Optimal modified performance of MIMO networked control systems with multi-parameter constraints

Area of Science:

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

Background:

• Networked Control Systems (NCSs) face challenges including channel noise, packet dropouts, and quantization.
• Existing performance metrics may not adequately address systems without integrators.
• Multi-input Multi-output (MIMO) systems introduce complexity in control and analysis.

Purpose of the Study:

• To investigate and optimize the modified performance of MIMO NCSs under various communication impairments.
• To introduce a novel tracking performance index for NCSs, particularly for plants without an integrator.
• To analyze the relationship between system performance and factors like encoding-decoding, channel noise, packet dropouts, and plant characteristics.

Main Methods:

• Utilizing coprime factorization and partial fraction methods to achieve optimal modified performance.
• Developing a new tracking performance index to ensure consistent tracking error.
• Analyzing the influence of non-minimum phase (NMP) zeros, unstable poles, and their directions on performance.

Main Results:

• The optimal modified performance is intrinsically linked to the plant's non-minimum phase (NMP) zeros and unstable poles, including their directions.
• Packet dropout probability, channel noise, and encoding-decoding strategies significantly affect the optimal modified performance.
• The proposed tracking performance index effectively manages tracking errors in systems lacking an integrator.

Conclusions:

• The study provides a theoretical framework for enhancing MIMO NCS performance under realistic network conditions.
• Understanding the interplay between plant dynamics and network impairments is crucial for optimal control design.
• The developed methods and index offer practical insights for designing robust and efficient NCSs.