scholarly journals Fault Diagnosis and Fault-Tolerant Control of Uncertain Robot Manipulators Using High-Order Sliding Mode

2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Mien Van ◽  
Pasquale Franciosa ◽  
Dariusz Ceglarek
Keyword(s):  
Fault Diagnosis ◽  
Velocity Measurement ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
Robot Manipulator ◽  
Robot Manipulators ◽  
Fault Tolerant Control ◽  
High Order ◽  
Component Faults ◽  
Uncertain Robot

A robust fault diagnosis and fault-tolerant control (FTC) system for uncertain robot manipulators without joint velocity measurement is presented. The actuator faults and robot manipulator component faults are considered. The proposed scheme is designed via an active fault-tolerant control strategy by combining a fault diagnosis scheme based on a super-twisting third-order sliding mode (STW-TOSM) observer with a robust super-twisting second-order sliding mode (STW-SOSM) controller. Compared to the existing FTC methods, the proposed FTC method can accommodate not only faults but also uncertainties, and it does not require a velocity measurement. In addition, because the proposed scheme is designed based on the high-order sliding mode (HOSM) observer/controller strategy, it exhibits fast convergence, high accuracy, and less chattering. Finally, computer simulation results for a PUMA560 robot are obtained to verify the effectiveness of the proposed strategy.

scholarly journals An SVM-Based Neural Adaptive Variable Structure Observer for Fault Diagnosis and Fault-Tolerant Control of a Robot Manipulator

2020 ◽  
Vol 10 (4) ◽  
pp. 1344 ◽  
Author(s):  
Farzin Piltan ◽  
Alexander E. Prosvirin ◽  
Muhammad Sohaib ◽  
Belem Saldivar ◽  
Jong-Myon Kim
Keyword(s):  
Fault Diagnosis ◽  
Fault Tolerant ◽  
Robot Manipulator ◽  
Variable Structure ◽  
Fault Tolerant Control ◽  
High Order ◽  
Support Vector ◽  
Structure Control ◽  
Hybrid Controller ◽  
Order Variable

A robot manipulator is a multi-degree-of-freedom and nonlinear system that is used in various applications, including the medical area and automotive industries. Uncertain conditions in which a robot manipulator operates, as well as its nonlinearities, represent challenges for fault diagnosis and fault-tolerant control (FDC) that are addressed through the proposed FDC technique. A machine-learning-based neural adaptive, high-order, variable structure observer for fault diagnosis (FD) and adaptive, modern, fuzzy, backstepping, variable structure control for use in a fault-tolerant control (FC) algorithm, are proposed in this paper. In the first stage, a variable structure observer is proposed as an FD technique for the robot manipulator. The chattering phenomenon associated with the variable structure observer(VSO) is solved using a high-order variable structure observer. Then, the dynamic behavior estimation performance in the high-order variable structure observer is improved by incorporating a neural network algorithm in the FD pipeline. This adaptive technique is also effective in improving the robustness of the fault signal estimation. Moreover, support vector machines (SVMs) that can derive adaptive threshold values are used to categorize faults. To design an effective fault-tolerant controller (FC), an adaptive modern fuzzy backstepping variable structure controller is used in this study. First, a new variable structure controller is designed. Next, to increase robustness and reduce high-frequency oscillations in uncertain conditions, a backstepping algorithm is used in parallel with the variable structure controller to design the backstepping variable structure controller. To design an effective hybrid controller, a fuzzy algorithm is integrated into the backstepping variable structure controller to create a fuzzy backstepping variable structure controller. Then, to improve the robustness and reliability of the FC, a neural adaptive. high-order. variable structure observer is applied to the fuzzy backstepping variable structure controller to design a modern fuzzy backstepping variable structure controller. An adaptive algorithm is used to fine-tune the variable structure coefficients and reduce the effect of faults on the robot manipulator. The effectiveness of the selected algorithm is validated using a PUMA robot manipulator. The neural adaptive. high-order variable structure observer improves the average performance for the identification of various faults by about 27% and 29.2%, compared with the neural high-order variable structure observer and variable structure observer, respectively.

Robust fault-tolerant control for uncertain robot manipulators based on adaptive quasi-continuous high-order sliding mode and neural network

2015 ◽  
Vol 229 (8) ◽  
pp. 1425-1446 ◽  
Author(s):  
Mien Van ◽  
Hee-Jun Kang
Keyword(s):  
Neural Network ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
Robot Manipulators ◽  
Fault Tolerant Control ◽  
Stability And Convergence ◽  
Fault Estimation ◽  
The Neural Network ◽  
Fault Information ◽  
Uncertain Robot

This paper investigates a robust fault-tolerant control scheme for uncertain robot manipulators. The proposed scheme is designed via active fault-tolerant control method by combining a fault estimation scheme with a novel robust adaptive quasi-continuous second-order sliding mode (AQC2S) controller, so as to accommodate not only system failures but also uncertainties. First, a neural network based fault estimation is designed to online approximate the unknown uncertainties and faults. The estimated uncertainty and fault information are then used to compensate in advance for the effects of uncertainties in fault-free operation and both uncertainties and faults in fault operation. To eliminate the neural network compensation error, QC2S with adaptation gain, named as adaptive QC2S (AQC2S), is proposed. By integrating the advantages of the neural network observer and the AQC2S controller, the integrated scheme has a good capability to accommodate both the uncertainties and faults with chattering-free, higher position tracking accuracy, and no requirement of prior knowledge of the fault information. The stability and convergence of the proposed fault-tolerant control system is proved theoretically. Simulation results for a PUMA560 robot demonstrate the effectiveness of the proposed algorithm.

scholarly journals Active Fault-Tolerant Control of a Quadcopter against Time-Varying Actuator Faults and Saturations Using Sliding Mode Backstepping Approach

2019 ◽  
Vol 9 (19) ◽  
pp. 4010 ◽  
Author(s):  
Ngoc Phi Nguyen ◽  
Sung Kyung Hong
Keyword(s):  
Fault Diagnosis ◽  
Active Fault ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
Fault Tolerant Control ◽  
Lyapunov Theory ◽  
Fault Estimation ◽  
Time Varying ◽  
Actuator Faults ◽  
Active Fault Tolerant Control

Fault-tolerant control is becoming an interesting topic because of its reliability and safety. This paper reports an active fault-tolerant control method for a quadcopter unmanned aerial vehicle (UAV) to handle actuator faults, disturbances, and input constraints. A robust fault diagnosis based on the H ∞ scheme was designed to estimate the magnitude of a time-varying fault in the presence of disturbances with unknown upper bounds. Once the fault estimation was complete, a fault-tolerant control scheme was proposed for the attitude system, using adaptive sliding mode backstepping control to accommodate the actuator faults, despite actuator saturation limitation and disturbances. The Lyapunov theory was applied to prove the robustness and stability of the closed-loop system under faulty operation. Simulation results show the effectiveness of the fault diagnosis scheme and proposed controller for handling actuator faults.

scholarly journals Advanced Adaptive Fault Diagnosis and Tolerant Control for Robot Manipulators

Energies ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 1281 ◽  
Author(s):  
Farzin Piltan ◽  
Cheol-Hong Kim ◽  
Jong-Myon Kim
Keyword(s):  
Fault Diagnosis ◽  
Fault Detection ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
Fault Tolerant Control ◽  
Sliding Surface ◽  
Surface Slope ◽  
Extended State ◽  
Mode Estimation ◽  
Fuzzy Sliding Mode

In this paper, an adaptive Takagi–Sugeno (T–S) fuzzy sliding mode extended autoregressive exogenous input (ARX)–Laguerre proportional integral (PI) observer is proposed. The proposed T–S fuzzy sliding mode extended-state ARX–Laguerre PI observer adaptively improves the reliability, robustness, estimation accuracy, and convergence of fault detection, estimation, and identification. For fault-tolerant control in the presence of uncertainties and unknown conditions, an adaptive fuzzy sliding mode estimation technique is introduced. The sliding surface slope gain is significant to improve the system’s stability, but the sliding mode technique increases high-frequency oscillation (chattering), which reduces the precision of the fault diagnosis and tolerant control. A fuzzy procedure using a sliding surface and actual output position as inputs can adaptively tune the sliding surface slope gain of the sliding mode fault-tolerant control technique. The proposed robust adaptive T–S fuzzy sliding mode estimation extended-state ARX–Laguerre PI observer was verified with six degrees of freedom (DOF) programmable universal manipulation arm (PUMA) 560 robot manipulator, proving qualified efficiency in detecting, isolating, identifying, and tolerant control for faults inherent in sensors and actuators. Experimental results showed that the proposed technique improves the reliability of the fault detection, estimation, identification, and tolerant control.

High order sliding mode observer‐based backstepping fault‐tolerant control for induction motor

2019 ◽  
Vol 21 (1) ◽  
pp. 33-42 ◽  
Author(s):  
Amal Guezmil ◽  
Hanen Berriri ◽  
Remus Pusca ◽  
Anis Sakly ◽  
Raphael Romary ◽  
...  
Keyword(s):  
Induction Motor ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
Fault Tolerant Control ◽  
High Order ◽  
Sliding Mode Observer

scholarly journals Fault Diagnosis and Fault-Tolerant Control Scheme for Quadcopter UAVs with a Total Loss of Actuator

Energies ◽  
2019 ◽  
Vol 12 (6) ◽  
pp. 1139 ◽  
Author(s):  
Ngoc Nguyen ◽  
Sung Hong
Keyword(s):  
Fault Diagnosis ◽  
Active Fault ◽  
Control Method ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
Fault Tolerant Control ◽  
Total Loss ◽  
Actuator Faults ◽  
Control Scheme ◽  
Robust Adaptive

Fault-tolerant control has drawn attention in recent years owning to its reliability and safe flight during missions. In this article, an active fault-tolerant control method is proposed to control a quadcopter in the presence of actuator faults and disturbances. Firstly, the dynamics of the quadcopter are presented. Secondly, a robust adaptive sliding mode Thau observer is presented to estimate the time-varying magnitudes of actuator faults. Thirdly, a fault-tolerant control scheme based on sliding mode control and reconfiguration technique is designed to maintain the quadcopter at the desired position despite the presence of faults. Unlike previous studies, the proposed method aims to integrate the fault diagnosis and a fault-tolerant control scheme into a single unit with total loss of actuator. Simulation results illustrate the efficiency of the suggested algorithm.

Sign in / Sign up

Export Citation Format

Share Document