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.
Update controller parameters to maximize an objective function in the presence of unknown system dynamics.
Track a reference plant model by adapting feedforward and feedback gains for an uncertain dynamical system.
Design an extremum seeking controller that maximizes the friction coefficient of an ABS system to achieve the shortest stopping distance.
Design an extremum seeking controller to adjust controller gains for an adaptive cruise control system.
Compute control actions to make an uncertain controlled system track the behavior of a given reference plant model.
Design MRAC controller that adapts plant uncertainty model parameters to achieve performance that matches an ideal reference model.
Design MRAC controller that adapts wing-rock disturbance model parameters to achieve performance that matches an ideal reference model.