$${L_\infty }$$ Fault Estimation and Fault-Tolerant Control for Nonlinear Systems by T–S Fuzzy Model Method with Local Nonlinear Models

2021 ◽  
Author(s):  
Yang Wang ◽  
Tieshan Li ◽  
Yue Wu ◽  
Ximing Yang ◽  
C. L. Philip Chen ◽  
...  
Keyword(s):  
Nonlinear Systems ◽  
Fault Tolerant ◽  
Nonlinear Models ◽  
Fuzzy Model ◽  
Fault Tolerant Control ◽  
Fault Estimation ◽  
Model Method

Fault-tolerant controller design with fault estimation capability for a class of nonlinear systems using generalized Takagi-Sugeno fuzzy model

2019 ◽  
Vol 41 (15) ◽  
pp. 4218-4229 ◽  
Author(s):  
Alireza Navarbaf ◽  
Mohammad Javad Khosrowjerdi
Keyword(s):  
Nonlinear Systems ◽  
Controller Design ◽  
Fault Tolerant ◽  
Fuzzy Model ◽  
Fault Estimation ◽  
Linear Matrix ◽  
Wide Range ◽  
Satisfy Lipschitz Condition ◽  
Unknown Disturbances ◽  
Takagi Sugeno

In this paper, a new design approach to construct a fault-tolerant controller (FTC) with fault estimation capability is proposed using a generalized Takagi-Sugeno (T-S) fuzzy model for a class of nonlinear systems in the presence of actuator faults and unknown disturbances. The generalized T-S fuzzy model consists of some local models with multiplicative nonlinear terms that satisfy Lipschitz condition. Besides covering a very wide range of nonlinear systems with a smaller number of local rules in comparison with the conventional T-S fuzzy model and hence having less computational burden, the existence of the multiplicative nonlinear term solves the uncontrollability issues that the other generalized T-S fuzzy models with additive nonlinear terms dealt with. A state/fault observer designed for the considered generalized T-S fuzzy model and then, a dynamic FTC law based on the estimated fault information is proposed and sufficient design conditions are given in terms of linear matrix inequalities (LMIs). It can be shown that the number of LMIs are less than that of previously proposed methods and then feasibility of our method is more likely. The effectiveness of the proposed FTC approach is verified using a nonlinear mass-spring-damper system.

Novel neural observer based fault estimation, reconstruction and fault-tolerant control scheme for nonlinear systems

2021 ◽  
Vol 41 (1) ◽  
pp. 355-386
Author(s):  
Muhammad Taimoor ◽  
Xiao Lu ◽  
Wasif Shabbir ◽  
Chunyang Sheng ◽  
Muhammad Samiuddin
Keyword(s):  
Neural Network ◽  
Nonlinear Systems ◽  
Fault Detection ◽  
Fault Tolerant ◽  
Fault Tolerant Control ◽  
High Gain ◽  
Fault Isolation ◽  
Fault Estimation ◽  
High Gain Observer ◽  
Highly Nonlinear

This research is concerned with the adaptive neural network observer based fault approximation and fault-tolerant control of time-varying nonlinear systems. A new strategy for adaptively updating the weights of neural network parameters is proposed to enhance fault detection accuracy. Lyapunov function theory (LFT) is applied for adaptively updating the learning parameters weights of multi-layer neural network (MLNN). The purpose of using adaptive learning rates to update the weight parameters of MLNN is to obtain the global minima for highly nonlinear functions without increasing the computational complexities and costs and increase the efficacy of fault detection. Results of the proposed adaptive MLNN observer are compared with conventional MLNN observer and high gain observer. The effects of various faults or failures are studied in detail. The proposed strategy shows more robustness to disturbances, uncertainties, and unmodelled system dynamics compared to the conventional neural network, high gain observer and other existing techniques in literature. Fault tolerant control (FTC) schemes are also proposed to account for the presence of various faults and failures. Separate sliding mode control (SMC) based FTC schemes are designed for each observer to ensure stability of the faulty system. The suggested strategy is validated on Boeing 747 100/200 aircraft. Results demonstrate the effectiveness of both the proposed adaptive MLNN observer and the FTC based on the proposed adaptive MLNN compared to the conventional MLNN, high gain observer and other existing schemes in literature. Comparison of the performance of all the strategies validates the superiority of the proposed strategy and shows that the FTC based on proposed adaptive MLNN strategy provides better robustness to various situations such as disturbances and uncertainties. It is concluded that the proposed strategy can be integrated into the aircraft for the purpose of fault diagnosis, fault isolation and FTC scheme for increasing the performance of the system.

scholarly journals Fuzzy Predictive Fault-Tolerant Control for Time-Delay Nonlinear Systems with Partial Actuator Failures

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-20 ◽  
Author(s):  
Huiyuan Shi ◽  
Ping Li ◽  
Chengli Su ◽  
Jingxian Yu
Keyword(s):  
Nonlinear Systems ◽  
State Space ◽  
Discrete Time ◽  
Fault Tolerant ◽  
Fuzzy Model ◽  
Fault Tolerant Control ◽  
Model Description ◽  
Time Varying ◽  
Actuator Failures ◽  
Stable Conditions

A fuzzy predictive fault-tolerant control (FPFTC) scheme is proposed for a wide class of discrete-time nonlinear systems with uncertainties, interval time-varying delays, and partial actuator failures as well as unknown disturbances, in which the main opinions focus on the relevant theory of FPFTC based on Takagi-Sugeno (T-S) fuzzy model description of these systems. The T-S fuzzy model represents the discrete-time nonlinear system in the form of the discrete uncertain time-varying delay state space, which is firstly constructed by a set of local linear models and the nonlinear membership functions. The novel improved state space model can be further obtained by extending the output tracking error to the constructed model. Then the fuzzy predictive fault-tolerant control law based on this extended model is designed, which can increase more control degrees of freedom. Utilizing Lyapunov-Krasovskill theory, less conservative delay-range-dependent stable conditions in terms of linear matrix inequality (LMI) constraints are given to ensure the asymptotically robust stability of closed-loop system. Meanwhile, the optimized cost function and H-infinity performance index are introduced to the stable conditions to guarantee the robust performance and antidisturbance capability. The simulation results on the temperature control of a strong nonlinear continuous stirred tank reactor (CSTR) show that the proposed control scheme is feasible and effective.

Adaptive optimal fault-tolerant control scheme for a class of strict-feedback nonlinear systems

2018 ◽  
Vol 41 (4) ◽  
pp. 1079-1087 ◽  
Author(s):  
Jiao Dai ◽  
Chunsheng Liu ◽  
Jingliang Sun
Keyword(s):  
Nonlinear Systems ◽  
Fault Tolerant ◽  
Fault Tolerant Control ◽  
Lyapunov Stability Theory ◽  
Adaptive Dynamic Programming ◽  
Fault Estimation ◽  
Control Law ◽  
Feedback Form ◽  
Estimation And Control ◽  
Strict Feedback

An active optimal fault-tolerant control (FTC) scheme for a class of nonlinear systems in strict-feedback form in the presence of partial loss of actuator effectiveness faults is proposed, using backstepping design technique and adaptive dynamic programming (ADP) algorithm to compensate the effects of failure. The proposed FTC scheme consists of feedforward controller that achieve the objective of fault-tolerant and feedback optimal controller, which can guarantee the performance index function is minimized. Since fault estimation and control law parameters are updated online, the control system has an adaptive failure compensation capability so as to reconfigure the control law in real time in response to failure indications. Based on Lyapunov stability theory, the whole closed-loop system is guaranteed to be ultimately uniformly bounded. Finally, the effectiveness of the proposed method is demonstrated by simulation.

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