scholarly journals Adaptive Fault Estimation for Hyperbolic PDEs

Mathematics ◽  
2021 ◽  
Vol 9 (14) ◽  
pp. 1613
Author(s):  
Yuan Yuan ◽  
Xiaodong Xu ◽  
Stevan Dubljevic
Keyword(s):  
External Disturbance ◽  
Hyperbolic Partial Differential Equations ◽  
Fault Estimation ◽  
Estimation Errors ◽  
Fault Type ◽  
Fault Parameters ◽  
Adaptive Laws ◽  
Original Plant ◽  
Estimation Scheme ◽  
Types Of Faults

The new adaptive fault estimation scheme is proposed for a class of hyperbolic partial differential equations in this paper. The multiplicative actuator and sensor faults are considered. There are two cases that require special consideration: (1). only one type of fault (actuator or sensor) occurs; (2). two types of faults occurred simultaneously. To solve the problem of fault estimation, three challenges need to be solved: (1). No prior information of fault type is known; (2). Unknown faults are always coupled with state and input; (3). Only one boundary measurement is available. The original plant is converted to Observer canonical form. Two filters are proposed and novel adaptive laws are developed to estimate unknown fault parameters. With the help of the proposed update laws, the true state of the faulty plant can be estimated by the proposed observers composed of two filters. By selecting a suitable Lyapunov function, it is proved that under unknown external disturbance, the estimation errors of state parameters and fault parameters decay to arbitrarily small value. Finally, the validity of the proposed observer and adaptive laws is verified by numerical simulation.

scholarly journals Robust Fast Adaptive Fault Estimation for T-S Fuzzy Markovian Jumping Systems with Mode-Dependent Time-Varying State Delays

2021 ◽  
Vol 2021 ◽  
pp. 1-26
Author(s):  
Chao Sun ◽  
Shengjuan Huang ◽  
Libing Wu ◽  
Suhuan Yi
Keyword(s):  
Adaptive Estimation ◽  
Estimation Error ◽  
External Disturbance ◽  
Estimation Algorithm ◽  
Fault Estimation ◽  
Time Varying ◽  
Markovian Jumping ◽  
Markovian Jumping Systems ◽  
Stochastically Stable ◽  
Estimation Scheme

This paper studies the problem of actuator fault estimation for a class of T-S fuzzy Markovian jumping systems, which is subject to mode-dependent interval time-varying delays and norm-bounded external disturbance. Based on the given fast adaptive estimation algorithm and by employing a novel Lyapunov–Krasovskii function candidate, a robust fault estimation scheme is proposed to estimate faults whose derivative is bounded. With this improved method, the proposed fault estimator minimizes the effect of disturbance on the estimation error and reduces the conservatism of systems stability results simultaneously. To be specific, an improved mode-dependent criterion for the existence of the fault estimation observer is established to guarantee the error dynamic system to be stochastically stable with a prescribed H ∞ performance and reduce the conservatism of designing procedure. Finally, three numerical examples are given to show the effectiveness of the proposed method.

scholarly journals Sliding Mode Fault Tolerant Control for a Quadrotor with Varying Load and Actuator Fault

Actuators ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 323
Author(s):  
Pu Yang ◽  
Zixin Wang ◽  
Zhiqing Zhang ◽  
Xukai Hu
Keyword(s):  
Fault Tolerant ◽  
Sliding Mode ◽  
Fault Tolerant Control ◽  
Fault Estimation ◽  
Terminal Sliding Mode ◽  
Performance Control ◽  
Prescribed Performance ◽  
Prescribed Performance Control ◽  
Adaptive Laws ◽  
Estimation Scheme

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.

scholarly journals Sensorless Pedalling Torque Estimation Based on Motor Load Torque Observation for Electrically Assisted Bicycles

Actuators ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 88
Author(s):  
Riccardo Mandriota ◽  
Stefano Fabbri ◽  
Matthias Nienhaus ◽  
Emanuele Grasso
Keyword(s):  
External Disturbance ◽  
State Observer ◽  
Position Estimation ◽  
Load Torque ◽  
Estimation Errors ◽  
Position Information ◽  
Longitudinal Dynamics ◽  
Rotor Position ◽  
Electrically Assisted ◽  
Motor Load

The need for reducing the cost of and space in Electrically Assisted Bicycles (EABs) has led the research to the development of solutions able to sense the applied pedalling torque and to provide a suitable electrical assistance avoiding the installation of torque sensors. Among these approaches, this paper proposes a novel method for the estimation of the pedalling torque starting from an estimation of the motor load torque given by a Load Torque Observer (LTO) and evaluating the environmental disturbances that act on the vehicle longitudinal dynamics. Moreover, this work shows the robustness of this approach to rotor position estimation errors introduced when sensorless techniques are used to control the motor. Therefore, this method allows removing also position sensors leading to an additional cost and space reduction. After a mathematical description of the vehicle longitudinal dynamics, this work proposes a state observer capable of estimating the applied pedalling torque. The theory is validated by means of experimental results performed on a bicycle under different conditions and exploiting the Direct Flux Control (DFC) sensorless technique to obtain the rotor position information. Afterwards, the identification of the system parameters together with the tuning of the control system and of the LTO required for the validation of the proposed theory are thoroughly described. Finally, the capabilities of the state observer of estimating an applied pedalling torque and of recognizing the application of external disturbance torques to the motor is verified.

Parameter-dependent actuator fault estimation for vehicle active suspension systems based on RBFNN

2021 ◽  
pp. 095440702199301
Author(s):  
Wenping Xue ◽  
Pan Jin ◽  
Kangji Li
Keyword(s):  
Fault Tolerant ◽  
External Disturbance ◽  
Active Suspension ◽  
Fault Estimation ◽  
Linear Matrix ◽  
Actuator Fault ◽  
Mass Variation ◽  
Fe Method ◽  
Comparison Results ◽  
Parameter Dependent

The actuator fault estimation (FE) problem is addressed in this study for the quarter-car active suspension system (ASS) with consideration of the sprung mass variation. Firstly, the ASS is modeled as a parameter-dependent system with actuator fault and external disturbance input. Then, a parameter-dependent FE observer is designed by using the radial basis function neural network (RBFNN) to approximate the actuator fault. In addition, the design conditions are turned into a linear matrix inequality (LMI) problem which can be easily solved with the aid of LMI toolbox. Finally, simulation and comparison results are given to show the accuracy and rapidity of the proposed FE method, as well as good adaptability against the sprung mass variation. Moreover, a simple FE-based active fault-tolerant control (AFTC) strategy is provided to further demonstrate the effectiveness and applicability of the proposed FE method.

scholarly journals Fault Diagnosis of Coal Mining Machinery Based on State Parameters

2020 ◽  
Author(s):  
Dong Song
Keyword(s):  
Fault Diagnosis ◽  
Coal Mining ◽  
Fault Type ◽  
Fault Parameters ◽  
Underground Coal Mines ◽  
Mining Machinery ◽  
The Status ◽  
New Perspective ◽  
Judgment Condition ◽  
Cutting Unit

The reliable operation of coal mining machinery acts as an important guarantee for safe productions in underground coal mines. The status monitoring and fault diagnosis of traditional coal mining machinery mainly rely on threshold judgments. However, a single judgment condition and a long fault propagation chain can be found in the method of threshold judgments, which make it difficult to accurately seek the fault type. By using the data analysis of state parameters for coal mining machinery, fault parameters and propagation paths can be analyzed effectively. This paper takes the cutting unit of a certain type of bolter miners as an example, a static and dynamic numerical analysis method of the cutting unit of bolter miners are established by virtue of FTA-Petri net models and BP-Firefly neural networks, which can provide a new perspective for fault diagnosis of coal mining machinery.

scholarly journals Robust Adaptive Sliding Mode Fault Tolerant Control for Nonlinear System with Actuator Fault and External Disturbance

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Liang Zheng ◽  
Xuelian Dong ◽  
Qian Luo ◽  
Menglan Zeng ◽  
Xinping Yang ◽  
...  
Keyword(s):  
Control Method ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
External Disturbance ◽  
Fault Tolerant Control ◽  
Actuator Fault ◽  
Estimation Errors ◽  
Adaptive Sliding Mode ◽  
Sliding Motion ◽  
Robust Adaptive

In this paper, an adaptive sliding mode fault tolerant control (ASMFTC) approach is proposed for a class of nonlinear systems with actuator fault, uncertainty, and external disturbance. Specifically, first, a novel observer is proposed to estimate the state, actuator fault, and external disturbance. Then, by utilising the observed information, a novel output sliding mode observer is constructed. In the control method, an adaptive law and two compensators are designed to attenuate the unknown estimation errors, actuator fault, and disturbance. Furthermore, the reaching ability of the sliding motion is analysed and the H-infinite performance is introduced to ensure the robustness of the system. Finally, a flexible single joint manipulator system and a two-cart system are used to verify the effectiveness of the proposed method.

Disturbance Estimation, Compensation, and Dynamic Shaping: New Approach and an Application to Output Stabilization of Multiple Cooperative Control

2014 ◽  
Vol 137 (1) ◽  
Author(s):  
Sang-Chul Lee ◽  
Kyungmin Jeong ◽  
Hyo-Sung Ahn
Keyword(s):  
Cooperative Control ◽  
Design Method ◽  
External Disturbance ◽  
Experimental Tests ◽  
Consensus Algorithm ◽  
Actual System ◽  
Multiple Systems ◽  
Disturbance Estimation ◽  
Output Stabilization ◽  
Estimation Scheme

This paper introduces a new disturbance estimation scheme, and a possible application to relative output stabilization of multiple systems. Using the proposed disturbance estimation scheme, total unknown external disturbance applied to a plant is estimated and compensated. Moreover, the model difference between an actual system and a desired system is also estimated and compensated. For the purpose of general use of the disturbance estimation scheme as an unknown input observer (UIO), a parameterized design method is given, even for the unstable and nonminimum phase systems. For the relative output stabilization of multiple systems, second-order consensus algorithm is additionally used. A case study, simulations, and experimental tests sequentially validate the proposed estimation and control methods.

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