Nearly optimal sliding mode fault-tolerant control for affine nonlinear systems with state constraints

2016 ◽  
Vol 216 ◽  
pp. 78-88 ◽  
Author(s):  
Quan-Yong Fan ◽  
Guang-Hong Yang
Keyword(s):  
Nonlinear Systems ◽  
State Constraints ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
Fault Tolerant Control ◽  
Affine Nonlinear Systems

An Output Feedback Based Adaptive Robust Fault Tolerant Control Scheme for a Class of Nonlinear Systems

2009 ◽  
Author(s):  
Shreekant Gayaka ◽  
Bin Yao
Keyword(s):  
Nonlinear Systems ◽  
Output Feedback ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
A Priori ◽  
Fault Tolerant Control ◽  
Modeling Uncertainties ◽  
Learning Capabilities ◽  
Robust Adaptive ◽  
Priori Information

In this paper we present an output feedback based Adaptive Robust Fault Tolerant Control (ARFTC) strategy to solve the problem of output tracking in presence of actuator failures, disturbances and modeling uncertainties for a class of nonlinear systems. The class of faults addressed here include stuck actuators, actuator loss of efficiency or a combination of the two. We assume no a priori information regarding the instant of failure, failure pattern or fault size. The ARFTC combines the robustness of sliding mode controllers with the online learning capabilities of adaptive control to accommodate sudden changes in system parameters due to actuator faults. Comparative simulation studies are carried out on a nonlinear hypersonic aircraft model, which shows the effectiveness of the proposed scheme over back-stepping based robust adaptive fault-tolerant control.

Adaptive Neural-Fuzzy Sliding-Mode Fault-Tolerant Control for Uncertain Nonlinear Systems

2017 ◽  
Vol 47 (8) ◽  
pp. 2268-2278 ◽  
Author(s):  
Shiping Wen ◽  
Michael Z. Q. Chen ◽  
Zhigang Zeng ◽  
Tingwen Huang ◽  
Chaojie Li
Keyword(s):  
Nonlinear Systems ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
Fault Tolerant Control ◽  
Uncertain Nonlinear Systems ◽  
Fuzzy Sliding Mode ◽  
Neural Fuzzy

RobustH∞sliding mode observer‐based fault‐tolerant control for One‐sided Lipschitz nonlinear systems

2019 ◽  
Vol 21 (1) ◽  
pp. 114-129 ◽  
Author(s):  
Abbas Rastegari ◽  
Mohammad Mehdi Arefi ◽  
Mohammad Hassan Asemani
Keyword(s):  
Nonlinear Systems ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
Fault Tolerant Control ◽  
Sliding Mode Observer ◽  
Lipschitz Nonlinear Systems

scholarly journals Active fault tolerant control of nonlinear systems: The cart-pole example

2011 ◽  
Vol 21 (3) ◽  
pp. 441-445 ◽  
Author(s):  
Marcello Bonfè ◽  
Paolo Castaldi ◽  
Nicola Mimmo ◽  
Silvio Simani
Keyword(s):  
Nonlinear Systems ◽  
Measurement Errors ◽  
Active Fault ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
Classical Model ◽  
Design Procedure ◽  
Fault Tolerant Control ◽  
Fault Detection And Diagnosis ◽  
Active Fault Tolerant Control

Active fault tolerant control of nonlinear systems: The cart-pole exampleThis paper describes the design of fault diagnosis and active fault tolerant control schemes that can be developed for nonlinear systems. The methodology is based on a fault detection and diagnosis procedure relying on adaptive filters designed via the nonlinear geometric approach, which allows obtaining the disturbance de-coupling property. The controller reconfiguration exploits directly the on-line estimate of the fault signal. The classical model of an inverted pendulum on a cart is considered as an application example, in order to highlight the complete design procedure, including the mathematical aspects of the nonlinear disturbance de-coupling method based on the nonlinear differential geometry, as well as the feasibility and efficiency of the proposed approach. Extensive simulations of the benchmark process and Monte Carlo analysis are practical tools for assessing experimentally the robustness and stability properties of the developed fault tolerant control scheme, in the presence of modelling and measurement errors. The fault tolerant control method is also compared with a different approach relying on sliding mode control, in order to evaluate benefits and drawbacks of both techniques. This comparison highlights that the proposed design methodology can constitute a reliable and robust approach for application to real nonlinear processes.

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