Model Predictive Control for Helicopter Shipboard Operations in the Ship Airwakes

Ngo, Tri D.; Sultan, Cornel

doi:10.2514/1.g001243

Cited by 32 publications

(5 citation statements)

References 21 publications

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“…The latter adjusts the controller parameters and structure in real-time depending on the former FDD results to ensure that the fault system achieves acceptable dynamics. The typical design methods for AFTCS include the interacting multiple model, [16][17][18] feedback linearization, 3,19,20 model predictive control, 21,22 Eigen structure assignment, 23 Model Reference Adaptive Control (MRAC), [24][25][26][27][28][29] and so on. With the development of the control theory, AFTC techniques have been successfully applied to the aviation system.…”

Section: Introductionmentioning

confidence: 99%

“…With the development of the control theory, AFTC techniques have been successfully applied to the aviation system. [19][20][21][22][23][24][25][26][27] MRAC, a representative adaptive FTC approach, excels in coping with uncertainties and faults in the system. In contrast to the fixed-gain controller, MRAC has a flexible structure and can adjust the control gain in real-time with disturbance influence changes, thereby weakening the disturbance influence.…”

Section: Introductionmentioning

confidence: 99%

“…The typical design methods for AFTCS include the interacting multiple model, 16–18 feedback linearization, 3,19,20 model predictive control, 21,22 Eigen structure assignment, 23 Model Reference Adaptive Control (MRAC), 24–29 and so on. With the development of the control theory, AFTC techniques have been successfully applied to the aviation system 19–27 …”

Section: Introductionmentioning

confidence: 99%

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Improved model reference‐based adaptive nonlinear dynamic inversion for fault‐tolerant flight control

Liu

Ming

et al. 2023

Intl J Robust & Nonlinear

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Due to lack of robustness, Nonlinear Dynamic Inversion (NDI) control cannot resist the influence of disturbances. In this paper, an adaptive fault‐tolerant control method, called Improved Model Reference‐based Adaptive NDI (IMR‐ANDI), is proposed and applied to develop a fault‐tolerant flight controller to improve robustness to faults and disturbances. To improve the estimation accuracy, this paper also modified the piecewise‐constant adaptation, which improves the accuracy of adaptive estimation without increasing the sampling frequency. Moreover, a low‐pass filter is introduced to the control law creatively to weaken the disturbance of high‐frequency dynamics to the adaptation, which balances the dynamic performance and robustness as well as prevents the system oscillation. Finally, a fault‐tolerant flight controller is developed based on the IMR‐ANDI and verified under the actuator fault and center of gravity variations. All simulation and hardware‐in‐the‐loop experiment results conform to the theoretical analysis, indicating that the developed IMR‐ANDI fault‐tolerant controller is robust to faults and disturbances and can achieve expected control performance.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Improved model reference‐based adaptive nonlinear dynamic inversion for fault‐tolerant flight control

Liu

Ming

et al. 2023

Intl J Robust & Nonlinear

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“…Some recent researches are addressed here. Ngo and Sultan (2016) have investigated a model predictive control for shipboard operations of a generic helicopter in the presence of ship air-wakes. Rakotomamonjy and Truong (2017) have presented a vision-based landing system for a helicopter using pole placement.…”

Section: Introductionmentioning

confidence: 99%

A vision-aided fuzzy adaptive sliding mode controller for autonomous landing of a nonlinear model helicopter on a moving marine platform

Pakro

Nikkhah

2022

AEAT

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Purpose A vision-assisted fuzzy adaptive sliding mode controller is presented in this research and implemented on a nonlinear helicopter model, which is about to land on a moving ship. Stabilization of the dynamics and tracking the landing path are required, at the same time. This study aims to take one step closer to fully autonomous landing, which is a growing trend. Design/methodology/approach An integrated guidance and control is considered for the model helicopter. A fuzzy logic is designed to adaptively choose the best control parameters for the sliding mode controller and solve the challenge of parameter tuning. A self-organizing matrix consisting of fuzzy sliding mode parameters is formed instead of a single parameter with the goal of enhancing controller tracking capability. A simple, precise and fast image recognition system based on OpenCV is used to detect the proper point for descending without getting any special data from the ship and by only using a general “H” sign. Findings The problem is simulated under intense disturbances, while the approach and landing performances are acceptable. Controller performance is compared and validated. Simulation results show the robustness, agility, stability and outperformance of the proposed controller. Originality/value The novelty of this paper is the designed procedure for using a simple image recognition system in the process of autonomous ship-landing, which does not use any special data sent from the ship. Besides, an improved nonlinear controller is designed for integrated guidance and control in this specific application.

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“…Many implementations of MPC on aerospace vehicles appear in literature [1]. Some of these include spacecraft and satellite attitude control [2][3][4], spacecraft rendezvous and docking [5], helicopters [6], and atmospheric re-entry [7,8].…”

Section: Introductionmentioning

confidence: 99%

Adaptive and Efficient Model Predictive Control for Booster Reentry

Chai

Medagoda²,

Kayacan

2020

Journal of Guidance, Control, and Dynamics

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Model Predictive Control for Helicopter Shipboard Operations in the Ship Airwakes

Cited by 32 publications

References 21 publications

Improved model reference‐based adaptive nonlinear dynamic inversion for fault‐tolerant flight control

Improved model reference‐based adaptive nonlinear dynamic inversion for fault‐tolerant flight control

A vision-aided fuzzy adaptive sliding mode controller for autonomous landing of a nonlinear model helicopter on a moving marine platform

Adaptive and Efficient Model Predictive Control for Booster Reentry

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