Predefined-Time Prescribed Performance Funnel Control for Stochastic Multiagent Systems With Input Continuous...

Area of Science:

• Control Theory
• Systems Engineering
• Nonlinear Dynamics

Background:

• Stochastic nonlinear multiagent systems (MASs) present complex control challenges.
• Existing control methods often struggle with precise tracking and stability guarantees in predefined timeframes.
• Quantization and initial state dependencies can hinder controller performance.

Purpose of the Study:

• To address the predefined-time tracking control problem for stochastic nonlinear MASs.
• To develop a novel control strategy that ensures stability and accurate tracking within a specified time.
• To eliminate controller chattering and dependence on initial system states.

Main Methods:

• Introduction of a novel continuous-time hysteretic quantizer for seamless level transitions.
• Development of a deferred activation function to remove initial state dependence in prescribed performance funnel control.
• Design of a controller guaranteeing semi-global practical predefined-time stability.

Main Results:

• The proposed hysteretic quantizer effectively eliminates controller chattering.
• The deferred activation function removes dependence on initial state values.
• The control strategy ensures semi-global practical predefined-time stability for all closed-loop signals.
• Satisfactory tracking performance for desired signals is achieved.

Conclusions:

• The developed control approach provides a robust solution for predefined-time tracking in stochastic nonlinear MASs.
• The method demonstrates efficacy and robustness in meeting prescribed performance specifications.
• Numerical simulations validate the effectiveness of the proposed control strategy.