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 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 Fault tolerant control for nonlinear systems using sliding mode and adaptive neural network estimator

2019 ◽  
Vol 24 (15) ◽  
pp. 11535-11544 ◽  
Author(s):  
Haiying Qi ◽  
Yiran Shi ◽  
Shoutao Li ◽  
Yantao Tian ◽  
Ding-Li Yu ◽  
...  
Keyword(s):  
Neural Network ◽  
Nonlinear Systems ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
Fault Tolerant Control ◽  
System Stability ◽  
Fault Estimation ◽  
Time Varying ◽  
Change Rate ◽  
The Impact

AbstractThis paper proposes a new fault tolerant control scheme for a class of nonlinear systems including robotic systems and aeronautical systems. In this method, a sliding mode control is applied to maintain system stability under the post-fault dynamics. A neural network is used as on-line estimator to reconstruct the change rate of the fault and compensate for the impact of the fault on the system performance. The control law and the neural network learning algorithms are derived using the Lyapunov method, so that the neural estimator is guaranteed to converge to the fault change rate, while the entire closed-loop system stability and tracking control is guaranteed. Compared with the existing methods, the proposed method achieved fault tolerant control for time-varying fault, rather than just constant fault. This greatly expands the industrial applications of the developed method to enhance system reliability. The main contribution and novelty of the developed method is that the system stability is guaranteed and the fault estimation is also guaranteed for convergence when the system subject to a time-varying fault. A simulation example is used to demonstrate the design procedure and the effectiveness of the method. The simulation results demonstrated that the post-fault is stable and the performance is maintained.

Active fault-tolerant control for vertical tail damaged aircraft with dissimilar redundant actuation system using integral sliding mode control

2018 ◽  
Vol 233 (7) ◽  
pp. 2361-2378 ◽  
Author(s):  
Salman Ijaz ◽  
Mirza T Hamayun ◽  
Lin Yan ◽  
Cun Shi
Keyword(s):  
Actuator Saturation ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
Fault Tolerant Control ◽  
Fault Estimation ◽  
Redundant Actuation ◽  
Severe Damage ◽  
Integral Sliding Mode ◽  
Actuation System ◽  
Electrohydraulic Actuator

The research about the dissimilar redundant actuation system has indicated the potential fault-tolerant capability in modern aircraft. This paper proposed a new design methodology to achieve fault-tolerant control of an aircraft equipped with dissimilar actuators and is suffered from vertical tail damage. The proposed design is based on the concept of online control allocation to redistribute the control signals among healthy actuators and integral sliding mode controller is designed to achieve the closed-loop stability in the presence of both component and actuator faults. To cope with severe damage condition, the aircraft is equipped with dissimilar actuators (hydraulic and electrohydraulic actuators). In this paper, the performance degradation due to slower dynamics of electrohydraulic actuator is taken in account. Therefore, the feed-forward compensator is designed for electrohydraulic actuator based on fractional-order control strategy. In case of failure of hydraulic actuator subject to severe damage of vertical tail, an active switching mechanism is developed based on the information of fault estimation unit. Additionally, a severe type of actuator failure so-called actuator saturation or actuator lock in place is also taken into account in this work. The proposed strategy is compared with the existing control strategies in the literature. Simulation results indicate the dominant performance of the proposed scheme. Moreover, the proposed controller is found robust with a certain level of mismatch between the actuator effectiveness level and its estimate.

Active Fault Tolerant Control Based on Fault Estimation

2014 ◽  
Vol 635-637 ◽  
pp. 1199-1202 ◽  
Author(s):  
Zheng Gao Hu ◽  
Guo Rong Zhao ◽  
Da Wang Zhou
Keyword(s):  
Active Fault ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
Fault Tolerant Control ◽  
Sliding Mode Observer ◽  
Fault Estimation ◽  
Control Law ◽  
Active Fault Tolerant Control ◽  
The Stability ◽  
Twisting Algorithm

For the chattering problem in the traditional sliding mode observer-based fault estimation, a second order sliding mode observer based on the Super-twisting algorithm was proposed. In order to avoid the cumbersome process of proving the stability of the Super-twisting algorithm, a Lyapunov function was adopted. An active fault tolerant control law was designed based on the fault estimation. Finally, simulation show the effectiveness of the proposed approach.

Neural Network Based Fault Tolerant Control for a Semi-Active Suspension

2019 ◽  
Author(s):  
Sergio Alberto Rueda Villanoba ◽  
Carlos Borrás Pinilla
Keyword(s):  
Neural Network ◽  
Control System ◽  
Fault Tolerant ◽  
Mr Damper ◽  
Fault Tolerant Control ◽  
Active Suspension ◽  
Suspension System ◽  
Vehicle Body ◽  
Force Model ◽  
The Neural Network

Abstract In this study a Neural Network based fault tolerant control is proposed to accommodate oil leakages in a magnetorheological suspension system based in a half car dynamic model. This model consists of vehicle body (spring mass) connected by the MR suspension system to two lateral wheels (unsprung mass). The semi-active suspension system is a four states nonlinear model; it can be written as a state space representation. The main objectives of a suspension are: Isolate the chassis from road disturbances (passenger comfort) and maintain contact between tire and road to provide better maneuverability, safety and performance. On the other hand, component faults/failures are inevitable in all practical systems, the shock absorbers of semi-active suspensions are prone to fail due to fluid leakage but quickly detect and diagnose this fault in the system, avoid major damage to the system and ensure the safety of the driver. To successfully achieve desirable control performance, it is necessary to have a damping force model which can accurately represent the highly nonlinear and hysteretic dynamic of the MR damper. To simulate parameters of the damper, a quasi-static model was applied, quasi-static approaches are based on non-newtonian yield stress fluids flow by using the Bingham MR Damper Model, relating the relative displacement of the piston, the frictional force, a damping constant, the stiffness of the elastic element of the damper and an offset force. The Fault detection and isolation module is based on residual generation algorithms. The residua r is computed as the difference between the displacement signal of functional and faulty model, when the residual is close to zero, the process is free of faults, while any change in r represents a faulty scheme then a wavelet transform, (Morlet wave function) is used to determine the natural frequencies and amplitudes of displacement and acceleration signal during the failure, this module provides parameters to the neural network controller in order to accommodate the failure using compensation forces from the remaining healthy damper. The neural network uses the error between the plant output and the neural network plant for computing the required electric current to correct the malfunction using the inverse dynamics function of the MR damper model. Consequently, a bump condition, and a random profile road (ISO 8608) described by the power spectral density (PSD) of its vertical displacement, is used as disturbance of control system. The performance of the proposed FTC structure is demonstrated trough simulation. Results shows that the control system could reduce the effect of the partial fault of the MR Damper on system performance.

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.

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