2018 AIAA Guidance, Navigation, and Control Conference 2018
DOI: 10.2514/6.2018-0842
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A Sparse Neural Network Approach to Model Reference Adaptive Control with Hypersonic Flight Applications

Abstract: Neural network-based model reference adaptive control (MRAC) is an effective architecture used in the flight control community to combat significant uncertainties where the structure of the uncertainty is unknown. In our previous work, a novel adaptive control architecture called sparse neural network (SNN) was developed in order to improve long-term learning and transient performance of flight vehicles with persistent uncertainties which lie in various regions throughout the operating regime. The SNN is desig… Show more

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Cited by 17 publications
(9 citation statements)
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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%
See 1 more Smart Citation
“…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%
“…To address the model uncertainties, robust control strategies including the sliding mode control 5‐7 and H control 8 are investigated on HFVs. Moreover, adaptive laws and intelligent learning are applied in References 9‐15 to achieve online identification. In References 16‐19, the learning performance is improved by mining the internal information of the HFV dynamics.…”
Section: Introductionmentioning
confidence: 99%
“…Applications of adaptive control can be found literally everywhere. From domestic applications [11], to engineering [17] and manufacturing [8], it is highly evident that adaptive control is very useful. Indicatively, recently, identification techniqes had been used to model a system response originating from Partial Differential Equations [18] and attempting to control it in an empirical, yet adaptive way.…”
Section: Introductionmentioning
confidence: 99%