scholarly journals Research of Parallel Computing Neuro-fuzzy Networks for Unmanned Vehicles

2021 ◽  
Author(s):  
Donato Repole

The Doctoral Thesis illustrates the author’s research in the field of VHDL based ‘neuro-fuzzy controllers’. The Thesis examines a novel software tool for the high-level ‘neuro-fuzzy controller’ description capable of executing controller simulations, optimisation tasks, performing learning / training tasks, and exporting the controller in VHDL code. The author introduces a design strategy that is looking for developing solutions for complex controller architecture of mobile robotic vehicles (of any nature) or even for multiple industrial application. This work enables further investigative research into autonomous robotics, particularly into the physical implementation of an autonomous aerial unmanned vehicle from an inexpensive RC plane.

MACRo 2015 ◽  
2015 ◽  
Vol 1 (1) ◽  
pp. 183-191 ◽  
Author(s):  
Tibor Tămas ◽  
Sándor Tihamér Brassai

AbstractThe purpose of this work is to present the design flow and the implementation of a neuro-fuzzy controller Intellectual Property (IP) core, using High Level Synthesis (HLS) tool. The realized IP core is designed for FPGA based embedded system architectures. The implemented control algorithm is a Sugeno model based Adaptive Neuro-Fuzzy Inference System (ANFIS). The optimization possibilities using the HLS tool and the designing of the interfaces for the IP core are presented.


2010 ◽  
Vol 4 (1) ◽  
pp. 8-15
Author(s):  
Azeddine Chaiba ◽  
◽  
Rachid Abdessemed ◽  
M. Lokmen Bendaas ◽  
◽  
...  

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2617
Author(s):  
Catalin Dumitrescu ◽  
Petrica Ciotirnae ◽  
Constantin Vizitiu

When considering the concept of distributed intelligent control, three types of components can be defined: (i) fuzzy sensors which provide a representation of measurements as fuzzy subsets, (ii) fuzzy actuators which can operate in the real world based on the fuzzy subsets they receive, and, (iii) the fuzzy components of the inference. As a result, these elements generate new fuzzy subsets from the fuzzy elements that were previously used. The purpose of this article is to define the elements of an interoperable technology Fuzzy Applied Cell Control-soft computing language for the development of fuzzy components with distributed intelligence implemented on the DSP target. The cells in the network are configured using the operations of symbolic fusion, symbolic inference and fuzzy–real symbolic transformation, which are based on the concepts of fuzzy meaning and fuzzy description. The two applications presented in the article, Agent-based modeling and fuzzy logic for simulating pedestrian crowds in panic decision-making situations and Fuzzy controller for mobile robot, are both timely. The increasing occurrence of panic moments during mass events prompted the investigation of the impact of panic on crowd dynamics and the simulation of pedestrian flows in panic situations. Based on the research presented in the article, we propose a Fuzzy controller-based system for determining pedestrian flows and calculating the shortest evacuation distance in panic situations. Fuzzy logic, one of the representation techniques in artificial intelligence, is a well-known method in soft computing that allows the treatment of strong constraints caused by the inaccuracy of the data obtained from the robot’s sensors. Based on this motivation, the second application proposed in the article creates an intelligent control technique based on Fuzzy Logic Control (FLC), a feature of intelligent control systems that can be used as an alternative to traditional control techniques for mobile robots. This method allows you to simulate the experience of a human expert. The benefits of using a network of fuzzy components are not limited to those provided distributed systems. Fuzzy cells are simple to configure while also providing high-level functions such as mergers and decision-making processes.


Author(s):  
Kiona Hagen Niehaus ◽  
Rebecca Fiebrink

This paper describes the process of developing a software tool for digital artistic exploration of 3D human figures. Previously available software for modeling mesh-based 3D human figures restricts user output based on normative assumptions about the form that a body might take, particularly in terms of gender, race, and disability status, which are reinforced by ubiquitous use of range-limited sliders mapped to singular high-level design parameters. CreatorCustom, the software prototype created during this research, is designed to foreground an exploratory approach to modeling 3D human bodies, treating the digital body as a sculptural landscape rather than a presupposed form for rote technical representation. Building on prior research into serendipity in Human-Computer Interaction and 3D modeling systems for users at various levels of proficiency, among other areas, this research comprises two qualitative studies and investigation of the impact on the first author's artistic practice. Study 1 uses interviews and practice sessions to explore the practices of six queer artists working with the body and the language, materials, and actions they use in their practice; these then informed the design of the software tool. Study 2 investigates the usability, creativity support, and bodily implications of the software when used by thirteen artists in a workshop. These studies reveal the importance of exploration and unexpectedness in artistic practice, and a desire for experimental digital approaches to the human form.


Actuators ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 51
Author(s):  
Jozef Živčák ◽  
Michal Kelemen ◽  
Ivan Virgala ◽  
Peter Marcinko ◽  
Peter Tuleja ◽  
...  

COVID-19 was first identified in December 2019 in Wuhan, China. It mainly affects the respiratory system and can lead to the death of the patient. The motivation for this study was the current pandemic situation and general deficiency of emergency mechanical ventilators. The paper presents the development of a mechanical ventilator and its control algorithm. The main feature of the developed mechanical ventilator is AmbuBag compressed by a pneumatic actuator. The control algorithm is based on an adaptive neuro-fuzzy inference system (ANFIS), which integrates both neural networks and fuzzy logic principles. Mechanical design and hardware design are presented in the paper. Subsequently, there is a description of the process of data collecting and training of the fuzzy controller. The paper also presents a simulation model for verification of the designed control approach. The experimental results provide the verification of the designed control system. The novelty of the paper is, on the one hand, an implementation of the ANFIS controller for AmbuBag pressure control, with a description of training process. On other hand, the paper presents a novel design of a mechanical ventilator, with a detailed description of the hardware and control system. The last contribution of the paper lies in the mathematical and experimental description of AmbuBag for ventilation purposes.


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