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Maple |
The MapleSim Control Design Toolbox provides a solid set of essential
control design tools that extend MapleSim’s exceptional plant
modelling capabilities tsupport control design. The MapleSim Control
Design Toolbox provides:
- Greater flexibility and accuracy in your controllers. The
symbolic approach for designing, analysing, 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 linearisation, PID tuning, development
of state-space control strategies, and custom compensator design.
- Incorporates symbolic techniques that make it possible to
- Characterise
all possible solutions ta 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 tmultiple related models without further tuning.
- Create controllers
where the design specifications are parametric, sthe same
controller can be used successfully under a variety of conditions.
- Provides
easy-to-use MapleSim templates for interactive controller development
and analysis.
- Includes a set of 20 Maple language commands,
which provides programmatic access tall functionality as an
alternative tthe interactive interface and supports custom
application development.
- Templates, documentation, and examples
are incorporated seamlessly intthe MapleSim environment, providing
a single consistent interface for developing both the plant and
the controller.
Toolbox functionality includes:
- Model linearisation
- 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
- State Feedback Control
- Single input pole placement (using
Ackermann’s formula)
- Multiple input pole placement
- Linear-quadratic regulator
(LQR)
- State Estimation
- Single output pole placement (using Ackermann’s
formula)
- Multiple output pole placement
- Kalman Filter
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