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Performance analysis method for NCSs with coding and quantization constraints.

Xi-Sheng Zhan1, Jun-Wei Hu1, Jie Wu1

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

ISA Transactions
|August 4, 2020
PubMed
Summary
This summary is machine-generated.

Networked control systems (NCSs) performance depends on plant characteristics and communication factors like noise and quantization. This study analyzes these impacts using spectral factorization for better control scheme design.

Keywords:
Coding-decodingNMP zerosQuantizationUnstable polesperformance

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Area of Science:

  • Control Systems Engineering
  • Networked Control Systems (NCSs)
  • Signal Processing

Background:

  • Networked Control Systems (NCSs) face performance degradation due to communication constraints.
  • Understanding the interplay between controller design and channel limitations is crucial for NCS stability and performance.

Purpose of the Study:

  • To analyze the performance of NCSs considering both coding/quantization in the forward channel and quantization/bandwidth in the feedback channel.
  • To develop a performance expression for NCSs under these constraints.

Main Methods:

  • Utilized spectral factorization to derive the performance expression.
  • Considered a two-degree of freedom (2DOF) controller in the forward channel.
  • Accounted for additive white Gaussian noise (AWGN), coding-decoding, quantization, and bandwidth limitations.

Main Results:

  • NCS performance is significantly influenced by plant construction, including non-minimum phase (NMP) zeros and unstable poles.
  • Channel parameters, such as AWGN, coding-decoding efficiency, quantization levels, and bandwidth, critically affect system performance.
  • The derived performance expression quantifies the impact of these diverse factors.

Conclusions:

  • The study confirms that both system dynamics and communication channel characteristics jointly determine NCS performance.
  • The proposed control scheme demonstrates effectiveness in managing performance under communication constraints.
  • Simulation results validate the theoretical findings and the merits of the developed control strategy.