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State-Space Control Design

LQG/LQR and pole-placement algorithms

State-space control design methods, such as LQG/LQR and pole-placement algorithms, are useful for MIMO design.

Functions

lqrLinear-Quadratic Regulator (LQR) design
lqryForm linear-quadratic (LQ) state-feedback regulator with output weighting
lqiLinear-Quadratic-Integral control
dlqrLinear-quadratic (LQ) state-feedback regulator for discrete-time state-space system
lqrdDesign discrete linear-quadratic (LQ) regulator for continuous plant
lqgLinear-Quadratic-Gaussian (LQG) design
lqgregForm linear-quadratic-Gaussian (LQG) regulator
lqgtrackForm Linear-Quadratic-Gaussian (LQG) servo controller
augstateAppend state vector to output vector
normNorm of linear model
estimForm state estimator given estimator gain
placePole placement design
regForm regulator given state-feedback and estimator gains

Topics

Linear-Quadratic-Gaussian (LQG) Design

Linear-quadratic-Gaussian (LQG) control is a state-space technique that allows you to trade off regulation/tracker performance and control effort, and to take into account process disturbances and measurement noise.

LQG Regulation: Rolling Mill Case Study

Use linear-quadratic-Gaussian techniques to regulate the beam thickness in a steel rolling mill.

Design Yaw Damper for Jet Transport

This case study illustrates the classical design process.

Design an LQG Regulator

Design an LQG regulator for a plant output in a system with noise.

Design an LQG Servo Controller

Design an LQG servo controller using a Kalman state estimator.

Design an LQR Servo Controller in Simulink

Design an LQR controller for a system modeled in Simulink®.

Pole Placement

Closed-loop pole locations have a direct impact on time response characteristics such as rise time, settling time, and transient oscillations. Pole placement uses state-space techniques to assign closed-loop poles.