Torch-based PID controllers for batched simulation.
Classes:
| Name | Description |
|---|---|
PID |
Vectorized PID controller for multiple environments. |
FlightController |
PID flight controller (batched). |
TrackController |
PID track controller (batched). |
PID(Kp: Tensor, Ki: Tensor | None = None, Kd: Tensor | None = None, dt: float = 0.01, N: float = 100.0, integral_limit: Tensor | None = None, num_envs: int = 1)
Vectorized PID controller for multiple environments.
Initialize PID gains and state tensors.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
|
Tensor
|
Proportional gain tensor with a leading environment dimension. |
required |
|
Tensor | None
|
Integral gain tensor with the same shape as |
None
|
|
Tensor | None
|
Derivative gain tensor with the same shape as |
None
|
|
float
|
Controller time step. |
0.01
|
|
float
|
First-order derivative filter coefficient. |
100.0
|
|
Tensor | None
|
Optional clamp applied elementwise to the integral state. |
None
|
|
int
|
Number of environments. |
1
|
Methods:
| Name | Description |
|---|---|
reset |
Reset PID state for selected environments. |
update |
Compute PID output for the given error tensor. |
reset(env_ids: slice | Sequence[int] | Tensor) -> None
Reset PID state for selected environments.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
|
slice | Sequence[int] | Tensor
|
Indices or slice selecting which environments to reset. |
required |
update(error: Tensor) -> torch.Tensor
Compute PID output for the given error tensor.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
|
Tensor
|
Batched control error tensor compatible with the internal
state shape determined from |
required |
Returns:
| Type | Description |
|---|---|
Tensor
|
torch.Tensor: Combined P+I+D control output. |
FlightController(params: VehicleParams = VehicleParams(), control_mask: list[int] = [1, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0], gains: dict | None = None, limits: dict | None = None, num_envs: int = 1, device: str | device = 'cpu')
Bases: ControllerBase
PID flight controller (batched).
Initialize the batched flight PID controller.
Methods:
| Name | Description |
|---|---|
randomize |
Randomize configured PID gains and command limits for selected environments. |
reset |
Reset PID loops for selected environments. |
update |
Update controller. |
Attributes:
| Name | Type | Description |
|---|---|---|
params |
VehicleParams
|
Vehicle parameters for the controller. |
control_mask |
ndarray | Tensor
|
unified control mask for target/state channels, used in update(). e.g. using 9~11 for attitude yaw control. |
instance-attribute
params: VehicleParams = params
Vehicle parameters for the controller.
instance-attribute
control_mask: ndarray | Tensor = control_mask
unified control mask for target/state channels, used in update(). e.g. using 9~11 for attitude yaw control.
randomize(env_ids=None, gains=None, limits=None)
Randomize configured PID gains and command limits for selected environments.
reset(env_ids)
Reset PID loops for selected environments.
update(target: Tensor, state: Tensor) -> torch.Tensor
Update controller.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
|
Tensor
|
(N, 12) desired [x, y, z, vx, vy, vz, roll, pitch, yaw, wx, wy, wz] |
required |
|
Tensor
|
(N, 12) current state same ordering. |
required |
Returns:
| Type | Description |
|---|---|
Tensor
|
torch.Tensor: Tensor of shape (N, 4): [thrust, roll_moment, pitch_moment, yaw_moment]. |
TrackController(params: VehicleParams = VehicleParams(), control_mask: list[int] = [0, 0, 0, 1, 0, 1], gains: dict | None = None, num_envs: int = 1, device: str | device = 'cpu')
Bases: ControllerBase
PID track controller (batched).
Initialize the batched track controller.
Methods:
| Name | Description |
|---|---|
randomize |
Randomize configured PID gains for all or selected environments. |
reset |
Reset PID loops for selected environments. |
update |
Update controller. |
Attributes:
| Name | Type | Description |
|---|---|---|
params |
VehicleParams
|
Vehicle parameters for the controller. |
control_mask |
ndarray | Tensor
|
unified control mask for target/state channels, used in update(). e.g. using 9~11 for attitude yaw control. |
instance-attribute
params: VehicleParams = params
Vehicle parameters for the controller.
instance-attribute
control_mask: ndarray | Tensor = control_mask
unified control mask for target/state channels, used in update(). e.g. using 9~11 for attitude yaw control.
randomize(env_ids=None, gains=None)
Randomize configured PID gains for all or selected environments.
reset(env_ids)
Reset PID loops for selected environments.
update(target: Tensor, state: Tensor) -> torch.Tensor
Update controller.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
|
Tensor
|
(N, 6) desired [x, y, yaw, u, v, r] |
required |
|
Tensor
|
(N, 6) current state same ordering. |
required |
Returns:
| Type | Description |
|---|---|
Tensor
|
torch.Tensor: (N, 2) left/right acceleration commands. |