Output Feedback Model Predictive Control for NCSs with Input Quantization

This paper addresses the robust output feedback model predictive control (MPC) schemes for networked control systems (NCSs) with input quantization. The logarithmic quantizer is considered in this paper, and the sector bound approach is applied, which appropriately treats the quantization error as a...

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Main Authors: Hongchun Qu, Yu Li, Wei Liu
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2022/6929902
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author Hongchun Qu
Yu Li
Wei Liu
author_facet Hongchun Qu
Yu Li
Wei Liu
author_sort Hongchun Qu
collection DOAJ
description This paper addresses the robust output feedback model predictive control (MPC) schemes for networked control systems (NCSs) with input quantization. The logarithmic quantizer is considered in this paper, and the sector bound approach is applied, which appropriately treats the quantization error as a sector-bounded uncertainty. The presented method involves an offline designed state observer using linear matrix inequality (LMI) and online robust output feedback MPC algorithms which optimize one free control move followed by the output feedback using the estimated state. Moreover, due to the uncertainty of estimation error, a technique of refreshing the bound of estimation error which involves the quantization error is provided so as to guarantee the recursive feasibility of the optimization problem. The proposed MPC schemes inherit the characteristics of the synthesis approach of MPC, guaranteeing the recursive feasibility of the optimization problem and the stability of a closed-loop system, and explicitly account for quantization error. Two simulation examples are given to illustrate the effectiveness of the proposed methods.
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institution Kabale University
issn 1099-0526
language English
publishDate 2022-01-01
publisher Wiley
record_format Article
series Complexity
spelling doaj-art-0a5465a9b7c848af93c45dd42354d11e2025-02-03T01:22:27ZengWileyComplexity1099-05262022-01-01202210.1155/2022/6929902Output Feedback Model Predictive Control for NCSs with Input QuantizationHongchun Qu0Yu Li1Wei Liu2College of Information Science and TechnologyCollege of AutomationCollege of AutomationThis paper addresses the robust output feedback model predictive control (MPC) schemes for networked control systems (NCSs) with input quantization. The logarithmic quantizer is considered in this paper, and the sector bound approach is applied, which appropriately treats the quantization error as a sector-bounded uncertainty. The presented method involves an offline designed state observer using linear matrix inequality (LMI) and online robust output feedback MPC algorithms which optimize one free control move followed by the output feedback using the estimated state. Moreover, due to the uncertainty of estimation error, a technique of refreshing the bound of estimation error which involves the quantization error is provided so as to guarantee the recursive feasibility of the optimization problem. The proposed MPC schemes inherit the characteristics of the synthesis approach of MPC, guaranteeing the recursive feasibility of the optimization problem and the stability of a closed-loop system, and explicitly account for quantization error. Two simulation examples are given to illustrate the effectiveness of the proposed methods.http://dx.doi.org/10.1155/2022/6929902
spellingShingle Hongchun Qu
Yu Li
Wei Liu
Output Feedback Model Predictive Control for NCSs with Input Quantization
Complexity
title Output Feedback Model Predictive Control for NCSs with Input Quantization
title_full Output Feedback Model Predictive Control for NCSs with Input Quantization
title_fullStr Output Feedback Model Predictive Control for NCSs with Input Quantization
title_full_unstemmed Output Feedback Model Predictive Control for NCSs with Input Quantization
title_short Output Feedback Model Predictive Control for NCSs with Input Quantization
title_sort output feedback model predictive control for ncss with input quantization
url http://dx.doi.org/10.1155/2022/6929902
work_keys_str_mv AT hongchunqu outputfeedbackmodelpredictivecontrolforncsswithinputquantization
AT yuli outputfeedbackmodelpredictivecontrolforncsswithinputquantization
AT weiliu outputfeedbackmodelpredictivecontrolforncsswithinputquantization