Sliding Mode Control for 2-D FMII Networked System Under Partially Known Fading Channel Information

Area of Science:

• Control Systems Engineering
• Networked Systems
• Stochastic Processes

Background:

• Networked systems are susceptible to channel uncertainties, impacting control performance.
• Fading channels introduce stochasticity, complicating system modeling and control design.
• The Fornasini-Marchesini (FMII) system is a key model for 2-D systems analysis.

Purpose of the Study:

• To develop a robust sliding mode control (SMC) scheme for 2-D FMII networked systems.
• To address control challenges under stochastic 2-D fading channel constraints.
• To optimize the control scheme using adaptive algorithms.

Main Methods:

• Characterization of 2-D fading channels using an extended 2-D hidden Markov process (HMP).
• Development of a 2-D FMII networked system model incorporating HMP.
• Derivation of SMC synthesis criteria for known and partially known transition probability matrices (TPM) and observation probability matrices (OPM).
• Application of particle swarm optimization (PSO) for adaptive parameter tuning and sliding mode domain optimization.

Main Results:

• A novel SMC scheme for 2-D FMII networked systems under 2-D fading channels was successfully developed.
• Criteria for SMC synthesis were established for both known and partially known HMP parameters (TPM and OPM).
• The particle swarm optimization (PSO) algorithm effectively tuned SMC parameters and optimized the sliding mode domain.

Conclusions:

• The proposed SMC scheme effectively manages uncertainties in 2-D fading channels for FMII systems.
• The developed control strategies are validated through thermal chemical and metal rolling process examples.
• The integration of HMP and PSO offers a robust solution for controlling 2-D networked systems in uncertain environments.