scenarioDeployPanels

It’s recommended to review the following scenario(s) first (and any recommended scenario(s) that they may have):

  1. examples/mujoco/scenarioArmWithThrusters.py

This script demonstrates how to simulate a spacecraft with solar panels deployed using a Proportional-Integral-Derivative (PID) controller. This script uses the MuJoCo-based DynamicObject MJScene.

In mujoco/scenarioArmWithThrusters.py, we saw how we can constrain joints to follow a specific angle by letting the dynamic engine figure out and apply the necessary torques. In this script, we are controlling the joints using a PID controller. This is a more adequate simulation setup when you want to simulate or design the control system for these joints. It is also generally more computationally efficient than letting the dynamic engine figure out the torques.

The multi-body system is defined in the XML file sat_w_deployable_panels.xml. This XML file defines a ‘hub’ body and six deployable solar panels. The panels are attached to the ‘hub’ body via revolute joints, allowing them to rotate from a stowed position to a deployed position.

This XML file (and this script) demonstrates the use of the range attribute in the joint element. This attribute allows the joint to be limited to a specific range of motion. For example, between 0 and 90 or 180 degrees. If the joint tries to move beyond this range, the dynamic engine will apply a force to prevent it from doing so (akin to a physical stop on the system). Note in the plots and in the 3D visualization how the panels never get deployed over their joint limit.

The deployment of the panels is controlled using an analog PID controller. The desired position and velocity profiles for the joints are generated using a trapezoidal/triangular velocity profile. These profiles are then used as inputs to the PID controller, which computes the torque required to achieve the desired motion. Note that the controller class extends StatefulSysModel, instead of SysModel, since we need to register the integral error as a continuous state.

The simulation is run for 80 minutes and the state of the system is recorded. The desired and achieved joint angles, as well as the torque applied to each joint, are plotted. The system can also be visualized in a 3D environment using the mujoco.visualize function.

class scenarioDeployPanels.PIDController(*a, **kw)[source]

Bases: StatefulSysModel

A Proportional-Integral-Derivative (PID) Controller class for controlling joint states.

This models an analog PID controller, which means that its output evolves in continuous time, not discrete time. Thus, it should be used within the dynamics task of MJScene.

K_p

Proportional gain.

Type:

float

K_d

Derivative gain.

Type:

float

K_i

Integral gain.

Type:

float

measuredInMsg

Reader for the measured joint state.

Type:

messaging.ScalarJointStateMsgReader

desiredInMsg

Reader for the desired joint state.

Type:

messaging.ScalarJointStateMsgReader

measuredDotInMsg

Reader for the measured joint state derivative.

Type:

messaging.ScalarJointStateMsgReader

desiredDotInMsg

Reader for the desired joint state derivative.

Type:

messaging.ScalarJointStateMsgReader

outputOutMsg

Output message, contains the torque for the connected actuator.

Type:

messaging.SingleActuatorMsg

scenarioDeployPanels.generateProfiles(initialPoint: float, finalPoint: float, vMax: float, aMax: float) → List[ScalarJointStateInterpolator][source]

Generate a position and velocity profile for a point-to-point movement.

This function calculates the position and velocity profiles for a point-to-point movement using either a trapezoidal or triangular velocity profile, depending on whether the maximum velocity is reached or not.

Parameters:

  • initialPoint (float) – The starting position.

  • finalPoint (float) – The target position.

  • vMax (float) – The maximum velocity.

  • aMax (float) – The maximum acceleration.

Returns:

A list containing two mujoco.ScalarJointStateInterpolator objects,

one for the position profile and one for the velocity profile.

Return type:

list

scenarioDeployPanels.run(initialSpin: bool = False, showPlots: bool = False, visualize: bool = False)[source]

Main function, see scenario description.

Parameters:

  • initialSpin (bool, optional) – If True, the satellite is given an initial angular velocity. Defaults to False.

  • showPlots (bool, optional) – If True, simulation results are plotted and show. Defaults to False.

  • visualize (bool, optional) – If True, the MJScene visualization tool is run on the simulation results. Defaults to False.