Sequential output information based predictive control for event-triggered networked control systems.

Area of Science:

• Control Engineering
• Networked Systems
• Signal Processing

Background:

• Event-triggering in Networked Control Systems (NCSs) aims to optimize network usage by minimizing data transmissions.
• Transmitting output data, instead of estimated states, offers packet size reduction but complicates state observation due to delays.
• Existing observer-based prediction schemes struggle with performance degradation caused by delayed output information.

Purpose of the Study:

• To develop an improved event-triggered scheme for NCSs that enhances state observer performance.
• To address the challenges of delayed output information in NCSs by proposing a novel sequential output transmission method.
• To investigate the application of this scheme in controlling physical systems like inverted pendulums and DC motors.

Main Methods:

• A sequential observer is designed to leverage successive output information for more accurate state estimation.
• A prediction scheme is incorporated to compensate for delays arising from event-triggering, network latency, and data dropouts.
• Event-triggering is applied to both feedback and forward channels to further reduce network load.

Main Results:

• The proposed sequential output transmission scheme significantly improves state observer performance in NCSs.
• The integrated prediction scheme effectively mitigates the negative impacts of delays and dropouts on system control.
• Experimental validation on an inverted pendulum and a DC motor system demonstrates the practical efficacy of the approach.

Conclusions:

• The sequential output transmission strategy offers a practical and effective solution for enhancing control performance in NCSs.
• This method is particularly beneficial in scenarios with limited network bandwidth and communication uncertainties.
• The study highlights the potential of advanced observer and prediction techniques for robust NCS design.