Finite-time adaptive neural command filtered control for pure-feedback time-varying constrained nonlinear systems with actuator faults

Finite‐time command filter‐based adaptive tracking control for nonstrict feedback nonlinear systems with full‐state restrictions and unmodeled dynamics

“…Remark This paper differs from Wu et al [41] in the following three aspects. (i) The research problems are different.…”

“…(i) The research problems are different. Command filter‐based adaptive control problem is discussed for a class of nonstrict feedback constrained nonlinear systems with input unmodeled dynamics in this paper, whereas command filter based adaptive tracking control problem was studied for a class of pure‐feedback constrained nonlinear systems with actuator faults in Wu et al [41]. (ii) In order to deal with input unmodeled dynamics, an extra updating parameter is constructed in this paper, whereas the actuator faults including loss of control effectiveness and stuck faults in the linear form are handled in Wu et al [41].…”

“…Command filter‐based adaptive control problem is discussed for a class of nonstrict feedback constrained nonlinear systems with input unmodeled dynamics in this paper, whereas command filter based adaptive tracking control problem was studied for a class of pure‐feedback constrained nonlinear systems with actuator faults in Wu et al [41]. (ii) In order to deal with input unmodeled dynamics, an extra updating parameter is constructed in this paper, whereas the actuator faults including loss of control effectiveness and stuck faults in the linear form are handled in Wu et al [41]. (iii) In order to tackle unknown control gain function, the integral Lyapunov function is introduced in Step $$$ n $$$ in this paper, whereas the quadratic Lyapunov function is introduced by constructing the input uncertain term in Step $$$ n $$$ in Wu et al [41].…”

“…(ii) In order to deal with input unmodeled dynamics, an extra updating parameter is constructed in this paper, whereas the actuator faults including loss of control effectiveness and stuck faults in the linear form are handled in Wu et al [41]. (iii) In order to tackle unknown control gain function, the integral Lyapunov function is introduced in Step $$$ n $$$ in this paper, whereas the quadratic Lyapunov function is introduced by constructing the input uncertain term in Step $$$ n $$$ in Wu et al [41].…”

“…By constructing a new state‐dependent switching law and adaptive fuzzy control signal, the existing restrictions on subsystems of switched systems were relaxed, all subsystems of the considered system were allowed to be unstabilizable. In Wu et al [41], by introducing the compensation signals and adding them into the whole Lyapunov function, and with the help of the defined compact set in stability analysis, it was strictly proved that all signals were semi‐globally practical finite‐time stable (SGPFS) and all the states were within the specified open set.…”