Stable fault-tolerant adaptive fuzzy/neural control for a turbine engine

Diao, Yixin; Passino, K.M.

doi:10.1109/87.918902

Cited by 149 publications

(5 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Substituting d * ðtÞ in (28), σ * ðtÞ in (29), and Δυ e ðtÞ in ( 23) into (27) yields Therefore, the matrixes S and P satisfying (24) can guarantee that the function V ðΔξ 1 ðtÞÞ in ( 25) is a solution to the inequality (16). Hence, the nonlinear robust faulttolerant controllers in ( 20) and ( 21) can regulate the shaft speeds of turbofan engines to asymptotically track the reference signals with dðtÞ ¼ 0 and σðtÞ ¼ 0.…”

Section: Nonlinear Robust Fault-tolerant Controllers For Turbofan Eng...mentioning

confidence: 99%

“…Consequently, the active nonlinear fault-tolerant control for turbofan engines has recently drawn great attention. According to modeling error and fault information learned by an online approximator, D. Yixin et al 29 treated turbofan engines as Takagi-Sugeno fuzzy models and designed adaptive controllers to achieve robust fault-tolerant control against engine deteriorations and component faults. The method strongly depends on the real-time engine analytical model and high accuracy fault information.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Nonlinear robust fault-tolerant control for turbofan engines with actuator faults

Cheng

Liu

2022

Proceedings of the Institution of Mechanical Engineers, Part G:

View full text Add to dashboard Cite

This paper investigates nonlinear robust fault-tolerant control for turbofan engines with actuator faults. The nonlinear robust fault-tolerant control method is proposed in this paper, which can guarantee the fault tolerance and robustness of turbofan engines when faults and disturbances occur. The design method is implemented in three steps: Firstly, the dynamic effects caused by actuator faults on turbofan engines are analyzed and then the multivariable polynomial state-space model of turbofan engines with actuator faults is proposed. Secondly, appropriate design parameters are chosen according to fault information. Thirdly, the nonlinear robust fault-tolerant control law for turbofan engines with actuator faults is designed by solving an optimization problem. In addition, stability and [Formula: see text] gain-like for turbofan engines with bounded disturbances and actuator faults are guaranteed by the proposed nonlinear robust fault-tolerant control method. The distinctive characteristic of the paper is that the nonlinear robust fault-tolerant control method for turbofan engines against actuator faults is proposed which can relax the accuracy requirements of the fault diagnosis subsystem and improve the fault-tolerant performance of the closed-loop control system. Simulations show that the nonlinear robust fault-tolerant control method has better control performances including transient responses, disturbance rejection, and fault tolerance for the turbofan engine with actuator faults.

show abstract

Section: Nonlinear Robust Fault-tolerant Controllers For Turbofan Eng...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Nonlinear robust fault-tolerant control for turbofan engines with actuator faults

Cheng

Liu

2022

Proceedings of the Institution of Mechanical Engineers, Part G:

View full text Add to dashboard Cite

show abstract

“…In recent years, many methods have been established to solve the problem of compensation for various actuator failures. such as multiple‐model, 1 pseudo‐inverse, 2 sliding mode control, 3 robust control, 4,5 probabilistic design, 6 fault detection and diagnosis design, 7,8 learning‐based method, 9 eigenstructure assignment 10 . The adaptive control method, which is especially suitable for systems with uncertainties and actuator failures, has attracted extensive attention, and many literatures have been applied, such as References 11‐15.…”

Section: Introductionmentioning

confidence: 99%

Adaptive compensation control of nonlinear systems with unknown actuator failures

Lü

Zhang

2023

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

In this paper, by using bound estimation method, Nussbaum function, K‐filters and higher‐order Lyapunov function, an adaptive output feedback compensation control scheme is proposed for uncertain nonlinear systems with infinite number of actuator failures and unknown control direction. A parametric model with unknown system uncertainties and infinite actuator failures is established, which is different from the existing results. This scheme ensures that closed‐loop signals are globally uniformly bounded. By properly selecting the design parameters, the tracking errors converges to a small neighborhood of the origin. Finally, two simulation examples are given to demonstrate its efficiency of the proposed design scheme.

show abstract

“…The traditional method can only be applied to limited steady-state points. For other working points, the SSMs are more dependent on interpolation or parameter scheduling methods, such as TS fuzzy model [16,17] and equilibrium manifold expansion (EME) model [18,19]. Compared with the SSMs directly established at the corresponding points, the accuracy of the model obtained by interpolation or other methods is relatively lower.…”

Section: Introductionmentioning

confidence: 99%

A State Space Modeling Method for Aero-Engine Based on AFOS-ELM

Chen

Pang

et al. 2022

Energies

View full text Add to dashboard Cite

State space models (SSMs) are important for multi-variable performance analysis and controller design of aero-engines. In order to solve the problems of the traditional state space modeling methods that rely on component-level models (CLMs) and cannot be carried out in real time, an aero-engine state space modeling method based on adaptive forgetting factor online sequential extreme learning machine (AFOS-ELM) is proposed in this paper. The structure of the extreme learning machine (ELM) is determined according to the form of the state space model, and the inverse-free ELM algorithm is used to automatically select the appropriate number of hidden nodes to improve the efficiency of offline initialization. The focus of the ELM on current operation performance is enhanced by the adaptive renewed forgetting factor, which reduces the impact of aero-engine history and deviated data on the current output and improves the accuracy of the model. Then, according to the analytical equation of the ELM model, the state space model of an aero-engine at each sampling time is obtained by using the partial derivative method. The simulation results based on engine test data show that the real-time performance and accuracy of the state space model established online in this paper can meet the needs of aero-engine control system requirement.

show abstract

Stable fault-tolerant adaptive fuzzy/neural control for a turbine engine

Cited by 149 publications

References 38 publications

Nonlinear robust fault-tolerant control for turbofan engines with actuator faults

Nonlinear robust fault-tolerant control for turbofan engines with actuator faults

Adaptive compensation control of nonlinear systems with unknown actuator failures

A State Space Modeling Method for Aero-Engine Based on AFOS-ELM

Contact Info

Product

Resources

About