Linear quadratic Gaussian control of 2-dimensional systems

Authors:
Ran Yang;Cishen Zhang;Lihua Xie
Affiliations:
School of Information Science and Technology, Sun Yat-Sen University, Guangzhou, People's Republic of China 510275;School of Electrical and Electronic Engineering, BLK S2, Nanyang Technological University, Singapore, Singapore 639798;School of Electrical and Electronic Engineering, BLK S2, Nanyang Technological University, Singapore, Singapore 639798
Venue:
Multidimensional Systems and Signal Processing
Year:
2007

Citing 4
Cited 1

Optimal control: linear quadratic methods

Optimal control: linear quadratic methods
2D Model-Following Servo System

Multidimensional Systems and Signal Processing
Stability Analysis for Linear Repetitive Processes

Stability Analysis for Linear Repetitive Processes
Brief H∞ control and robust stabilization of two-dimensional systems in Roesser models

Automatica (Journal of IFAC)

Gain-scheduled control of two-dimensional discrete-time linear parameter-varying systems in the Roesser model

Automatica (Journal of IFAC)

Quantified Score

Hi-index	0.00

Visualization

Abstract

The linear quadratic Gaussian (LQG) control for one-dimensional (1D) systems has been known to be one of the fundamental and significant methods in linear system theory. However, the LQG control problem for two-dimensional (2D) systems has not been satisfactorily solved due to their structural and dynamical complexity. In this paper, sufficient conditions for evaluation of the quadratic performance indices of 2D systems in terms of the system state and control variables are proposed. Using these conditions, systematic design methods for finite horizon and infinite horizon LQG controls of 2D systems are developed using a convex optimization method.