Prescribed-Time Asymptotic Tracking Control of Strict Feedback Systems With Time-Varying Parameters and Unknown Control Direction

The practical preset time fault‐tolerant control (FTC) problem is explored in this article for uncertain Euler–Lagrange systems with input saturation and guaranteed performance. To cope with the uncertainty of the Euler–Lagrange systems, the adaptive neural network (NN) is exploited to approximate the unknown continuous function. Most existing results that consider input saturation and actuator faults simultaneously need to design compensation strategies separately, which increases the complexity of control algorithms. To overcome the above obstacle, the Nussbaum gain technique is used to deal with the effects of input saturation and actuator faults in this article. Besides, with the help of error transformation technology and speed function, the proposed control algorithm can ensure that the tracking error converges within the preset time and its overshoot is constrained within the prescribed performance boundaries. Furthermore, the boundedness of all closed‐loop system signals is confirmed. Finally, comparative simulation results are depicted to highlight the superiority of the designed control algorithm.

Section: Problem Formulation and Preliminariessupporting

confidence: 57%

Practical preset time fault‐tolerant control of uncertain Euler–Lagrange systems with input saturation and guaranteed performance

Hu,

Yan,

Wang

et al. 2024

“…To remove the initial condition restriction, a composite function is designed for global prescribed time tracking control 29 . In Reference 30, a novel global preset time tracking control method is investigated. The transformation of states in Reference 30 is more concise than the result of Reference 29.…”

Section: Introductionmentioning

confidence: 99%

“…In Reference 30, a novel global preset time tracking control method is investigated. The transformation of states in Reference 30 is more concise than the result of Reference 29.…”

Section: Introductionmentioning

confidence: 99%

Enhanced extended state observer based prescribed time tracking control of wheeled mobile robot with slipping and skidding

Qin,

Yan,

et al. 2024

This article focuses on the trajectory tracking control for a perturbed wheeled mobile robot (WMR) with slipping and skidding. The external disturbances and uncertainties caused by the slipping and skidding compose the “total” disturbance. By analyzing the stable state of the controlled system, the WMR reference model driven by a favorable disturbance is constructed. This article proposes an enhanced extended state observer (EESO) to reckon the difference between the “total” disturbance and the favorable disturbance. Then, a practical prescribed time tracking method is developed. By introducing a time‐dependent scaling function, the initial value restriction can be relaxed, and the peaking phenomenon caused by the EESO can be tolerated. With the proposed EESO and the prescribed time tracking controller, the estimation error is input‐to‐state stable, and the tracking control of WMR with global prescribed performance is achieved. Simulation results show the advantages.

“…Chen et al discuss the global exponential stability of nonlinear systems with an unknown time‐varying control coefficient 33 . Asymptotic tracking control of systems with an unknown time‐varying control gain is resolved by Shi et al 34 Moreover, the above‐mentioned results 33,34 are only suitable for systems with single unknown control gain, while in practical systems, multiple unknown control gains are more general. Command filtering control for nonlinear MIMO saturated systems with multiple unknown control coefficients are designed by Yu et al using Nussbaum function‐based methods 35 .…”

Section: Introductionmentioning

confidence: 99%

Nussbaum‐based robust adaptive control for nonlinear switching systems with switching unknown control coefficients

Tang

Yang

Chen

et al. 2023

This paper develops a robust adaptive dynamic surface control (DSC) design approach for switching strict feedback nonlinear systems with multiple switching control gains and unknown control directions. To capture the multiple unknown control directions, we design multiple Nussbaum‐type gains for every subsystem. Based on this Nussbaum‐type gain design, we construct a common Lyapunov function for all subsystems via backstepping technique, which can ensure the system stability under the existence of random switches. Meanwhile, the problem of multiple switching control gains is resolved by this means. To obviate repeated differentiation and decrease computation complexity, the dynamic surface control technique is introduced. Finally, two simulation examples are provided to validate the effectiveness of the developed method.