Control System Toolbox

Dynamic System Modeling

Create linear models of your control system as transfer functions, (sparse) state-space models, LPV and LTV models, and other representations. Discretize and resample models. Simplify analysis and control design by reducing model order.

Linear Analysis

Visualize system behavior in the time and frequency domain. Compute system characteristics such as rise time, overshoot, and settling time. Analyze system stability by computing gain and phase margins and crossover frequencies.

PID Tuning

Automatically tune PID controller gains to balance performance and robustness using the PID Tuner app or command-line functions. Tune continuous or discrete controllers and 2-DOF PID controllers.

Compensator Design

Interactively design and analyze single-input, single-output (SISO) controllers with the Control System Designer app, using automated tuning methods. Graphically tune common control components using root locus, Bode diagrams, and Nichols charts.

State Estimation and State-Space Control Design

Use state-space control design methods, such as LQR/LQG and pole-placement algorithms. Estimate system states using observers, including linear and nonlinear Kalman filters.

Multiloop, Multiobjective Tuning

Automatically tune arbitrary SISO and MIMO decentralized control structures modeled in MATLAB or Simulink to satisfy time and frequency-domain design requirements using the Control System Tuner app.

Gain Scheduling

Design gain-scheduled controllers for nonlinear or time-varying plants. Specify requirements and automatically tune gain surface coefficients. Validate the tuning results across the entire operating range of your design.

Control Design in Simulink

Analyze and tune control systems modeled in Simulink and analyze its time and frequency domain characteristics using Simulink Control Design. Linearize Simulink models and compute time and frequency responses. Graphically or automatically tune feedback loops modeled in Simulink.

Reference Applications

Use reference application examples for flight control, power electronics, robotics, and other applications to design and analyze controllers for systems modeled in MATLAB and Simulink.

“Simulink enabled us to produce a stable control system in a short time. We modeled the entire system, including a state machine and cascaded PI controls. We refined this model to improve robustness and response times, then verified it with RCP, and generated embedded code.”

René Pätznick, WOM