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Control systems are everywhere in contemporary society, influencing diverse applications from aerospace to automated manufacturing. These systems can be found naturally within biological processes, such as blood sugar regulation and heart rate adjustment in response to stress, as well as in man-made systems like elevators and automated vehicles. A control system is essentially a network of subsystems and processes that collaboratively convert specific inputs into desired outputs.
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Optimal modified tracking performance for networked control systems with QoS constraint.

Xi-Sheng Zhan1, Xin-Xiang Sun1, Jie Wu1

  • 1College of Mechatronics and Control Engineering, Hubei Normal University, Huangshi 435002, PR China.

ISA Transactions
|August 6, 2016
PubMed
Summary
This summary is machine-generated.

This study optimizes networked control systems performance under quality of service constraints. The research introduces a modified tracking index to mitigate data loss and noise, enhancing system reliability.

Keywords:
Data dropoutsNetworked control systemsOptimal modified tracking performanceQuality of service

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Area of Science:

  • Control Systems Engineering
  • Networked Systems
  • Signal Processing

Background:

  • Networked control systems (NCS) face challenges like data dropout and channel noise, impacting tracking performance.
  • Existing performance indices may not adequately address systems without integrators, leading to potential invalid data.
  • Quality of Service (QoS) is crucial for NCS, necessitating robust performance metrics.

Purpose of the Study:

  • To investigate and optimize the modified tracking performance of NCS under QoS constraints.
  • To develop a modified tracking performance index that accounts for data dropout and Gaussian noise.
  • To design an optimal filter that mitigates channel noise effects in the feedback loop.

Main Methods:

  • Utilizing co-prime factorization to derive the optimal modified tracking performance expression.
  • Developing a novel modified tracking performance index to handle tracking error variations.
  • Designing an optimal filter to eliminate channel noise influence.

Main Results:

  • The optimal modified tracking performance is significantly influenced by non-minimum phase zeros, modification factor, and packet dropout probability.
  • The characteristics of reference signals also play a role in determining the optimal performance.
  • The derived optimal filter effectively suppresses channel noise.

Conclusions:

  • The proposed method provides a robust approach to optimizing NCS performance under QoS constraints.
  • The findings offer valuable guidance for the design and implementation of reliable NCS.
  • The model's efficiency is validated through practical examples.