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Motion planning and modeling for isothermal parallel chemical reactions

Motion planning and modeling for isothermal parallel chemica...

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International symposium on Applied computational intelligence and Informatics ( SACI)

作者： Eszter Virágh Dániel András Drexler Bálint Kiss Physiological Controls Research Center University Research and Innovation Center Óbuda University Budapest Hungary Department of Control Engineering and Information Technology Budapest University of Technology and Economics Budapest Hungary

For several chemical reactions, the intermediate states of the system has to be known. They can be given, e.g., by sampling, measurements, or motion planning. By motion planning, we can determine the time function of the concentrations and the temperature, using the mathematical model of the system. From this, we can conclude the state of the system at every moment. We provide a motion planning method for isothermal parallel structural chemical reactions. We simulate the behavior of the three-step parallel reaction. The results of the motion planning can help to decide, if it is necessary to intervene from outside, thus we can ensure that the concentration is in a specified interval.

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Exploring Fuzzy Signatures in Sensor Fusion: A Comparative Study with the Complementary Filter

Exploring Fuzzy Signatures in Sensor Fusion: A Comparative S...

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International symposium on computational intelligence and Informatics

作者： Ahmet Mehmet Karadeniz Áron Ballagi László T. Kóczy Doctoral School of Multidisciplinary Engineering Sciences Széchenyi István University Györ Hungary Department of Automation and Mechatronics Széchenyi István University Györ Hungary Department of Information Technology Széchenyi István University Györ Hungary

ISBN: (数字)9798350353433

ISBN: (纸本)9798350353440

Sensing has become a pivotal element in the development of autonomous systems with the advancement of the technology. These systems operate on a sense-think-act cycle to execute tasks, necessitating the integration of multiple sensors. The challenge of synthesizing meaningful information from diverse data sources escalates with the complexity of the data. This study tackles the issue of sensor data complexity by investigating the potential of Fuzzy Signatures, which are promising in handling complex data due to their hierarchical structures. The main goal is to present a concept for sensor fusion based on Fuzzy Signatures, which may facilitate their use in autonomous system tasks. To demonstrate this concept, accelerometer and gyroscope data are utilized, with results compared to those from a Complementary Filter providing insight into the sensor fusion capabilities of Fuzzy Signatures. The study also underscores the importance of aggregation operators in Fuzzy Signatures, focusing on the Max and WRAO (weighted relevance aggregation operator) aggregation operators. The potential to employ various aggregation operators or to develop new ones for specific applications is highlighted. The findings indicate that Fuzzy Signatures could be an effective solution for sensor fusion challenges, offering prospects for enhancement and broader application in autonomous systems.

关键词： Autonomous systems Soft sensors Focusing Sensor fusion Sensor systems Complexity theory Gyroscopes Informatics Intelligent sensors computational intelligence

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Crowding and Mutation Improvements in an EA for Flight control Correction in a Flapping-Wing Vehicle

Crowding and Mutation Improvements in an EA for Flight Contr...

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ieee symposium Series on computational intelligence (SSCI)

作者： John C. Gallagher Michael W. Oppenheimer Eric T. Matson Electrical and Computer Enginnering University of Cincinnati Cincinnati OH USA Autonomous Control Branch Wright-Patterson Air Force Base Dayton OH USA Computer and Information Technology Purdue University West Lafayette IN

Small Flapping-Wing Micro Air Vehicles (FW-MA Vs) may be subjected to either or both of manufacturing defects or in-service damage that render their pre-designed controllers less than adequately effective. Even minor damage to wings, for example, can remove the vehicle's ability to reliably follow waypoint trails even if that same damage does not result in a catastrophic loss of altitude. One solution to this problem is to adapt the core wing motion scripts (wing gaits) in an attempt to use wing motion to compensate for losses of force and torque generation due to in-service damage or manufacturing faults. This approach presents a number of challenges - especially if it is to be deployed in a resource restricted vehicle in an online mode during an actual mission. Prior to this paper, we had presented only anecdotal treatment of fully unrestricted, 3D flight. In this paper, we will definitively establish the utility of EA adaptation of flight control in unrestricted flight in a pendulum-stable FW-MA V. We will, additionally, introduce mutation and crowding modifications that provide demonstrable utility in a manner amenable to implementation on a resource-restricted micro vehicle. The paper will conclude with a discussion of open-issues and the potential application of the reported methods to other problems.

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Co-Design Optimisation of Morphing Topology and control of Winged Drones

Co-Design Optimisation of Morphing Topology and Control of W...

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ieee International Conference on Robotics and automation (ICRA)

作者： Fabio Bergonti Gabriele Nava Valentin Wüest Antonello Paolino Giuseppe L’Erario Daniele Pucci Dario Floreano Artificial and Mechanical Intelligence Laboratory Istituto Italiano di Tecnologia (IIT) School of Computer Science University of Manchester Laboratory of Intelligent Systems Ecole Polytechnique Federale de Lausanne (EPFL) Department of Industrial Engineering University of Naples Federico II

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

The design and control of winged aircraft and drones is an iterative process aimed at identifying a compromise of mission-specific costs and constraints. When agility is required, shape-shifting (morphing) drones represent an efficient solution. However, morphing drones require the addition of actuated joints that increase the topology and control coupling, making the design process more complex. We propose a co-design optimisation method that assists the engineers by proposing a morphing drone’s conceptual design that includes topology, actuation, morphing strategy, and controller parameters. The method consists of applying multi-objective constraint-based optimisation to a multi-body winged drone with trajectory optimisation to solve the motion intelligence problem under diverse flight mission requirements, such as energy consumption and mission completion time. We show that co-designed morphing drones outperform fixed-winged drones in terms of energy efficiency and mission time, suggesting that the proposed co-design method could be a useful addition to the aircraft engineering toolbox.

关键词： Energy consumption Costs computational modeling Process control Energy efficiency Topology Trajectory

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On the Simulation of Lower Order control Strategies for Higher Order Systems

On the Simulation of Lower Order Control Strategies for High...

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International symposium on computational intelligence and Informatics

作者： Awudu Atinga János F. Bitó József K. Tar Doctoral School of Applied Informatics and Applied Mathematics Óbuda University Budapest Hungary ABC iRob John von Neumann Faculty of Informatics Óbuda University Budapest Hungary Doctoral School of Applied Informatics and Applied Mathematics ABC iRob John von Neumann Faculty of Informatics Óbuda University Budapest Hungary

ISBN: (纸本)9798350398830

In model-based control of dynamical systems the order of the necessary controller is that of the time-derivative of the generalized coordinate of the system that immediately can be set by the controller. It is determined by the “physics” of the system to be controlled. In finite time-resolution approach the digital controllers model the derivatives by finite differences, and the simplest numerical integration via Euler’s method also uses such differences. Whenever some fractional order derivative of the tracking error is fed back, this long memory term allows the realization of such control strategies for various integer order systems by appropriately masking” and weighting certain elements of longer sequences. On this mathematical basis the idea of controlling a higher order system by the application of a lower order strategy can be formulated, too. The main benefit may be achieving monotonic decrease in the components of the tracking error. In this paper the first order control of a popular second order system often used for benchmark applications, the van der Pol oscillator is considered. The realization of a simple proportional feedback first order controller in two variants, and a PID-type Computed Torque control are considered in the fixed point iteration-based adaptive framework to tackle the problems caused by modeling imprecisions. The applicability and the limits of the investigated approaches are concluded.

关键词： Adaptation models computational modeling Torque control Kinematics Transforms Benchmark testing control systems

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FROST: Fusion and Multimodal 3D Reconstruction of Icy Surfaces for Robotic Exploration

FROST: Fusion and Multimodal 3D Reconstruction of Icy Surfac...

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computational intelligence on Engineering/Cyber Physical Systems Companion (CIES Companion), ieee symposium on

作者： Huy Xuan Pham Erdal Kayacan Department of Electrical and Computer Engineering Artificial Intelligence in Robotics Laboratory (Air Lab) Aarhus University Aarhus C Denmark Automatic Control Group (RAT) Paderborn University Paderborn Germany

ISBN: (数字)9798331508494

ISBN: (纸本)9798331508500

Three-dimensional (3D) reconstruction serves as a cornerstone in various robotic applications, playing critical roles in scene understanding and navigation. Traditionally, LiDAR has been instrumental in generating precise point clouds of the environment, providing essential data for these applications. However, the efficacy of LiDAR sensors is significantly hindered in challenging conditions, such as the presence of water or icy surfaces. The complex interplay between laser beams and icy or non-ideal surfaces can result in signal degradation, distortion, or even complete signal loss, adversely affecting the accuracy and reliability of the 3D reconstruction process. The reflective and refractive properties of ice, along with its variable surface conditions, present challenges that traditional LiDAR sensors struggle to address. This paper proposes a diverse dataset to facilitate a multimodal approach for reconstructing icy surfaces using various sensors. A preliminary study based on this dataset demonstrates the feasibility of combining the geometric surface obtained from consecutive LiDAR scans with reconstructed meshes from visual cameras. The integration of distinct data sources has the potential to improve the robustness of reconstruction algorithms in diverse scenarios. The dataset can be downloaded at https://***/records/13862009.

关键词： Point cloud compression Surface reconstruction Laser radar Three-dimensional displays Navigation Ice Robustness Laser beams Image reconstruction Surface treatment

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Soft Robot Optimal control Via Reduced Order Finite Element Models

Soft Robot Optimal Control Via Reduced Order Finite Element ...

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ieee International Conference on Robotics and automation (ICRA)

作者： Tonkens, Sander Lorenzett, Joseph Pavone, Marco Stanford Univ Dept Mech Engn Stanford CA 94305 USA Stanford Univ Dept Aeronaut & Astronaut Stanford CA 94305 USA

ISBN: (纸本)9781728190778

Finite element methods have been successfully used to develop physics-basixl models of soft robots that capture the nonlinear dynamic behavior induced by continuous deformation. These high-fidelity models are therefore ideal for designing controllers for complex dynamic tasks such as trajectory optimization and trajectory tracking. However, finite element models are also typically very high-dimensional, which makes real-time control challenging. In this work we propose an approach for finite element model-based control of soft robots that leverages model order reduction techniques to significantly increase computational efficiency. In particular, a constrained optimal control problem is formulated based on a nonlinear reduced order finite element model and is solved via sequential convex programming. This approach is demonstrated through simulation of a cable-driven soft robot for a constrained trajectory tracking task, where a 9768-dimensional finite element model is used for controller design.

关键词： Trajectory tracking computational modeling Optimal control Soft robotics Stability analysis Finite element analysis computational efficiency

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High Abstraction in Engineering Communication 20

High Abstraction in Engineering Communication

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20th ieee Jubilee World symposium on Applied Machine intelligence and Informatics, SAMI 2022

作者： Horvath, Laszlo Óbuda University Institute of Applied Mathematics and Doctoral School of Applied Informatics and Applied Mathematics Budapest Hungary

ISBN: (纸本)9781665497046

Engineering essentially changed during the past two decades. The main cause of this is changing for systems organized and situation driven autonomous operation of engineering achievements. This change in engineering essentially changed the related communication. The formerly documentation and passive model based communication between engineers are changed for communication with contextual Autonomous Model System (AMS). Specific informatics, mathematics, and systemics are in the center of AMS. AMS is capable of autonomous communication with any participant of an engineering process including authorized human, model, and physical device in its contextually connected environment. In this way, sources of knowledge, former experience, law, and standard can be integrated with AMS. New approach to communication and appropriate modeling methodology are demanded. As a new contribution, this paper introduces a communication model called as Context Mediated Communication (CMC). CMC communication can work autonomously, except for direct human interaction and other participants which have not permission for this. CMC checks correctness and appropriateness of any new context in the context of existing approved contexts. CMC is situation driven so that cooperative situation awareness of involved systems and humans is essential in its autonomous processes. Following this, the Experimental Research Support Model (ERSM) concept is introduced. ERSM is a special purposed AMS which is configured for CMC intensive research project. Finally, implementation of the above results at research project is outlined considering suitable engineering platform together with its contextual connections among others with cyber-physical-biological (CPB) structures. © 2022 ieee.

关键词： computational modeling Documentation Mathematical models Informatics Standards Machine intelligence Context modeling

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Secure Storage and Access control for Personal and EEG Data using Blockchain

Secure Storage and Access Control for Personal and EEG Data ...

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International symposium on computational intelligence and Informatics

作者： Gyula Ádám Nemes Bence Tureczki Katalin Szenes György Eigner Physiological Controls Research Center Óbuda University Biomatics and Applied Artificial Intelligence Institute John von Neumann Faculty of Informatics Óbuda University Doctoral School of Applied Informatics and Applied Mathematics John von Neumann Faculty of Informatics Óbuda University Bećsi road 96/B Budapest Hungary Institute for Cyber-Physical Systems John von Neumann Faculty of Informatics Óbuda University Bećsi road 96/B Budapest Hungary

This paper introduces a blockchain-based solution for secure and efficient management of personal and EEG data for research subjects. Our approach separates but interlinks the data to ensure privacy and integrity, with role-based access controls implemented via a Solidity smart contract on the Ethereum blockchain. We integrate the principles of operational excellence to enhance traditional information security methodologies, focusing on a more comprehensive understanding and functionality of data management. Our method offers a secure, efficient, and user-friendly data management system, drawing stakeholders closer to essential professional practices and upholding the values of privacy and integrity.

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Intelligent control algorithms for industrial automation systems

Intelligent control algorithms for industrial automation sys...

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ieee Students' Conference on Electrical, Electronics and Computer Science (SCEECS)

作者： Sarathkumar D Anil. A. R J Sivadasan T. Jayakumar Murugesan Manivel Anandhakumar C Department of Electrical and Electronics Engineering Kongu Engineering College Tamil Nadu India Department of Computer Science &Engineering Sree Buddha College of Engineering Pattoor Alappuzha Kerala India Department of Electronics and Communication Engineering PSR Engineering College Sivakasi Tamil Nadu India Department of Electrical and Electronics Engineering Nandha Engineering College Tamil Nadu India Department of Electrical and Electronics Engineering Karpagam Institute of Technology Coimbatore Tamilnadu India Department of Electrical and Electronic Engineering Sri Ramakrishna Institute of Technology Coimbatore Tamil Nadu India

ISBN: (数字)9798331529833

ISBN: (纸本)9798331529840

Industrial automation has become a cornerstone of modern manufacturing, enhancing efficiency, reliability, and scalability. The integration of intelligent control algorithms, such as fuzzy logic, neural networks, genetic algorithms, and model predictive control, has revolutionized traditional automation systems, enabling more adaptive, efficient, and robust operations. This paper explores the application and impact of these intelligent control techniques in industrial settings. It highlights how machine learning algorithms can predict equipment failures, optimize processes, and enhance decision-making in real-time. Case studies are presented to illustrate the benefits and challenges of deploying these algorithms across various automated systems, such as robotic assembly lines, process control in chemical plants, and smart warehousing. Furthermore, the paper discusses the integration of these algorithms with industrial IoT (IIoT) platforms, facilitating seamless communication and data exchange between machines and control systems. The research also addresses the challenges of implementing intelligent control, such as computational complexity, security concerns, and the need for real-time processing. Finally, this study evaluates future trends, emphasizing the potential of combining artificial intelligence and deep learning techniques with industrial automation for a more adaptive and autonomous manufacturing ecosystem.

关键词： Fuzzy logic automation Machine learning algorithms Neural networks Prediction algorithms Real-time systems Optimization Intelligent control Industrial Internet of Things Predictive control

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