4 research outputs found
A review of variable-pitch propellers and their control strategies in aerospace systems
The relentless pursuit of aircraft flight efficiency has thrust
variable-pitch propeller technology into the forefront of aviation innovation.
This technology, rooted in the ancient power unit of propellers, has found
renewed significance, particularly in the realms of unmanned aerial vehicles
and urban air mobility. This underscores the profound interplay between
visionary aviation concepts and the enduring utility of propellers.
Variable-pitch propellers are poised to be pivotal in shaping the future of
human aviation, offering benefits such as extended endurance, enhanced
maneuverability, improved fuel economy, and prolonged engine life. However,
with additional capabilities come new technical challenges. The development of
an online adaptive control of variable-pitch propellers that does not depend on
an accurate dynamic model stands as a critical imperative. Therefore, a
comprehensive review and forward-looking analysis of this technology is
warranted. This paper introduces the development background of variable-pitch
aviation propeller technology, encompassing diverse pitch angle adjustment
schemes and their integration with various engine types. It places a central
focus on the latest research frontiers and emerging directions in pitch control
strategies. Lastly, it delves into the research domain of constant speed pitch
control, articulating the three main challenges confronting this technology:
inadequacies in system modeling, the intricacies of propeller-engine
compatibility, and the impact of external, time-varying factors. By shedding
light on these multifaceted aspects of variable-pitch propeller technology,
this paper serves as a resource for aviation professionals and researchers
navigating the intricate landscape of future aircraft development
Adaptive Model Predictive Control for Engine-Driven Ducted Fan Lift Systems using an Associated Linear Parameter Varying Model
Ducted fan lift systems (DFLSs) powered by two-stroke aviation piston engines
present a challenging control problem due to their complex multivariable
dynamics. Current controllers for these systems typically rely on
proportional-integral algorithms combined with data tables, which rely on
accurate models and are not adaptive to handle time-varying dynamics or system
uncertainties. This paper proposes a novel adaptive model predictive control
(AMPC) strategy with an associated linear parameter varying (LPV) model for
controlling the engine-driven DFLS. This LPV model is derived from a global
network model, which is trained off-line with data obtained from a general mean
value engine model for two-stroke aviation engines. Different network models,
including multi-layer perceptron, Elman, and radial basis function (RBF), are
evaluated and compared in this study. The results demonstrate that the RBF
model exhibits higher prediction accuracy and robustness in the DFLS
application. Based on the trained RBF model, the proposed AMPC approach
constructs an associated network that directly outputs the LPV model parameters
as an adaptive, robust, and efficient prediction model. The efficiency of the
proposed approach is demonstrated through numerical simulations of a vertical
take-off thrust preparation process for the DFLS. The simulation results
indicate that the proposed AMPC method can effectively control the DFLS thrust
with a relative error below 3.5%
Review of Water Leak Detection Methods in Smart Building Applications
In recent years, the identification of water leak detection methods has entered a wide range of fields. Pipeline failures in water distribution networks lead to the loss of a considerable amount of high-quality water. Different monitoring methods are often used to identify the failing infrastructure, which is subsequently maintained. Increased pressures on a fast-expanding water supply network needs the development of better leak detection technologies, particularly for use in smart building applications. This paper offers a detailed examination of water leak detection methods, intending to determine the state-of-the-art approaches and make recommendations for future research. It is designed to demonstrate smart buildings, but it may also be utilized in another similar context. This review concludes that, despite prior achievements, there is still much room for improvement, particularly in the domain of real-time models for earlier leak detection methods in building automation. These models should enable the integration of leakage detection, evaluation, and control system that, with minimal human interaction, may be customized for efficient leakage detection in real-world circumstances
Review of Water Leak Detection Methods in Smart Building Applications
In recent years, the identification of water leak detection methods has entered a wide range of fields. Pipeline failures in water distribution networks lead to the loss of a considerable amount of high-quality water. Different monitoring methods are often used to identify the failing infrastructure, which is subsequently maintained. Increased pressures on a fast-expanding water supply network needs the development of better leak detection technologies, particularly for use in smart building applications. This paper offers a detailed examination of water leak detection methods, intending to determine the state-of-the-art approaches and make recommendations for future research. It is designed to demonstrate smart buildings, but it may also be utilized in another similar context. This review concludes that, despite prior achievements, there is still much room for improvement, particularly in the domain of real-time models for earlier leak detection methods in building automation. These models should enable the integration of leakage detection, evaluation, and control system that, with minimal human interaction, may be customized for efficient leakage detection in real-world circumstances