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adaptive control design -凯发k8网页登录

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.

  • — model-free adaptation to maximize an objective function derived from the control system

  • — model-based adaptation to track the output of a known reference model

  • — model-free adaptation to reject internal and external disturbances of a plant

模块

compute controller parameters in real time by maximizing objective function
compute control actions to make controlled system track reference model
design controller for plants with unknown dynamics and disturbances

主题

extremum seeking control


  • 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.

model reference adaptive control


  • compute control actions to make an uncertain controlled system track the behavior of a given reference plant model.

  • design an mrac controller that adapts plant uncertainty model parameters to achieve performance that matches an ideal reference model.

  • design an indirect mrac controller that estimates the properties of an unknown first-order system.

  • design an indirect mrac controller that estimates the parameters of an unknown mimo system.

active disturbance rejection control


  • design a disturbance rejection controller for plants with unknown dynamics and disturbances.

  • design adrc for a water-tank model and compare performance against a gain-scheduled pid controller.

  • design adrc for a brushless dc motor speed controller using pulse width modulation.

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