(t, x))$

fn output(&self, _t: T, x: &Array1<T>, u: &Array1<T>) -> Array1<T>

Calculate the output, i.e., $y = g(t, x, u(t, x))$