Neural Network-Based Adaptive Practical Prescribed-Time Control for a Helicopter System with State Constraints

Pure Feedback Control for Nonlinear Systems Based on Predefined-Time Performance Function

This paper investigates the predefined-time adaptive neural tracking control problem for a class of nonlinear pure feedback systems with full state constraints, and proves that all closed loop signals are predefined-time-bounded and the tracking error meets the preset performance specifications.

Robust Adaptive Neural Network-Based Backstepping Tracking for Second-Order Euler-Lagrange Systems with Unknown Parameters

A continuous adaptive control law is developed that eliminates chattering typically caused by discontinuous robust terms and proves that all closed-loop signals are uniformly ultimately bounded, achieving asymptotic trajectory tracking with smooth control inputs.

Adaptive Prescribed-Time Tracking Control for Output-Constrained Hydraulic Servo Systems with Time-Varying Parameters

This paper proposes an adaptive prescribed-time tracking control strategy based on the dynamic surface technique for hydraulic servo systems subject to time-varying parameters, external disturbances, and output constraints. First, a state-constrained transformation function is introduced to convert the strict output co...

Adaptive prescribed-time control for stochastic nonlinear systems over infinite horizon: A dynamic threshold strategy with application to ship maneuvering systems.

This paper studies the prescribed-time tracking control problem with output constraints for stochastic nonlinear systems over an infinite horizon, motivated by ship maneuvering dynamics. The steady-state tracking accuracy of existing methods is uncertain due to unknown system parameters, which may fail to meet high-pre...

Prescribed-time sliding mode control for uncertain nonlinear systems based on periodic delayed feedback and disturbance observer.

This paper addresses the trajectory tracking control problem of nonlinear systems subject to uncertain disturbances by proposing a unified prescribed-time control framework integrating disturbance observation and performance constraints. First, a prescribed-time disturbance observer with smooth adaptive gains and a tim...

Reinforcement Learning-Based Predefined-Time Consensus Control for Uncertain Multirobot Systems with Improved Prescribed Performance Function