Realization of Prescribed Performance Control for DC Converter System in DC Microgrid via Finite-Time Sliding Mode Observer

Author(s):  
Xingchen Xu ◽  
Zhigang Zeng ◽  
Qingshan Liu
Actuators ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 282
Author(s):  
Peiyu Wang ◽  
Liangkuan Zhu ◽  
Chunrui Zhang ◽  
Chengcheng Wang ◽  
Kangming Xiao

The actuator of a particleboard glue-dosing system, the glue pump motor, is affected by external disturbances and unknown uncertainty. In order to achieve accurate glue-flow tracking, in this paper, a glue pump motor compound control method was designed. First, the prescribed performance control method is used to improve the transient behaviors, and the error of the glue flow tracking is guaranteed to converge to a preset range, as a result of the design of an appropriate performance function. Second, two extended state observers were designed to estimate the state vector and the disturbance, in order to improve the robustness of the controlled system. To further strengthen the steady-state performance of the system, the sliding-mode dynamic surface control method was introduced to compensate for uncertainties and disturbances. Finally, a Lyapunov stability analysis was conducted, in order to prove that all of the signals are bounded in a closed-loop system, and the effectiveness and feasibility of the proposed method were verified through numerical simulation.


Actuators ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 323
Author(s):  
Pu Yang ◽  
Zixin Wang ◽  
Zhiqing Zhang ◽  
Xukai Hu

In this paper, an adaptive sliding mode fault-tolerant control scheme based on prescribed performance control and neural networks is developed for an Unmanned Aerial Vehicle (UAV) quadrotor carrying a load to deal with actuator faults. First, a nonsingular fast terminal sliding mode (NFTSM) control strategy is presented. In virtue of the proposed strategy, fast convergence and high robustness can be guaranteed without stimulating chattering. Secondly, to obtain correct fault magnitudes and compensate the failures actively, a radial basis function neural network-based fault estimation scheme is proposed. By combining the proposed fault estimation strategy and the NFTSM controller, an active fault-tolerant control algorithm is established. Then, the uncertainties caused by load variation are explicitly considered and compensated by the presented adaptive laws. Moreover, by synthesizing the proposed sliding mode control and prescribed performance control (PPC), an output error transformation is defined to deal with state constraints and provide better tracking performance. From the Lyapunov stability analysis, the overall system is proven to be uniformly asymptotically stable. Finally, numerical simulation based on a quadrotor helicopter is carried out to validate the effectiveness and superiority of the proposed algorithm.


Author(s):  
Dandan Zheng ◽  
Jianjun Luo ◽  
Zeyang Yin ◽  
Zhaohui Dang

This paper studies the problem of autonomous rendezvous in the libration point orbit without relative velocity measurement information. The proposed rendezvous algorithm consists of the finite-time-convergent differentiator and the finite-time prescribed performance controller. Wherein, the differentiator is used to compute the unknown relative velocity between the target and the chaser spacecraft. The novel differentiator-based finite-time prescribed performance controller ensures that the rendezvous error converges to an arbitrarily small prescribed region in finite time in spite of the presence of additive bounded disturbances. Furthermore, the prescribed convergence rate can be also achieved simultaneously. The associated stability proof is constructive and accomplished by the development of a Lyapunov function candidate. Numerical simulations on a final rendezvous approach example are provided to demonstrate the effectiveness and robustness of the proposed control algorithm.


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