Robust Decentralized Nonlinear Control for a Twin Rotor MIMO System

Belmonte, Lidia M.; Morales, Rafael; Fernández-Caballero, Antonio; Somolinos, J.A.

doi:10.3390/s16081160

Cited by 23 publications

(15 citation statements)

References 27 publications

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“…Experimental (e.g., [73][74][75]): Two kinds of experiments were considered: offline tests with which to validate the proposed solution by using data and images recorded on a previously performed flight, and lab tests in which the proposal is tested by using a laboratory platform that simulates the dynamic behavior of a real aircraft (for instance, Twin Rotor MIMO System [76][77][78]).…”

Section: Type Of Validationmentioning

confidence: 99%

Computer Vision in Autonomous Unmanned Aerial Vehicles—A Systematic Mapping Study

2019

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Personal assistant robots provide novel technological solutions in order to monitor people’s activities, helping them in their daily lives. In this sense, unmanned aerial vehicles (UAVs) can also bring forward a present and future model of assistant robots. To develop aerial assistants, it is necessary to address the issue of autonomous navigation based on visual cues. Indeed, navigating autonomously is still a challenge in which computer vision technologies tend to play an outstanding role. Thus, the design of vision systems and algorithms for autonomous UAV navigation and flight control has become a prominent research field in the last few years. In this paper, a systematic mapping study is carried out in order to obtain a general view of this subject. The study provides an extensive analysis of papers that address computer vision as regards the following autonomous UAV vision-based tasks: (1) navigation, (2) control, (3) tracking or guidance, and (4) sense-and-avoid. The works considered in the mapping study—a total of 144 papers from an initial set of 2081—have been classified under the four categories above. Moreover, type of UAV, features of the vision systems employed and validation procedures are also analyzed. The results obtained make it possible to draw conclusions about the research focuses, which UAV platforms are mostly used in each category, which vision systems are most frequently employed, and which types of tests are usually performed to validate the proposed solutions. The results of this systematic mapping study demonstrate the scientific community’s growing interest in the development of vision-based solutions for autonomous UAVs. Moreover, they will make it possible to study the feasibility and characteristics of future UAVs taking the role of personal assistants.

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Section: Type Of Validationmentioning

confidence: 99%

Computer Vision in Autonomous Unmanned Aerial Vehicles—A Systematic Mapping Study

2019

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“…The main rotor is the most important aerodynamic part of the helicopter, while the high-speed rotating rotor makes the aircraft have unique flight behavior and maneuverability [6,7]. However, the aerodynamic design of the rotor also affects its stealth characteristics [8,9]. Using the Maxwell equations as the main control equations, a set of numerical calculation methods for the rotor radar cross-section (RCS) characteristics based on the time-domain finite volume method is established.…”

Section: Introductionmentioning

confidence: 99%

Influence of Rotor Dynamic Scattering on Helicopter Radar Cross-Section

Zhou

Huang

2020

Sensors

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With the continuous improvement and development of armed helicopters, the research on their stealth characteristics has become more and more in depth. In order to obtain the complex effect of stealth characteristics caused by the high-speed rotation of rotor-like components, a dynamic scattering method (DSM) is presented. Rotation speed, azimuth, elevation angle, pitching angle, and rolling angle are studied and discussed in detail. The results show that the electromagnetic scattering characteristics of the main rotor and tail rotor are dynamic and periodic. This period characteristic is related to the rotation speed and attitude angle of the rotor. The radar cross-section (RCS) of the helicopter varies greatly at different observation angles and attitude angles, but the dynamic electromagnetic scattering effect caused by the main rotor and tail rotor cannot be ignored. The presented DSM is effective and efficient for studying the dynamic RCS of the rotor-type parts of a helicopter or the whole machine.

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“…These coupling actions tends to overlap, resulting in different influences and effects on the temperature in different parts. The analysis results show that analyzing and predicting the temperature change of multiple parts captured by multiple sensors on a pump unit is a multivariable and nonlinear problem [6,7], which is a research hotspot and a difficult concept at present [8,9,10]. …”

Section: Introductionmentioning

confidence: 99%

Grey Model Optimized by Particle Swarm Optimization for Data Analysis and Application of Multi-Sensors

Qiu

Yang

et al. 2018

Sensors

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Data on the effective operation of new pumping station is scarce, and the unit structure is complex, as the temperature changes of different parts of the unit are coupled with multiple factors. The multivariable grey system prediction model can effectively predict the multiple parameter change of a nonlinear system model by using a small amount of data, but the value of its q parameters greatly influences the prediction accuracy of the model. Therefore, the particle swarm optimization algorithm is used to optimize the q parameters and the multi-sensor temperature data of a pumping station unit is processed. Then, the change trends of the temperature data are analyzed and predicted. Comparing the results with the unoptimized multi-variable grey model and the BP neural network prediction method trained under insufficient data conditions, it is proved that the relative error of the multi-variable grey model after optimizing the q parameters is smaller.

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Robust Decentralized Nonlinear Control for a Twin Rotor MIMO System

Cited by 23 publications

References 27 publications

Computer Vision in Autonomous Unmanned Aerial Vehicles—A Systematic Mapping Study

Computer Vision in Autonomous Unmanned Aerial Vehicles—A Systematic Mapping Study

Influence of Rotor Dynamic Scattering on Helicopter Radar Cross-Section

Grey Model Optimized by Particle Swarm Optimization for Data Analysis and Application of Multi-Sensors

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