The Wolfram Language provides powerful functions to compute state-feedback and estimator gains using pole-placement or optimal techniques. In addition, it has functions that directly assemble regulator and estimator models based on design specifications or precomputed gains.

Pole Placement

StateFeedbackGains— feedback gains computed using pole placement

EstimatorGains— estimator gains computed using pole placement

Optimal Control and Estimation

LQRegulatorGains— feedback gains that minimize a quadratic cost function

LQOutputRegulatorGains— feedback gains that minimize a quadratic output cost function

LQEstimatorGains— estimator gains that minimize a quadratic cost function

DiscreteLQRegulatorGains— emulated discrete-time feedback gains

DiscreteLQEstimatorGains— emulated discrete-time estimator gains

Optimal Control with Constraints

ModelPredictiveController— optimal controller with state and control constraints

DiscreteInputOutputModel— general input-output model

Controllers and Estimators

KalmanEstimator— Kalman estimator with specified covariance matrices

LQGRegulator— linear quadratic Gaussian (LQG) regulator

StateOutputEstimator— estimator model with specified gains

EstimatorRegulator— regulator model with specified estimator and feedback gains