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Wolfram Language & System Documentation Center
ConnectSystemModelController
  • See Also
    • SystemModel
    • StateFeedbackGains
    • LQRegulatorGains
    • DiscreteLQRegulatorGains
    • EstimatorRegulator
    • LQGRegulator
    • PIDTune
  • Related Guides
    • System Model Analytics & Design
    • See Also
      • SystemModel
      • StateFeedbackGains
      • LQRegulatorGains
      • DiscreteLQRegulatorGains
      • EstimatorRegulator
      • LQGRegulator
      • PIDTune
    • Related Guides
      • System Model Analytics & Design

ConnectSystemModelController[model,controller]

connects the system model model with a controller according to the controller data controller.

Details
Details and Options Details and Options
Examples  
Basic Examples  
Scope  
StateFeedbackGains  
LQRegulatorGains  
DiscreteLQRegulatorGains  
Show More Show More
EstimatorRegulator  
LQGRegulator  
PIDTune  
ModelPredictiveController  
Tracking  
See Also
Related Guides
Related Links
History
Cite this Page
BUILT-IN SYMBOL
  • See Also
    • SystemModel
    • StateFeedbackGains
    • LQRegulatorGains
    • DiscreteLQRegulatorGains
    • EstimatorRegulator
    • LQGRegulator
    • PIDTune
  • Related Guides
    • System Model Analytics & Design
    • See Also
      • SystemModel
      • StateFeedbackGains
      • LQRegulatorGains
      • DiscreteLQRegulatorGains
      • EstimatorRegulator
      • LQGRegulator
      • PIDTune
    • Related Guides
      • System Model Analytics & Design

ConnectSystemModelController

ConnectSystemModelController[model,controller]

connects the system model model with a controller according to the controller data controller.

Details

  • ConnectSystemModelController is typically used to connect a controller to a SystemModel plant model and give the closed-loop system back. The resulting system can then be simulated and analyzed for real-world performance.
  • The model can be a SystemModel object, a full model name string or a shortened model name accepted by SystemModel.
  • ConnectSystemModelController["NewModel",…] gives the created model the name "NewModel".
  • The controller is a SystemsModelControllerData object produced by control design functions.
  • With state feedback from model, the control design functions include:
  • StateFeedbackGainspole placement state feedback
    LQRegulatorGainslinear quadratic optimal control
    DiscreteLQRegulatorGainsdiscrete-time linear quadratic optimal control
    ModelPredictiveControllerconstrained model predictive controller
  • With output feedback from model, the controller design functions include:
  • EstimatorRegulatorassembling state feedback and state estimator
    LQGRegulatorlinear quadratic control and estimator
    PIDTuneautomatically tuned PID controller
  • ConnectSystemModelController returns a SystemModel.

Examples

open all close all

Basic Examples  (1)

Start with a model for a DC motor:

Linearize it around an equilibrium point:

Create a controller:

Generate the closed-loop system for the controlled model:

Provide a reference input and plot the output:

Scope  (16)

StateFeedbackGains  (3)

Start with a model for a submerging submarine:

Linearize it around an equilibrium point:

Design a controller:

Generate the closed-loop system for the controlled model:

Perturb the submarine with a vertical force:

Simulate the closed-loop system with the same disturbance:

Plot the depth of the submarine in the original model:

In the closed-loop system, the submarine changes its density to preserve its depth:

Start with a model for a spacecraft in a circular orbit:

Linearize it around an equilibrium point:

Design a controller:

Generate the closed-loop system for the controlled model:

Simulate the original model with an initial velocity:

Simulate the closed-loop system with the same initial velocity:

Plot the deviations from the circular trajectory in the original model:

The closed-loop system brings the spacecraft back to its circular orbit:

Start with a model for an inverted pendulum:

Linearize it around an equilibrium point:

Design a controller:

Generate the closed-loop system for the controlled model:

Apply a tangential force to the pendulum and simulate it:

Simulate the closed-loop system with the same disturbance:

Plot the angle of the pendulum in the original model:

The closed-loop system applies a horizontal force and brings the pendulum back to the vertical position:

LQRegulatorGains  (2)

Start with a model for a continuous stirred-tank reactor:

Linearize it around an equilibrium point:

Design a controller:

Generate the closed-loop system:

Simulate the original model with a deficit in the concentration of the reactant from its equilibrium value:

Simulate the closed-loop system with the same initial condition:

Plot the change in reactant concentration in the original model:

The closed-loop system controls the flow rate and brings the concentration back to the equilibrium value:

Start with a model for a ball placed on top of a beam that can rotate around its center of mass:

Linearize it around an equilibrium point:

Design a controller:

Generate the closed-loop system:

Simulate the original model placing the ball at the edge of the beam:

Simulate the closed-loop system with the same initial condition:

Plot the position of the ball, measured from the middle of the beam, in the original model:

The closed-loop system applies a torque and brings the ball back to the middle of the beam:

DiscreteLQRegulatorGains  (2)

Start with a model for a continuous stirred-tank reactor:

Linearize it around an equilibrium point:

Design a controller:

Generate the closed-loop system:

Simulate the original model with a deficit in the concentration of the reactant from its equilibrium value:

Simulate the closed-loop system with the same initial condition:

Plot the change in reactant concentration in the original model:

The closed-loop system controls the flow rate and brings the concentration back to the equilibrium value:

Start with a model for a ball placed on top of a beam that can rotate around its center of mass:

Linearize it around an equilibrium point:

Design a controller:

Generate the closed-loop system:

Simulate the original model placing the ball at the edge of the beam:

Simulate the closed-loop system with the same initial condition:

Plot the position of the ball, measured from the middle of the beam, in the original model:

The closed-loop system applies a torque and brings the ball back to the middle of the beam:

EstimatorRegulator  (2)

Start with a model for a spacecraft in a circular orbit:

Linearize it around an equilibrium point:

Design a controller and observer and put them together in EstimatorRegulator:

Generate the closed-loop system for the controlled model:

Simulate the closed-loop system with an initial velocity:

The closed-loop system brings the spacecraft back to its circular orbit:

Start with a model for an inverted pendulum:

Linearize it around an equilibrium point:

Design a controller and observer and put them together in EstimatorRegulator:

Generate the closed-loop system for the controlled model:

Simulate the closed-loop system with an initial angle away from the equilibrium:

The closed-loop system applies forces to bring the pendulum back to vertical position:

LQGRegulator  (2)

Start with a model for a continuous stirred-tank reactor:

Linearize it around an equilibrium point:

Design a controller:

Generate the closed-loop system for the controlled model:

Simulate the original model with a deficit in the concentration of the reactant from its equilibrium value:

The closed-loop system controls the flow rate and brings the concentration back to the equilibrium value:

Start with a model for a ball placed on top of a beam that can rotate around its center of mass and add some rotational damping:

Linearize it around an equilibrium point:

Design a controller:

Generate the closed-loop system for the controlled model:

Simulate the closed-loop system placing the ball away from the middle of the beam:

The closed-loop system applies a torque and brings the ball back to the middle of the beam:

PIDTune  (1)

Start with a model for an RLC circuit:

Linearize it around an equilibrium point:

Design a controller:

Generate the closed-loop system for the controlled model:

Provide a reference input and plot the output:

ModelPredictiveController  (2)

Start with a model for a camera stabilizer:

Linearize it around an equilibrium point:

Create a controller:

Generate the closed-loop system for the controlled model:

Perturb the system with a vertical force:

Simulate the closed-loop system with the same disturbance:

Plot the position of the camera in the original model:

In the closed-loop system, the position of the camera does not change as much:

Start with a model for a continuous stirred-tank reactor:

Linearize it around an equilibrium point:

Create a controller:

Generate the closed-loop system for the controlled model:

Simulate the original model with a deficit in the concentration of the reactant from its equilibrium value:

Simulate the closed-loop system with the same initial condition:

Plot the change in reactant concentration in the original model:

The closed-loop system controls the flow rate and brings the concentration back to the equilibrium value:

Tracking  (2)

Start with a model for a submarine:

Linearize it around an equilibrium point:

Design a controller that tracks the depth of the submarine:

Generate the closed-loop system for the controlled model:

Simulate the closed-loop system providing a reference signal for the depth and noise:

Plot the reference and the output:

Plot the density change needed to reproduce the reference:

Start with a model for a ball placed on top of a beam that can rotate around its center of mass:

Linearize it around an equilibrium point:

Design a controller that tracks the position of the ball:

Generate the closed-loop system for the controlled model:

Simulate the closed-loop system providing a reference signal for the position and noise:

Plot the reference and the output:

Plot the input torque needed to reproduce the reference:

See Also

SystemModel  StateFeedbackGains  LQRegulatorGains  DiscreteLQRegulatorGains  EstimatorRegulator  LQGRegulator  PIDTune

Related Guides

    ▪
  • System Model Analytics & Design

Related Links

  • ▪ Wolfram System Modeler Documentation

History

Introduced in 2021 (12.3) | Updated in 2022 (13.1)

Wolfram Research (2021), ConnectSystemModelController, Wolfram Language function, https://reference.wolfram.com/language/ref/ConnectSystemModelController.html (updated 2022).

Text

Wolfram Research (2021), ConnectSystemModelController, Wolfram Language function, https://reference.wolfram.com/language/ref/ConnectSystemModelController.html (updated 2022).

CMS

Wolfram Language. 2021. "ConnectSystemModelController." Wolfram Language & System Documentation Center. Wolfram Research. Last Modified 2022. https://reference.wolfram.com/language/ref/ConnectSystemModelController.html.

APA

Wolfram Language. (2021). ConnectSystemModelController. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/ConnectSystemModelController.html

BibTeX

@misc{reference.wolfram_2025_connectsystemmodelcontroller, author="Wolfram Research", title="{ConnectSystemModelController}", year="2022", howpublished="\url{https://reference.wolfram.com/language/ref/ConnectSystemModelController.html}", note=[Accessed: 01-May-2026]}

BibLaTeX

@online{reference.wolfram_2025_connectsystemmodelcontroller, organization={Wolfram Research}, title={ConnectSystemModelController}, year={2022}, url={https://reference.wolfram.com/language/ref/ConnectSystemModelController.html}, note=[Accessed: 01-May-2026]}

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