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Open AccessJournal ArticleDOI

Non-affine parameter dependent LPV model and LMI based adaptive control for turbofan engines

TLDR
The contribution of this work lies in the combination of linear system control and nonlinear system control methods to design an effective controller for the turbofan engine and to provide a new way for turb ofan engine control research.
About
This article is published in Chinese Journal of Aeronautics.The article was published on 2019-03-01 and is currently open access. It has received 23 citations till now. The article focuses on the topics: Adaptive control & Robust control.

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Citations
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Journal ArticleDOI

Development of parametric reduced-order model for consequence estimation of rare events

TL;DR: This work proposes a k-nearest neighbor (kNN)-based parametric reduced-order model (PROM) for consequence estimation of rare events to enhance numerical robustness with respect to parameter change.
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Improved nonlinear MPC for aircraft gas turbine engine based on semi-alternative optimization strategy

TL;DR: In this paper, a semi-alternative optimization strategy based on model predictive control is proposed to achieve the complicated aircraft engine control, where a nonlinear state-space model is generated as the predictive model on the basis of a baseline engine model.
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Recent research progress on airbreathing aero-engine control algorithm

TL;DR: In this paper , the authors provide a summary report of recent research progress on air-breathing aero-engine control to help researchers working on this topic, including uncertainty problem, multiobjective and multivariable control, fault-tolerant control, distributed control system, and airframe/propulsion integrated control system.
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Aero-Engine Real-Time Models and Their Applications

TL;DR: An up-to-date review on aero-engine real-time modeling methods, model adaptation techniques, and applications for the last several decades is provided.
Journal ArticleDOI

Robust Resilient Control Based on Multi-Approximator for the Uncertain Turbofan System With Unmeasured States and Disturbances

TL;DR: In this paper, a resilient anti-disturbance control for uncertain turbofan system subject to unmeasured states and multiple disturbances is studied, where a state observer and a disturbance observer are jointly constructed to estimate the state and unknown disturbance, and the estimation on disturbance is used in the feedforward controller to reject the disturbances and the state estimation is applied to the resilient output feedback controller.
References
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Journal ArticleDOI

Survey Research on gain scheduling

TL;DR: Current research on gain scheduling is clarifying customary practices as well as devising new approaches and methods for the design of nonlinear control systems.
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Nearly optimal control laws for nonlinear systems with saturating actuators using a neural network HJB approach

TL;DR: It is shown that the constrained optimal control law has the largest region of asymptotic stability (RAS) and the result is a nearly optimal constrained state feedback controller that has been tuned a priori off-line.
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Online actor-critic algorithm to solve the continuous-time infinite horizon optimal control problem

TL;DR: An online algorithm based on policy iteration for learning the continuous-time optimal control solution with infinite horizon cost for nonlinear systems with known dynamics, which finds in real-time suitable approximations of both the optimal cost and the optimal control policy, while also guaranteeing closed-loop stability.
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Affine parameter-dependent Lyapunov functions and real parametric uncertainty

TL;DR: These LMI-based tests are applicable to constant or time-varying uncertain parameters and are less conservative than quadratic stability in the case of slow parametric variations, and they often compare favorably with /spl mu/ analysis for time-invariant parameter uncertainty.
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Survey of Gain-Scheduling Analysis & Design

TL;DR: The scope of this paper includes the main theoretical results and design procedures relating to continuous gain-scheduling (in the sense of decomposition of non-linear design into linear sub-problems) control with the aim of providing both a critical overview and a useful entry point into the relevant literature.
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