MapleSim Control™ Design Toolbox - Maplesoft

MapleSim Control Design Toolbox

MapleSim Control Design Toolbox

The MapleSim Control Design Toolbox provides a solid set of essential control design tools that extend MapleSim’s exceptional plant modeling capabilities to support control design. The MapleSim Control Design Toolbox provides:

  • Greater flexibility and accuracy in your controllers. The symbolic approach for designing, analyzing, and testing control systems produces superior results.
  • Increased reusability of your controller designs. You can document your design decisions using the extensive technical documentation tools available with MapleSim.
  • An accelerated design process. Developing your plants and controllers together in the same environment reduces the need for inefficient tool-swapping.

Key Features

  • Provides tools for model linearization, PID tuning, development of state-space control strategies such as LQR,  custom compensator design and the creation of feedback system configurations including LQG.
  • Incorporates symbolic techniques that make it possible to
    • Characterize all possible solutions to a given control problem and then pick the best solution based on the particular situation.
    • Build and investigate controllers where the model includes symbolic, unspecified parameters. The same controller design can then be applied to multiple related models without further tuning.
    • Create controllers where the design specifications are parametric, so the same controller can be used successfully under a variety of conditions.
  • Includes easy-to-use MapleSim templates for interactive controller development and analysis.
  • Provides programmatic access to all functionality as an alternative to the interactive interface and supports custom application development.
  • Templates, documentation, and examples are incorporated seamlessly into the MapleSim environment, providing a single consistent interface for developing both the plant and the controller.

Toolbox functionality includes:

  • Model linearization
  • Standard PID tuning techniques
    • Ziegler-Nichols time response
    • Ziegler-Nichols frequency response
    • Cohen-Coon
  • Advanced PID tuning techniques
    • Dominant pole placement
    • Pole placement in a specified region
    • Gain and phase margin
    • Automatic PID tuning method selection
  • State Feedback Control
    • Single input pole placement (using Ackermann’s formula)
    • Multiple input pole placement
    • Linear-quadratic regulator (LQR)
    • Automatic computation of design parameters
  • State Estimation
    • Single output pole placement (using Ackermann’s formula)
    • Multiple output pole placement
    • Kalman Filter
  • System Manipulation
    • Closed-loop form of feedback systems
    • Removal of non-minimal states of the system