IFAC-PapersOnLine最新文献

In this paper, we introduce a metric to evaluate the equity in mobility and a routing framework to enhance the metric within multi-modal intelligent transportation systems. The mobility equity metric (MEM) simultaneously accounts for service accessibility and transportation costs to quantify the equity and fairness in a transportation network. Finally, we develop a system planner integrated with MEM that aims to distribute travel demand for the transportation network, resulting in a socially optimal mobility system. Our framework results in a transportation network that is efficient in terms of travel time, improves accessibility, and ensures equity in transportation.

This paper examines the imperative of LGBTQ+ equity, diversity and inclusion within organizations like IFAC. It highlights IFAC’s commitment to integrating D&I principles into its activities and decision making. This paper explores the intersection of LGBTQ+ experiences with automation and control systems, emphasizing ongoing challenges faced by LGBTQ+ individuals. Methodological considerations for D&I research in LGBTQ+ communities are discussed, advocating for direct engagement and participative qualitative approaches. The paper addresses the marginalization of LGBTQ+ digital culture and the role of AI in perpetuating biases. With this in mind it underscores the need to expand D&I efforts to encompass equity, fostering a sense of belonging for all individuals within organizations and communities. Through these insights, the paper contributes to the ongoing discourse on promoting inclusivity and equity in professional and academic spheres. It also offers methodological guidelines for those conducting scholarly studies including the LGBTQ+ community in an automated world.

The paper presents a study on the women in engineering in two Eastern Partnership countries – Ukraine and Moldova. Both countries were part of the former Soviet Union and gained independence in 1991 as the Soviet Union dissolved. Their recent history is marked by some conflicts and a war. The study aims to identify the dynamics of the involvement of women in engineering from the Soviet era, when women were encouraged to study science and technology, through the de-industrialization post-Soviet period, and through the impact of conflicts and war. The paper is part of a larger study, inspired by the Diversity and Inclusion Working Group in the International Federation of Automatic Control (IFAC); the study focuses on women in science and technology, particularly engineering, in different regions and countries of the world. The authors of the study search for common elements, specificities and trends, and aim to encourage the inclusion of more women and girls in the fields of engineering and technology.

The influence of digital technologies on the Cultural Heritage sector has grown as the use of Artificial Intelligence (AI), the Internet of Things (IOT), Virtual Reality (VR) and Augmented Reality (AR) has become more dominant in society. The digitisation of Cultural Heritage content can be seen across many areas of the world such as in the European Union (EU) within projects like meSch and Emotive that were funded under the Horizon 2020 research and innovation funding programme to support personalisation and education. Machine learning techniques have also been utilised in culturally significant work across Asia and Africa in sectors such as education, healthcare, agriculture, and Cultural Heritage with the goal of improving the life and wellbeing of people in these regions. This paper aims to deduce key machine learning techniques that are applicable for smart Cultural Heritage spaces and determine their adherence with the Human-Centred philosophy in selected projects within Africa, Asia, and Europe. The techniques chosen were Collaborative Filtering and Unsupervised Learning and whilst the results indicated that human-centredness was evident there were areas which could be improved to ensure a broad adherence with this philosophical approach.

Mobile robots are revolutionizing healthcare with their potential to streamline logistics, patient care, and facility maintenance in hospitals. This paper introduces a mobile robot designed for medicine distribution in patient rooms, detailing its mechanical design and working principle. A scenario demonstrating robot path planning for medicine distribution is presented. Future research directions are outlined.

STEM education aims to prepare students for their future jobs, providing authentic tasks and problems to solve. Usually, approaches to teaching STEM subjects are based on a constructivist learning theory that accentuates active, practical, and interactive learning approaches. Nowadays, the implementation of STEM education faces several logistical and pedagogical challenges, which can impact the effectiveness of STEM education programs. The conditions for applying information technologies in STEM education in Bulgarian schools and universities are presented. The paper proposes a conceptual model of the innovative STEM educational system, which includes personalization and optimization of the applied teaching methods.

A practical surface modification method for the QTF sensors which is used as the sensing element for a digitalized measurement system, has been experimentally evaluated and demonstrated a 14% reduction of the overall deviation in the digitized resonance frequency measurement result. In recent years, digitized sensing measurement has become more popular in the research field of Quartz Tuning Fork (QTF) sensing technology due to the simplicity of its system structure compared to the conventional system. However, the inherent issue of noise interference for the highly sensitive sensing element is accompanied, raising the challenge of achieving reliable stability. The proposed method aims to effectively reduce the deviation in the measurement of highly sensitive QTF sensing elements in a digitized measurement system. The method utilising PTFE-based composition as coating material achieved an effective insulation for noise cancellation. The method can potentially be improved by adopting suitable post-treatment. Further analysis of the consistency in the repeatability was also carried out.

This work proposes a novel architecture for constructing remote laboratories, employing modular building blocks: Matlab/Simulink software for control system design and simulation, WebSocket communication technology for continuous data exchange, and a front-end application developed using the Angular framework. To facilitate WebSocket communication on the Matlab server side, the MatlabWebSocket library is implemented. Beyond the Angular framework, interactivity within the remote laboratory is further enhanced through 3D visualization of the controlled system using a Three.js based library.

These combined technologies are applied in the development of a remote laboratory for a fast, unstable, and nonlinear magnetic levitation system. The laboratory allows users to remotely set desired values and control parameters for experiments, while also providing continuous data visualization in various forms, including numerical readouts, graphs, and 3D animations. This approach demonstrates the effectiveness of the proposed architecture for building remote laboratories for complex systems.

Autotuners represent a combination of a relay feedback identification test and some control design method. In this contribution, models with up to three parameters are estimated by means of a single asymmetrical relay experiment. Then a stable low order transfer function with a time delay term is identified by a relay experiment. Autotuning principles then combine asymmetrical relay feedback tests with a control synthesis. Two algebraic control syntheses then are presented in this paper. The first one is based on the ring of proper and stable rational functions R_PS. The second one utilizes a special ring R_MS, a set of RQ-meromorphic functions. In both cases, controller parameters are derived through a general solution of a linear Diophantine equation in the appropriate ring. A final controller can be tuned by a scalar real parameter m>0. The presented philosophy covers a generalization of PID controllers and the Smith-like control structure. This contribution deals with the implementation of proposed autotuners and presents some illustrative examples.

This paper focuses on the implementation of recognition and detection algorithms for programmable logic controllers (PLCs) based on artificial intelligence (AI). AI methods based on deep neural networks (DNN) are characterized by a large number of hidden layers and neurons in hidden layers, which increases the computational complexity of computing the outputs of artificial neural networks (ANNs). Popular convolutional neural networks (CNN) are among such ResNet, AlexNet, GoogLeNet and others. A remote cloud solution is proposed in this paper to compute CNN outputs. The CNN implementation was tested on object recognition and detection applications. Training and testing of the CNN and YOLO detector was carried out in the Python environment.