Optimal Control of Linear Discrete-Time Systems with Quantization Effects
Weizhou Su
2013-12-29
Abstract:
This work studies optimal control designs for networked linear discrete-time systems with quantization effects
and/or fading channel. The quantization errors and/or fading channels are modeled as multiplicative noises. The $H_2$
optimal control in mean-square sense, optimal regulation and optimal tracking problems are formulated. The necessary and
sufficient condition to the existence of the optimal $H_2$ control via state feedback is presented for the systems. It is
a nature extension for the result in the standard optimal discrete-time $H_2$ state feedback design. It is shown that this
optimal state feedback design problem is generalized eigenvalue problem (GEVP) and the optimal design algorithm is deve-
loped. These results are extended to the output feedback design in the case when the plants have no non-minimum phase zeros
from control inputs to measurements. In particular, the plants with input delays are considered in this case. It is turned
out that the optimal design involves optimal state feedback design and optimal estimation design. The former is determined
by a solution of a new modified algebraic Riccati equation (MARE) and the analytic solution to the latter is obtained.
Moreover, it is shown that the optimal output feedback design is a GEVP problem as well. Then the optimal regulation and
optimal tracking problems are studied. It is found that the cost functions in these problems have the same form as that in
the optimal $H_2$ control problem in mean-square sense. In the light of the study for the optimal $H_2$ control problem in
mean-square sense, these problems via state feedback and output feedback are studied, respectively
About speaker:
Weizhou Su received the B.Eng. and M.Eng. degrees in automatic control engineering from the Southeast University,
Nanjing,Jiangsu, China, in 1983 and 1986, respectively, the M.Eng. degree in electrical and electronic engineering from
Nanyang Technological University, in 1996, and the PhD. degree in electrical engineering from the University of Newcastle,
Newcastle, NSW, Australia, in 2000. From 2000 to 2004, he held research positions in the School of Electrical and Computer
Engineering, Newcastle University, Australia, the Department of Electrical and Electronic Engineering, Hong Kong University
of Science and Technology, Hong Kong, China; the School of QMMS, University of Western Sydney, Sydney, Australia,
respectively. He joined the School of Automation Science and Engineering, South China University of Technology, Guangzhou,
China, where he is currently a professor. His research interests include networked control and estimation, robust control,
fundamental performance limitation of feedback control, and signal processing