Optimal control for networked control systems with disturbances: a delta operator approach

This study deals with the optimal control problem for a class of delta-domain networked control systems (NCSs) subjected to both matched and unmatched disturbances. In the presence of the disturbances, the so-called $\epsilon $ϵ-optimum is proposed to quantify the control performance. The purpose of...

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Bibliographic Details
Published in:IET control theory & applications Vol. 11; no. 9; pp. 1325 - 1332
Main Authors: Yuan, Yuan, Yuan, Huanhuan, Wang, Zidong, Guo, Lei, Yang, Hongjiu
Format: Journal Article
Language:English
Published: The Institution of Engineering and Technology 02.06.2017
Subjects:
control system synthesis
controller parameters
convex optimisation algorithms
convex programming
delta operator approach
delta‐domain networked control systems
dynamic programming
dynamic programming method
multivariable control systems
NCS
network induced constraints
networked control systems
optimal control
optimal control problem
optimal control strategy
Research Article
optimal control problem
network induced constraints
dynamic programming
optimal control
control system synthesis
convex programming
controller parameters
convex optimisation algorithms
delta operator approach
multivariable control systems
networked control systems
optimal control strategy
dynamic programming method
delta-domain networked control systems
NCS
ISSN:1751-8644, 1751-8652
Online Access:Get full text
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Summary:This study deals with the optimal control problem for a class of delta-domain networked control systems (NCSs) subjected to both matched and unmatched disturbances. In the presence of the disturbances, the so-called $\epsilon $ϵ-optimum is proposed to quantify the control performance. The purpose of the addressed problem is to design the optimal control strategy such that the cost function is minimised over the finite-/infinite-horizon under the network-induced constraints. In virtue of the dynamic programming method, sufficient conditions are established to guarantee the existence of the desired control strategies, and the controller parameters are designed. For the obtained optimal control strategy, an upper bound for the $\epsilon $ϵ-optimum is provided explicitly, and convex optimisation algorithms are given to compute such upper bound. Both simulation and experimental results are provided to illustrate the usefulness and applicability of the proposed methods.
ISSN:1751-8644
1751-8652
DOI:10.1049/iet-cta.2016.1279