Virtual-command-based model reference adaptive control for abrupt structurally damaged aircraft

Zhang, Jing; Yang, Xin; Yang, Lingyu

doi:10.1016/j.ast.2018.04.043

Cited by 14 publications

(3 citation statements)

References 23 publications

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“…The ideal sliding state is achieved by the existence of a finite time (tf) such that the solution of the system satisfies s(k) = 0 for all t ≥ tf (Zhao, Wu & Ma, 2013).…”

Section: Optimal Sliding Surfacementioning

confidence: 99%

Optimal Second Order Sliding Control for the Robust Tracking of a 2-Degree-of-Freedom Helicopter System based on Metaheuristics and Artificial Neural Networks

JOUIROU,

BOUKADIDA,

BENAMOR

2023

SIC

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This paper presents a novel formulation for a Second-order Sliding Controller (SOSMC) for the trajectory tracking of a 2-degree-of-freedom (DoF) helicopter system based on the combination of a robust Second-order Discrete Sliding Mode Controller (SDOSMC) and a Linear Quadratic Regulator (LQR). The combination of these two approaches guarantees the effectiveness of the SOSMC in the face of uncertainties and disturbances. A new approach based on the resolution of the Sylvester equation is proposed in order to design a sliding surface that would ensure the optimal performance of the Sliding Mode Control (SMC). The performance of the SMC heavily depends on the selection of the sliding surface. The reformulation of the control problem is treated as a multi-objective optimization problem, and a new objective function based on dynamic aggregation is proposed for this purpose. The main contribution of this article lies in using the set of solutions provided by metaheuristics to leverage the capabilities of Deep Learning (DL) and to predict the optimal solution in terms of performance. The proposed control methodology is applied to control the pitch and yaw axes of the Quanser helicopter system. The simulation results, along with a comparative analysis were included to support the importance and efficacy of the suggested control technique.

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“…The ideal sliding state is achieved by the existence of a finite time (tf) such that the solution of the system satisfies s(k) = 0 for all t ≥ tf (Zhao, Wu & Ma, 2013).…”

Section: Optimal Sliding Surfacementioning

confidence: 99%

Optimal Second Order Sliding Control for the Robust Tracking of a 2-Degree-of-Freedom Helicopter System based on Metaheuristics and Artificial Neural Networks

JOUIROU,

BOUKADIDA,

BENAMOR

2023

SIC

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“…An effective fault-tolerant feedback controller is required to compensate the damage, and to guarantee the safety of aircraft. References [12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27] investigated adaptive control schemes to compensate the structural uncertainties due to aircraft failures or damage. References 3,13 examined FTC algorithm for an aircraft that suffers from vertical tail loss.…”

Section: Introductionmentioning

confidence: 99%

“…Simulating the effect of wing tip loss and controlling the damage airplane were examined in the literature 22,23 in which an adaptive proportional integral derivative 22 and an adaptive MRAC algorithm with nonlinear dynamic inversion 23 were applied to the dynamics of the wing-damaged airplane. MRAC scheme was also applied on a wing-damaged airplane in Zhang et al 24 where a virtual-command was introduced to the standard MRAC to maintain the tracking error within a small range and provide more robustness. In Chowdhary et al, 25 a neural network-based MRAC strategy as the fast inner-loop control algorithm, and a linear controller as the outer-loop attitude controller was proposed and implemented on a transport category aircraft with 25% left wing damage and a 50% of sudden right wing-loss.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear robust adaptive control of an airplane with structural damage

Asadi

Ahmadi

2020

Proceedings of the Institution of Mechanical Engineers, Part G:

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This article investigates the design of a novel nonlinear robust adaptive control architecture to stabilize and control an airplane in the presence of left-wing damage. Damage effect is modeled by considering the sudden mass and inertia changes, center of gravity, and aerodynamic variations. The novel nonlinear control algorithm applies a state predictor as well as the error between the real damaged dynamics and a virtual model based on the nominal aircraft dynamics in the control loop of the adaptive strategy. The projection operator is used for the purpose of robustness of the adaptive control algorithm. The stability of the proposed nonlinear robust adaptive controller is demonstrated applying the Lyapunov stability theory. The performance of the proposed controller is compared with two previous successful algorithms, which are implemented on the Generic Transport Model airplane to accommodate wing damage. Numerical simulations demonstrate the effectiveness and advantages of the proposed robust adaptive algorithm regarding two other algorithms of adaptive sliding mode and L 1 adaptive control.

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Fault-Tolerant Control for Aircraft with Structural Damage Using Sparse Online Gaussian Process Regression

Lee,

Kim,

Zewge

et al. 2024

Int. J. Aeronaut. Space Sci.

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This paper presents the design of data-driven fault-tolerant control using sparse online Gaussian process regression (SOGPR) to stabilize an aircraft with left-wing damage. The structural damage causes changes in mass, moment of inertia, center of gravity, and aerodynamic coefficients. These parameter variations deteriorate the performance of model-based nonlinear control methods. Hence, Gaussian process-based nonlinear dynamic inversion (GP-NDI) is proposed to compensate for uncertainties in situations of structural damage. Unlike parametric adaptive control approaches, Gaussian process regression is a non-parametric method that does not need prior information about uncertainties. And the proposed method implements SOGPR to reduce computational time and memory by incrementally updating the mean and variance. To compensate for the error in the estimated uncertainty, a robust control input is designed. In addition, a weighted delete score is used to improve the transient response. Numerical simulation results are compared with model reference adaptive control (MRAC) and nonlinear disturbance observer (NDO) to analyze a stabilizing and tracking performance in a structural damage situation.

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Virtual-command-based model reference adaptive control for abrupt structurally damaged aircraft

Cited by 14 publications

References 23 publications

Optimal Second Order Sliding Control for the Robust Tracking of a 2-Degree-of-Freedom Helicopter System based on Metaheuristics and Artificial Neural Networks

Optimal Second Order Sliding Control for the Robust Tracking of a 2-Degree-of-Freedom Helicopter System based on Metaheuristics and Artificial Neural Networks

Nonlinear robust adaptive control of an airplane with structural damage

Fault-Tolerant Control for Aircraft with Structural Damage Using Sparse Online Gaussian Process Regression

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