3 research outputs found
Adaptive Fuzzy Tracking Control for Nonlinear State Constrained Pure-Feedback Systems With Input Delay via Dynamic Surface Technique
This brief constructs the adaptive backstepping control scheme for a class of
pure-feedback systems with input delay and full state constraints. With the
help of Mean Value Theorem, the pure-feedback system is transformed into
strict-feedback one. Barrier Lyapunov functions are employed to guarantee all
of the states remain constrained within predefined sets. By introducing the
Pade approximation method and corresponding intermediate, the impact generated
by input delay on the output tracking performance of the system can be
eliminated. Furthermore, a low-pass filter driven by a newly-defined control
input, is employed to generate the actual control input, which facilitates the
design of backstepping control. To approximate the unknown functions with a
desired level of accuracy, the fuzzy logic systems (FLSs) are utilized by
choosing appropriate fuzzy rules, logics and so on. The minimal learning
parameter (MLP) technique is employed to decrease the number of nodes and
parameters in FLSs, and dynamic surface control (DSC) technique is leveraged to
avoid so-called "explosion of complexity". Moreover, smooth robust compensators
are introduced to circumvent the influences of external disturbance and
approximation errors. By stability analysis, it is proved that all of signals
in the closed-loop system are semi-globally ultimately uniform bounded, and the
tracking error can be within a arbitrary small neighbor of origin via selecting
appropriate parameters of controllers. Finally, the results of numerical
illustration are provided to demonstrate the effectiveness of the designed
method.Comment: arXiv admin note: text overlap with arXiv:2310.1540
Finite-Time Adaptive Fuzzy Tracking Control for Nonlinear State Constrained Pure-Feedback Systems
This paper investigates the finite-time adaptive fuzzy tracking control
problem for a class of pure-feedback system with full-state constraints. With
the help of Mean-Value Theorem, the pure-feedback nonlinear system is
transformed into strict-feedback case. By employing finite-time-stable like
function and state transformation for output tracking error, the output
tracking error converges to a predefined set in a fixed finite interval. To
tackle the problem of state constraints, integral Barrier Lyapunov functions
are utilized to guarantee that the state variables remain within the prescribed
constraints with feasibility check. Fuzzy logic systems are utilized to
approximate the unknown nonlinear functions. In addition, all the signals in
the closed-loop system are guaranteed to be semi-global ultimately uniformly
bounded. Finally, two simulation examples are given to show the effectiveness
of the proposed control strategy