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Improved predictive control approach to networked control systems based on quantization dependent Lyapunov function.

Xiaoming Tang1, Shuang Yang1, Li Deng1

  • 1College of Automation, Chongqing University of Posts and Telecommunications, 400065, China.

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Summary
This summary is machine-generated.

This study enhances model predictive control (MPC) for networked control systems (NCSs) facing packet loss and quantization. The improved approach guarantees closed-loop stability and offers better performance than existing methods.

Keywords:
Actuator saturationMPCNCSsPacket lossQuantization

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Area of Science:

  • Control Systems Engineering
  • Networked Control Systems
  • Optimization Theory

Background:

  • Networked control systems (NCSs) face challenges like packet loss, quantization, and actuator saturation.
  • Existing model predictive control (MPC) methods for NCSs can be conservative.
  • Lyapunov function methods are crucial for stability analysis in control systems.

Purpose of the Study:

  • To develop an improved model predictive control (MPC) approach for linear discrete-time systems with packet loss, quantization, and actuator saturation.
  • To reduce conservatism in networked MPC by employing a quantization-dependent Lyapunov function (QDLF).
  • To enhance control performance by optimizing weighting on feedback laws.

Main Methods:

  • Application of the quantization-dependent Lyapunov function (QDLF) method.
  • Solving an infinite horizon optimization problem to derive a quantized state-feedback controller.
  • Extension of the method to multiple-input systems.

Main Results:

  • The proposed networked MPC approach yields less conservative results compared to previous work.
  • Closed-loop stability of the system is guaranteed.
  • The method demonstrates improved control performance through optimized weighting strategies.
  • Effectiveness is validated via a numerical example.

Conclusions:

  • The developed QDLF-based networked MPC effectively addresses packet loss, quantization, and saturation in linear discrete-time systems.
  • The proposed controller ensures closed-loop stability and superior performance.
  • The approach is robust and applicable to multiple-input systems, offering a significant advancement in NCS control.