Adaptive Control Design

Design controllers that can adapt to changing process information

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 the following real-time adaptive control methods for computing controller parameters.

Extremum Seeking Control — Model-free adaptation to maximize an objective function derived from the control system
Model Reference Adaptive Control — Model-based adaptation to track the output of a known reference model

Blocks

Extremum Seeking Control	Compute controller parameters in real time by maximizing objective function
Model Reference Adaptive Control	Compute control actions to make controlled system track reference model

Topics

Extremum Seeking Control

Extremum Seeking Control
Update controller parameters to maximize an objective function in the presence of unknown system dynamics.
Extremum Seeking Control for Reference Model Tracking of Uncertain Systems
Track a reference plant model by adapting feedforward and feedback gains for an uncertain dynamical system.
Anti-Lock Braking Using Extremum Seeking Control
Design an extremum seeking controller that maximizes the friction coefficient of an ABS system to achieve the shortest stopping distance.
Adaptive Cruise Control Using Extremum Seeking Control
Design an extremum seeking controller to adjust controller gains for an adaptive cruise control system.

Model Reference Adaptive Control

Model Reference Adaptive Control
Compute control actions to make an uncertain controlled system track the behavior of a given reference plant model.
Model Reference Adaptive Control of Satellite Spin
Design MRAC controller that adapts plant uncertainty model parameters to achieve performance that matches an ideal reference model.
Model Reference Adaptive Control of Aircraft Undergoing Wing Rock
Design an MRAC controller that adapts disturbance model parameters to achieve performance that matches an ideal reference model.
Indirect Model Reference Adaptive Control of First-Order System
Design an indirect MRAC controller that estimates the properties of an unknown first-order system.
Indirect MRAC Control of Mass-Spring-Damper System
Design an indirect MRAC controller that estimates the parameters of an unknown MIMO system.

Adaptive Control Design

Blocks

Topics

Extremum Seeking Control

Model Reference Adaptive Control

Related Information