Digital LQG Controller Design Applied to an Electronic System

Experimental Evaluation of the Robust Controllers Applied on a Single Inductor Multiple Output DC-DC Buck Converter to Minimize Cross Regulation Considering Parametric Uncertainties and CPL Power Variations

“…The LQR control is a well-known optimal-based approach to state feedback controller that can solve some problems in systems like instability or low stability margins, manipulating the system inputs and avoiding some typical problems on the stabilization problem like saturation control signal and fast actuator degradation [35]. This controller design is based on the choice of weight matrices of the states and control signal, Q and R respectively, which is used in the minimizing cost function.…”

“…) Positive-definite matrix "S" is a solution of the discrete-time algebraic Ricatti equation. 12) In this structure the LQR control on closed loop has not guaranteed perturbation reject in low frequency, however, this problem can be solved by an integrator addition on system input, creating a different model called "velocity model" [35]. The discrete integrator ∆= 1 − 𝑧𝑧 −1 is inserted on the system plant, by this way creating a new state variable ∆x(k).…”

Development of a didactic plant and a human-machine interface to compare different digital controllers

“…The KF, being an optimal observer, is able to provide the controller with access to all state variables of the augmented model. Thus, the states of the identified model are optimally estimated by KF, which allows both measurement errors and modeling errors to be disregarded (Castro et al, 2020). For the implementation of KF with LQR, the following system described by the state space model is considered:…”

Control of inventory system with random demand and product damage during delivery using the linear quadratic gaussian method

“…One of the methods used to solve optimization problems with uncertain parameters is the linear quadratic gaussian (LQG) [12]. There are several reports in varying fields regarding the advantages of using this control method: for example, power system [13], [14], mechanical control problem [15], [16], power flow [17], unmanned aerial vehicle [18], simplified car [19], acquisition process [20], slung transportation [21], vehicle automation [22], [23], buck converter controlling [24], robotic & electronic systems [25], [26], and optics system [27].…”