linear-quadratic regulator

Recommend using a linear-quadratic regulator for such applications.

Another example is the separation of the linear-quadratic-Gaussian control solution into the Kalman filter and optimal controller for a linear-quadratic regulator.

The second matrix Riccati differential equation solves the linear-quadratic regulator problem (LQR).

Linear-quadratic regulator (LQR)

The Kalman filter, the linear-quadratic regulator and the linear-quadratic-Gaussian controller are solutions to what arguably are the most fundamental problems in control theory.

One of the main results in the theory is that the solution is provided by the linear-quadratic regulator (LQR), a feedback controller whose equations are given below.

Optimisation control schemes include: linear-quadratic regulator design (LQR), model predictive control (MPC) and eigenstructure assignment methods.

Together with the linear-quadratic regulator (LQR), the Kalman filter solves the linear-quadratic-Gaussian control problem (LQG).

The LQG controller is simply the combination of a Kalman filter i.e. a linear-quadratic estimator (LQE) with a linear-quadratic regulator (LQR).