NDLI: Optimal Tracking Design of an MIMO Linear System with Quantization Effects ?

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Optimal Tracking Design of an MIMO Linear System with Quantization Effects ?

Content Provider	Semantic Scholar
Author	Su, Weizhou Qi, Tian Chen, Jie Fu, Minyue
Copyright Year	2011
Abstract	This paper studies optimal design for a linear time-invariant (LTI) MIMO discretetime networked feedback system in tracking a step signal. It is assumed that the outputs of the controller are quantized by logarithm quantization laws, respectively, and then transmitted through a communication network to the remote plant in the feedback system, whereas the quantization errors in all quantized signals are modeled as a product of a white noise with zero mean and the source signal respectively, the variances of the white noises are determined by the accuracies of the quantization laws. The tracking performance of the system we interested in is defined as the averaged energy of the error between the output of the plant and the reference input. Three problems are studied for the system: 1) For a set of given logarithm laws, how to design an optimal stabilizing controller for the closed-loop system in mean-square stability sense? 2) What is a minimal communication load to stabilize the networked feedback system in terms of the characteristics of the logarithm quantization laws? 3) For a set of given logarithm laws, how to design an optimal controller to achieve minimal tracking cost? We find that the problems 1 and 3 have a unique solution, respectively, and obtain an analytic solution for problem 2 when the plant is a minimum phase system.
File Format	PDF HTM / HTML
Alternate Webpage(s)	http://www.eng.newcastle.edu.au/~mf140/home/Papers/IFAC2011_4.pdf
Alternate Webpage(s)	http://www.nt.ntnu.no/users/skoge/prost/proceedings/ifac11-proceedings/data/html/papers/1014.pdf
Language	English
Access Restriction	Open
Subject Keyword	Arabic numeral 0 Assumed Control system Controllers Linear system Linear time-invariant theory Logarithm MIMO Mean squared error Minimum phase Optimal control Optimal design Quantization (signal processing) Stochastic process Telecommunications network Time complexity Time-invariant system White noise disease transmission
Content Type	Text
Resource Type	Article

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