Sliding mode fault-tolerant control for unmanned marine vehicles with signal quantization and time-delay

2020 ◽  
Vol 215 ◽  
pp. 107882
Author(s):  
Li-Ying Hao ◽  
He Zhang ◽  
Hui Li ◽  
Tie-Shan Li
Keyword(s):  
Time Delay ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
Fault Tolerant Control ◽  
Signal Quantization ◽  
Marine Vehicles

Aero‐Engine DCS Fault‐Tolerant Control with Markov Time Delay Based On Augmented Adaptive Sliding Mode Observer

2018 ◽  
Vol 22 (2) ◽  
pp. 788-802
Author(s):  
Ledi Zhang ◽  
Shousheng Xie ◽  
Yu Zhang ◽  
Litong Ren ◽  
Bin Zhou ◽  
...  
Keyword(s):  
Time Delay ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
Fault Tolerant Control ◽  
Sliding Mode Observer ◽  
Adaptive Sliding Mode ◽  
Aero Engine

Active fault-tolerant control of a Schon̈flies parallel manipulator based on time delay estimation

Robotica ◽  
2021 ◽  
pp. 1-18
Author(s):  
Pegah Ghaf-Ghanbari ◽  
Mahmood Mazare ◽  
Mostafa Taghizadeh
Keyword(s):  
Time Delay ◽  
Feedback Linearization ◽  
Parallel Manipulator ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
Fault Tolerant Control ◽  
Time Delay Estimation ◽  
Lyapunov Theory ◽  
Delay Estimation ◽  
Fault Estimation

Abstract In this paper, a new hybrid fault-tolerant control (FTC) strategy based on nonsingular fast integral-type terminal sliding mode (NFITSM) and time delay estimation (TDE) is proposed for a Schönflies parallel manipulator. In order to detect, isolate, and accommodate actuator faults, TDE is used as an online fault estimation algorithm. Stability analysis of the closed-loop system is performed using Lyapunov theory. The proposed controller performance is compared with conventional sliding mode and feedback linearization control methods. The obtained results reveal the superiority of the proposed FTC based on TDE and NFITSM.

scholarly journals Distributed Cooperative Sliding Mode Fault-Tolerant Control for Multiple High-Speed Trains Based on Actor-Critic Neural Network

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Xiangyu Kong ◽  
Tong Zhang
Keyword(s):  
Neural Network ◽  
Time Delay ◽  
High Speed ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
Tracking Error ◽  
Fault Tolerant Control ◽  
Actuator Faults ◽  
High Speed Trains ◽  
Critic Neural Network

This article investigates the cooperative fault-tolerant control problem for multiple high-speed trains (MHSTs) with actuator faults and communication delays. Based on the actor-critic neural network, a distributed sliding mode fault-tolerant controller is designed for MHSTs to solve the problem of actuator faults. To eliminate the negative effects of unknown disturbances and time delay on train control system, a distributed radial basis function neural network (RBFNN) with adaptive compensation term of the error is designed to approximate the nonlinear disturbances and predict the time delay, respectively. By calculating the tracking error online, an actor-critic structure with RBFNN is used to estimate the switching gain of the distributed controller, which reduces the chattering phenomenon caused by sliding mode control. The global stability and ultimate bounded of all signals of the closed-loop system are proposed with strict mathematic proof. Simulations show that the proposed method has superior effectiveness and robustness compared with other fault-tolerant control methods, which ensures the safe operation of MHSTs under moving block conditions.

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