A resource-aware sliding mode control approach for Markov jump systems.

Area of Science:

• Control Theory
• Systems Engineering
• Stochastic Systems

Background:

• Markov jump systems (MJSs) are complex systems with randomly varying parameters.
• Traditional control methods can be computationally intensive.
• Resource-aware control is crucial for efficient system operation.

Purpose of the Study:

• To develop a novel sliding mode control (SMC) strategy for MJSs.
• To implement a resource-aware triggering mechanism for computational efficiency.
• To achieve simultaneous disturbance attenuation and system stability.

Main Methods:

• Introduction of a self-triggered policy for pre-computing execution times.
• Derivation of switching surfaces and system dynamics using a self-triggered sampling scheme.
• Formulation of sufficient conditions using linear matrix inequalities (LMIs).

Main Results:

• A novel self-triggered SMC law is proposed for MJSs.
• Guaranteed system stability and disturbance attenuation performance.
• Demonstrated time finiteness of switching surface reachability and desirable sliding motion.

Conclusions:

• The developed resource-aware triggering mechanism effectively saves computational resources.
• The proposed SMC strategy ensures system stability and disturbance attenuation for MJSs.
• Simulation results validate the effectiveness and superiority of the proposed control scheme.