Control of Nonlinear Networked Cascade Control System under Multi-channel Quantization and Event-triggered Mechanism

The article delves into the control of nonlinear networked cascade control systems (NCCSs) under multi-channel quantization and event-triggered mechanisms. Traditional single-loop control systems often fall short in precise control of complex systems, whereas cascade control systems (CCSs) enhance control quality through an additional control link. The integration of CCSs with networked control systems (NCSs) forms networked cascade control systems (NCCSs), which face challenges such as network congestion and data packet loss. The study introduces an improved adaptive event-triggered mechanism (AETM) and dynamic quantization strategy to address these issues. The AETM, composed of multiple dynamic sub-functions, alleviates network burden, while the dynamic quantization parameter, coordinated by the quantized signal and original parameters, avoids singularity problems. The paper also considers actuator saturation and nonlinear systems, providing a comprehensive approach to improving NCCS performance. The main contributions include the development of a T-S fuzzy NCCS model and the design of state feedback controllers. The effectiveness of the proposed methods is validated through a simulation example, demonstrating the system's stability and performance under the designed conditions.