Real time estimation of impaired aircraft flight envelope using feedforward neural networks

Norouzi, Ramin; Kosari, Amirreza; Sabour, Mohammad Hossein

doi:10.1016/j.ast.2019.04.048

Cited by 24 publications

(8 citation statements)

References 26 publications

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“…The neuron number in hidden layers can be set an ANN algorithm developer. Therefore, neuron number selection for different ANN structures is flexible and this has been a persistent and hot topic in multi-discipline studies [31]- [33]. Bayesian network, SVM and other ML methods can also be trained and used in similar ways thus they should be categorised as surrogate algorithms.…”

Section: B Surrogate Algorithmmentioning

confidence: 99%

Filter Design and Optimization of Electromechanical Actuation Systems Using Search and Surrogate Algorithms for More-Electric Aircraft Applications

Gao

Yang

Bozhko

et al. 2020

IEEE Trans. Transp. Electrific.

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Section: B Surrogate Algorithmmentioning

confidence: 99%

Filter Design and Optimization of Electromechanical Actuation Systems Using Search and Surrogate Algorithms for More-Electric Aircraft Applications

Gao

Yang

Bozhko

et al. 2020

IEEE Trans. Transp. Electrific.

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“…In recent years, embedded systems are fast becoming a key proportion of computer science and technology in different domains, such as driverless vehicles, medical implants, weather monitoring sensors, wearable devices, and so on [1][2][3][4][5][6]. Most embedded devices are battery-powered.…”

Section: Introductionmentioning

confidence: 99%

Analysis and Design of the Battery Initial Energy Level with Task Scheduling for Energy-Harvesting Embedded Systems

Miao

Wei

2021

Complexity

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When the energy-harvesting embedded system (EHES) is running, its available energy (harvesting energy and battery storage energy) seems to be sufficient overall. However, in the process of EHES task execution, an energy shortage may occur in the busy period such that system tasks cannot be scheduled. We call this issue the energy deception (ED) of the EHES. Aiming to address the ED issue, we design an appropriate initial energy level of the battery. In this paper, we propose three algorithms to judge the feasibility of the task set and calculate the appropriate initial energy level of the battery. The holistic energy evaluation (HEE) algorithm makes a preliminary judgment of the task set feasibility according to available energy and consumption energy. A worst-case response time-based initial energy level of the battery (WCRT-IELB) algorithm and an accurate cycle-initial energy level of the battery (AC-IELB) algorithm can calculate the proper initial battery capacity. We use the YARTISS tool to simulate the above three algorithms. We conducted 250 experiments on As Late As Possible (ALAP) and As Soon As Possible (ASAP) scheduling with the maximum battery capacities of 50, 100, 200, 300, and 400. The experimental results show that setting a reasonable initial energy level of the battery can effectively improve the feasibility of the task set. Among the 250 task sets, the HEE algorithm filtered 2.8% of them as infeasible task sets. When the battery capacity is set to 400, the WCRT-BIEL algorithm increases the success rates of the ALAP and ASAP by 17.2% and 26.8%, respectively. The AC-BIEL algorithm increases the success rates of the ALAP and ASAP by 18% and 26.8%, respectively.

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“…Real-time embedded systems are widely used in high-reliability application domains to ensure reliable execution of mission-critical tasks. These domains include aerospace, unmanned aerial vehicles, automobiles, and so on [1][2][3]. With the development of computer technology, such systems are becoming more intelligent, and the demand for long time running is getting stronger.…”

Section: Introductionmentioning

confidence: 99%

A Group-Based Energy-Efficient Dual Priority Scheduling for Real-Time Embedded Systems

Liu

2020

Information

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As the limitation of energy consumption of real-time embedded systems becomes more and more strict, it has been difficult to ignore the time overhead and energy consumption of context switches for fixed-priority tasks with preemption scheduling (FPP) in multitasking environments. In addition, the scheduling for different types of tasks may disrupt each other and affect system reliability. A group-based energy-efficient dual priority scheduling (GEDP) is proposed in this paper. The GEDP isolates different types of tasks to avoid the disruption. Furthermore, it also reduces context switches effectively, thus decreasing system energy consumption. As many studies ignored the context switches’ overhead in the worst-case response time (WCRT) model, and it will affect the accuracy of WCRT, thereby affecting the system schedulability. Consequently, the WCRT model is improved based on considering context switches’ overhead. The GEDP is designed and implemented in Linux, and the time overhead and energy consumption of context switches is compared in different situations with GEDP and FPP. The experimental results show that GEDP can reduce context switches by about 1% and decrease energy consumption by about 0.6% for given tasks.

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Real time estimation of impaired aircraft flight envelope using feedforward neural networks

Cited by 24 publications

References 26 publications

Filter Design and Optimization of Electromechanical Actuation Systems Using Search and Surrogate Algorithms for More-Electric Aircraft Applications

Filter Design and Optimization of Electromechanical Actuation Systems Using Search and Surrogate Algorithms for More-Electric Aircraft Applications

Analysis and Design of the Battery Initial Energy Level with Task Scheduling for Energy-Harvesting Embedded Systems

A Group-Based Energy-Efficient Dual Priority Scheduling for Real-Time Embedded Systems

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