The purpose of this paper is to provide a unified presentation of the formulas arising in the discrete-time finite-horizon linear Linear Quadratic Regulator problem, the Linear Quadratic Gaussian problem, the Linear Exponential of Quadratic Gaussian problem, and the minimax Linear Quadratic Gaussian problem. For these classes of optimal control problems, the paper presents formulas for optimal ...

A novel data-driven control performance assessment (CPA) method is proposed for batch processes controlled by iterative learning control (ILC) based on two-dimensional linear quadratic Gaussian (LQG) benchmark. Previous studies on CPA for ILC are based on an assumption that the model of the controlled batch process is known, whereas this study proposes a model-free CPA method. Based on the two-...

This paper provides a framework for control design and simulation of a closed-loop system with partial input/output data of a plant. Given the input/output crosscorrelation and output autocorrelation data of an open loop dynamic system, a simulation model implemented in fixed-point digital devices which matches these data is obtained using q-Markov Covariance Equivalent Realizations. These resu...

This work presents a field programmable gate array (FPGA)-based embedded software platform coupled with a softwarebased plant, forming a hardware-in-the-loop (HIL) that is used to validate a systematic sensor selection framework. The systematic sensor selection framework combines multi-objective optimization, linear-quadratic-Gaussian (LQG)-type control, and the nonlinear model of a maglev susp...

The objective of this paper is to investigate a multi-objective linear quadratic Gaussian (LQG) control problem. Specifically, we examine an optimal problem that minimizes cost over finite time horizon for stochastic systems subject energy constraints. To tackle problem, propose efficient bisection line search algorithm outperforms other approaches such as semidefinite programming in terms comp...

The average cost control problem for linear stochastic systems with Gaussian noise and quadratic cost is considered in the presence of communication constraints. The latter take the form of finite alphabet codewords, being transmitted to the controller with ensuing delay and distortion. It is shown that if instead of the state observations an associated "innovations process" is encoded and tran...

Automotive is one of the most important industries in world, which lead to a need for continuous improvement vehicles and their internal systems. Suspension systems have been improved better vehicle performance passenger comfort, keeping tire contact with road surface. Active suspensions require optimal control modulate flow energy generate force by implementing active actuators able provide ne...

This paper is concerned with linear-quadratic-Gaussian (LQG) control for a field-mediated feedback connection of plant and coherent (measurement-free) controller. The controller are multimode open quantum harmonic oscillators governed by linear stochastic differential equations. objective to make the closed-loop system internally stable minimize infinite-horizon quadratic cost variables output ...

This paper revisits the classical Linear Quadratic Gaussian (LQG) control from a modern optimization perspective. We analyze two aspects of landscape LQG problem: (1) Connectivity set stabilizing controllers $$\mathcal {C}_n$$ ; and (2) Structure stationary points. It is known that similarity transformations do not change input-output behavior dynamic controller or cost. inherent symmetry by ma...