IBLFs-Based Adaptive Event-Triggered Control for a Class of Stochastic Nonlinear Systems

Authors: tingting  gao
tieshan  li
Venue: IEEE_org_ICIST_2024_Conference
Published: 2024-08-14 03:15:03

Abstract: In this paper, an adaptive tracking control problem is addressed for nonstrict-feedback stochastic nonlinear systems subject to state constraints. Fuzzy logic systems (FLSs) are used to model unknown nonlinearities and avoid the algebraic loop arising from the system structure. Appropriate integral Barrier Lyapunov functions (IBLFs) are chosen so that time-varying full state constraints can be guaranteed directly rather than by transforming the constraint object. In the framework of backstepping technology, the relative threshold strategy is introduced to modify the adaptive control scheme so that the controller can be updated only after the trigger condition has been met, which reduces the update frequency of the controller and the loss of the actuator.

Main paper: 
 : 
 ( ) ( ) ( ) ( ) ( ) ( ) 1 1 d d d , 1, , 1 d d d , T i i i i T n n n x f x x t g x i n x f x u t g x yx   +  = + + =    -   = + +   =   (1) where   1 ,, T n n x x x R =    is the state vector, and all state variables satisfy ( ) Choose BLFs with the integral type as ( ) ( ) ( )EQUATION36 6 0 6 1 d , 1, , , j j j z c z j cj kt V j n kt    - == -+  (2)where the variable  denotes the member of the integrating range 0, j z   ,  
 
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