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Adaptive Control Design

Design controllers that can adapt to changing process information
Since R2021a

When a control system contains uncertainties that change over time, such as unmodeled system dynamics and disturbances, an adaptive controller can compensate for the changing process information by adjusting its parameters in real time. By doing so, such a controller can achieve desired reference tracking despite the uncertainties in the plant dynamics.

Simulink® Control Design™ software provides several Simulink blocks for the following real-time adaptive control methods.

  • Extremum Seeking Control — Model-free adaptation to maximize an objective function derived from the control system

  • Model Reference Adaptive Control — Adaptation to track the output of a known reference model

  • ESO-Based Disturbance Compensation — Model-free adaptation to reject internal and external disturbances of a plant


Extremum Seeking ControlCompute controller parameters in real time by maximizing objective function
Model Reference Adaptive ControlCompute control actions to make controlled system track reference model (Since R2021b)
Active Disturbance Rejection ControlDesign controller for plants with unknown dynamics and disturbances (Since R2022b)
Extended State ObserverEstimate states and disturbances of a system (Since R2024a)
Disturbance CompensatorModify control actions to compensate for unknown dynamics and disturbances (Since R2024a)


Extremum Seeking Control

Model Reference Adaptive Control

Active Disturbance Rejection Control

Disturbance Compensation

Sliding Mode Control

Iterative Learning Control