scholarly journals Combining Artificial Intelligence and Advanced Techniques in Fault-Tolerant Control

Author(s):  
A. Vargas-Martínez ◽  
L. E. Garza-Castañón

We present the integration of artificial intelligence, robust, nonlinear and model reference adaptive control (MRAC)methods for fault-tolerant control (FTC). We combine MRAC schemes with classical PID controllers, artificial neuralnetworks (ANNs), genetic algorithms (GAs), H∞  ∞  ∞ ). The third scheme is an MRAC controller with a sliding mode controller (SMC). The fourth scheme is an MRAC controller with an ANN. The fifth scheme is an MRAC controller with a PID controller optimized by a GA. Finally, thelast scheme is an MRAC classical control system. The objective of this research is to generate more powerful FTCmethods and compare the performance of above schemes under different fault conditions in sensors and actuators.An industrial heat exchanger process was the test bed for these approaches. Simulation results showed that the useof Pattern Search Optimization and ANNs improved the performance of the FTC scheme because it makes the controlsystem more robust against sensor and actuator faults.control(H controls and sliding mode controls. Six different schemas are proposed: the first one is an MRAC with an artificial neural network and a PID controller whose parameters weretuned by a GA using Pattern Search Optimization. The second scheme is an MRAC controller with an H

2021 ◽  
Vol 13 (9) ◽  
pp. 168781402110454
Author(s):  
Ruinan Chen ◽  
Jian Ou

In this paper, a hybrid fault-tolerant control strategy is putted forward to improve the stability of the four-wheel independent drive (4WID) electric vehicle with motor failures. To improve the handling performance of the vehicle with in-wheel motor failures, the faults of in-wheel motors are analyzed and modeled. Then, a model reference adaptive fault observer was designed to observe the faults in real-time. Based on the observation results, there are designed a model predictive control (MPC) based high-performance active fault-tolerant control (AFTC) strategy and a sliding mode control based high-robust passive fault-tolerant control (PFTC) strategy. However, the fault observation results may not always be accurately. For this circumstance, a hybrid fault-tolerant control strategy was designed to make the control method find a balance between optimality and robustness. Finally, a series of simulations are conducted on a hardware-in-loop (HIL) real-time simulator, the simulation results show that the control strategy designed in this paper is effectiveness.


Author(s):  
Tong Li ◽  
Youmin Zhang ◽  
Brandon Gordon

In this paper, two sliding mode based fault tolerant control (SM-FTC) strategies are designed, implemented and flight-tested in a physical quadrotor unmanned helicopter under the propeller damage and actuator fault conditions. Sliding model control (SMC) is well known for its capability of handling uncertainty and is expected to be a robust controller. Based on the concept of sliding mode control, both passive and active fault tolerant controls have been designed and experimentally tested on a quadrotor UAV (unmanned aerial vehicle) test-bed, known as Qball-X4, available at Concordia University in the presence of actuator faults and propeller damages. These two types of controllers are carried out and compared through theoretical analysis, simulation, and experimental flight tests on the quadrotor UAV system. Good control performance has been achieved in the presence of actuator faults and propeller damages.


2021 ◽  
pp. 002029402110286
Author(s):  
Pu Yang ◽  
Peng Liu ◽  
ChenWan Wen ◽  
Huilin Geng

This paper focuses on fast terminal sliding mode fault-tolerant control for a class of n-order nonlinear systems. Firstly, when the actuator fault occurs, the extended state observer (ESO) is used to estimate the lumped uncertainty and its derivative of the system, so that the fault boundary is not needed to know. The convergence of ESO is proved theoretically. Secondly, a new type of fast terminal sliding surface is designed to achieve global fast convergence, non-singular control law and chattering reduction, and the Lyapunov stability criterion is used to prove that the system states converge to the origin of the sliding mode surface in finite time, which ensures the stability of the closed-loop system. Finally, the effectiveness and superiority of the proposed algorithm are verified by two simulation experiments of different order systems.


Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 643 ◽  
Author(s):  
Juan Tan ◽  
Yonghua Fan ◽  
Pengpeng Yan ◽  
Chun Wang ◽  
Hao Feng

The unmanned aerial vehicle (UAV) has been developing rapidly recently, and the safety and the reliability of the UAV are significant to the mission execution and the life of UAV. Sensor and actuator failures of a UAV are one of the most common malfunctions, threating the safety and life of the UAV. Fault-tolerant control technology is an effective method to improve the reliability and safety of UAV, which also contributes to vehicle health management (VHM). This paper deals with the sliding mode fault-tolerant control of the UAV, considering the failures of sensor and actuator. Firstly, a terminal sliding surface is designed to ensure the state of the system on the sliding mode surface throughout the control process based on the simplified coupling dynamic model. Then, the sliding mode control (SMC) method combined with the RBF neural network algorithm is used to design the parameters of the sliding mode controller, and with this, the efficiency of the design process is improved and system chattering is minimized. Finally, the Simulink simulations are carried out using a fault tolerance controller under the conditions where accelerometer sensor, gyroscope sensor or actuator failures is assumed. The results show that the proposed control strategy is quite an effective method for the control of UAVs with accelerometer sensor, gyroscope sensor or actuator failures.


Author(s):  
Jun Zhou ◽  
Jing Chang ◽  
Zongyi Guo

The paper describes the design of a fault-tolerant control scheme for an uncertain model of a hypersonic reentry vehicle subject to actuator faults. In order to improve superior transient performances for state tracking, the proposed method relies on a back-stepping sliding mode controller combined with an adaptive disturbance observer and a reference vector generator. This structure allows for a faster response and reduces the overshoots compared to linear conventional disturbance observers based sliding mode controller. Robust stability and performance guarantees of the overall closed-loop system are obtained using Lyapunov theory. Finally, numerical simulations results illustrate the effectiveness of the proposed technique.


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