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UPB Scientific Bulletin, Series C: Electrical engineering and Computer Science 2022年第1期84卷 51-62页

作者： Militaru, Gabriel Popescu, Dan Dept. of Automatic Control and Industrial Informatics University POLITEHNICA of Bucharest Romania

Unmanned systems, artificial intelligence and affordable wireless technologies represent the main drivers for the digital transformation that could have a positive impact for the rural areas development. This article presents today’s options for wireless communications technologies for UAV applications. Available solutions, advantages and limitations of implementing UAV precision farming for medium and large scale WSN were reviewed and compared for the reader's benefit. The authors proposed and simulated an optimum cost-efficient communication system architecture and presented its conclusions to validate the proposed communication system. © 2022, Politechnica University of Bucharest. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

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Constrained Predictive Current control in dq Frame for a Permanent Magnet Synchronous Machine

Constrained Predictive Current Control in dq Frame for a Per...

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Madalin Costin Corneliu Lazar Dept.of Automatic Control and Applied Informatics "Gheorghe Asachi" Technical University of Iasi Iasi Romania Dept. of Automatic Control and Electrical Engineering "Dunarea de Jos" University of Galati Galati Romania

In the paper, the design and Simulink implementation of a predictive current control structure in dq frame for a permanent magnet synchronous machine (PMSM) are presented. Starting from the multivariable model of the currents in the dq reference frame, first it is decoupled and through the rejection of the disturbance introduced by the back-EMF, two single-input single-output (SISO) systems result whose dynamics are generated by R-L circuits. For these SISO systems, the model predictive control (MPC) algorithms are designed that allow the consideration of physical limitations through constraints The performances of the current control structure with MPC algorithms are compared with those obtained with the conventional PI controllers.

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Pose-free visual servoing from 3D measurements

Pose-free visual servoing from 3D measurements

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European control Conference (ECC)

作者： Adrian Burlacu Radu L. Rosca Andrei I. Iancu Enric Cervera Dept. of Automatic Control and Applied Informatics Gheorghe Asachi Technical University of Iasi Romania Dept. of Computer Science and Engineering Jaume I University Spain

In this paper, a novel approach to visual servo control robotic systems is proposed. It is focused on developing a solution using 3D point features without recovering the rigid object’s pose. Pose-free motion is achieved using motion parameterization techniques based on dual numbers and dual vectors. Considering an imposed velocity field over the motion of the 3D point features ensemble, this work proposes a close-form solution to a visual servoing problem. The solution provides stable motion control while preserving the image features in the field of view. However, when some point features leave the field of view, their contribution to the control law is dropped without losing stability. The proposed solution is easy to tune and implement. Various scenarios are used in simulations and real experiments to show how the proposed solution overcomes classic servoing problems.

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Mixed Reality Framework for Eye-in-Hand Collaborative Robot-Human Interaction

Mixed Reality Framework for Eye-in-Hand Collaborative Robot-...

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International Conference on System Theory, control, and Computing (ICSTCC)

作者： Ionut Sopon Cristina Tincu Aura Ganciu Adrian Burlacu Dept. of Automatic Control and Applied Informatics Gheorghe Asachi Technical University of Iasi Iasi Romania

In recent years, the manufacturing sector has undergone a significant transition from a paradigm of robotic autonomy to human-robot collaboration. This approach allows operators from different domains to rapidly adapt to a new way of working and reduces redundant learning costs, while also enabling intuitive robot control. To further enhance this paradigm, integrating Mixed Reality (MR) technology has emerged as a promising approach to creating and working in a virtual workspace while having a safe environment for training. This work develops a framework, based on digital twin representation, to integrate the MR with real-life equipment and humans. This allows for the control of a collaborative robot in an environment with objects or humans perceived by the eye-in-hand visual sensor. The efficiency of the proposed framework is emphasized by a comparison of Unity simulations versus the real-time behavior of the collaborative robot.

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MELANOMA AUTOMATED DETECTION SYSTEM INTEGRATED WITH AN EHR PLATFORM

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: Electrical engineering and Computer Science 2024年第1期86卷 57-68页

作者： El-Khatib, Hassan Ștefan, Ana-Maria Popescu, Dan Dept. of Automatic Control and Industrial Informatics National University of Science and Technology POLITEHNICA Bucharest Romania Dept. of Electronics Telecommunications and Information Technology National University of Science and Technology POLITEHNICA Bucharest Romania

Early melanoma detection is vital for improved treatment outcomes and reduced mortality. This paper proposes integrating an automated melanoma detection system into the Electronic Health Record, offering benefits like seamless screening during routine medical visits, enhancing early lesion detection. The system's efficiency allows providers to focus on patient care, while real-time alerts ensure timely follow-up. Patient engagement promotes proactive skin health. Interoperability within the EHR facilitates comprehensive care, resulting in better outcomes, reduced costs, and proactive prevention. © 2024, Politechnica University of Bucharest. All rights reserved.

关键词： Automation

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From Model Predictive control to Data Driven control to Meet High Efficiency Objective of a PMSM Drive System

From Model Predictive Control to Data Driven Control to Meet...

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International Conference on Applied and Theoretical Electricity (ICATE)

作者： Madalin Costin Ion Bivol Dept. of Electrical Engineering and Energy Conversion Systems “Dunarea de Jos” University of Galati Galati Romania Dept. of Automatic Control and Applied Informatics “Gheorghe Asachi” Technical University of Iasi Iasi Romania

ISBN: (数字)9798350388107

ISBN: (纸本)9798350388114

In this paper is proposed a Data Driven control (DDC) law of a Permanent Magnet Synchronous Machine (PMSM) drive as an alternative to the Model Predictive control (MPC) strategy. The DDC method is designed for the inner control structure of the PMSM drive, the outer speed loop being employed by a classical linear PI controller. Thus, the DDC is based on build up a database of the relevant quantities as electromagnetic torque, speed, voltages and current, all obtained in steady - state regime with MPC strategy, being selected for the highest efficiency values for a given pair of speed and torque. The learning process of the DDC strategy by a mutidimesional interpolation method leads to obtain high performances in both steady - state and dynamic regimes, without any additional optimal current reference command. A comparative analysis done in Matlab simulation environment of the results obtained by both MPC and DDC control laws shows the effectiveness of the last strategies. The DDC method provide a robust optimal control under energetic constraints, being more suitable then the classical MPC law that can not offers reliable results for a large area of conditions in practice.

关键词： Permanent magnet machines Interpolation Torque Stator windings Prediction algorithms Permanent magnets Temperature control Steady-state Reliability Predictive control

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Assessing Uncertainty in Space Weather Forecasting Using Quantile Regression and Complex Nonlinear Systems Identification Techniques

Assessing Uncertainty in Space Weather Forecasting Using Qua...

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International Conference on Computing, Electronics & Communications engineering (iCCECE)

作者： Hua-Liang Wei Michael A. Balikhin Richard J. Boynton Simon N. Walker Dept. of Automatic Control and Systems Engineering The University of Sheffield Sheffield UK

Space weather forecasting is of global interest, and its importance is well established in research community and recognized by government, industries and stockholders. Over the past years, many types of predictive models have been developed in the literature. There is a general agreement that forecasting models should not only provide point prediction but also inform the uncertainty associated with the prediction. This study presents a novel method bases on quantile regression and complex dynamic modelling for measuring uncertainties in space weather forecasting. The approach is implemented using Quantile regression and Nonlinear AutoRegressive Moving Average with Exogenous inputs (NARMAX) methods (for short the approach is called Q-NARMAX). The method is applied to Disturbance storm index (Dst) observations to examine its interpretability and capability for uncertainty analysis. Results show that the proposed Q-NARX model can produce excellent predictions of the Dst index, and meanwhile provides a measure for assessing the uncertainty in the forecast. The innovative integration of quantile regression, complex dynamic modelling and nonlinear system identification techniques enables the proposed work to have following attractive advantages and properties: 1) it can produce excellent prediction accuracy for space weather forecasting, 2) it uses transparent models to approximate (represent) black-box systems, enabling to interpret the dependent relationship between space weather indices (system outputs) and their drivers (system inputs), and 3) more importantly, it allows for uncertainty assessment and analysis of models and forecasts.

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Cooperative adaptive cruise control with string stability based on DMPC for vehicle platooning

Cooperative adaptive cruise control with string stability ba...

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International Conference on System Theory, control, and Computing (ICSTCC)

作者： Ovidiu Pauca Mircea Lazar Constantin F. Caruntu Dept. of Automatic Control and Applied Informatics ”Gheorghe Asachi” Technical University of Iasi Iasi Romania Dept. of Electrical Engineering Eindhoven University of Technology Eindhoven The Netherlands

The cooperative adaptive cruise control (CACC) functionality received significant interest in the state-of-the-art due to its advantages in optimizing traffic flow. The model-based predictive control (MPC) strategy was used in various studies due to its advantages in improving the performance of the vehicles (reducing the travel costs, improving the quality of the travel by reducing sudden accelerations, and ensuring the stability of the platoons). Moreover, MPC solutions are built to maximize the advantages of vehicular communication by sharing predictions on states of vehicles (e.g., velocities, accelerations, trajectories). In addition, MPC is also used to compensate for the disturbances added by communications. Thus, this paper proposes a CACC strategy for a vehicle platoon. The solution is based on the distributed MPC (DMPC) strategy, and the controller is proposed in discrete time, ensuring predecessor-follower string stability for the whole platoon.

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Tuning the Feedback controller Gains is a Simple Way to Improve Autonomous Driving Performance

Tuning the Feedback Controller Gains is a Simple Way to Impr...

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UKACC International Conference on control (control)

作者： Wenyu Liang Pablo R. Baldivieso Ross Drummond Donghwan Shin Dept. of Automatic Control and Systems Engineering University of Sheffield Sheffield UK Dept. of Computer Science University of Sheffield Sheffield UK

ISBN: (数字)9798350374261

ISBN: (纸本)9798350374278

Typical autonomous driving systems are a combination of machine learning algorithms (often involving neural networks) and classical feedback controllers. Whilst significant progress has been made in recent years on the neural network side of these systems, only limited progress has been made on the feedback controller side. Often, the feedback control gains are simply passed from paper to paper with little re-tuning taking place, even though the changes to the neural networks can alter the vehicle's closed loop dynamics. The aim of this paper is to highlight the limitations of this approach; it is shown that re-tuning the feedback controller can be a simple way to improve autonomous driving performance. To demonstrate this, the PID gains of the longitudinal controller in the TCP autonomous vehicle algorithm are tuned. This causes the driving score in CARLA to increase from 73.21 to 77.38, with the results averaged over 16 driving scenarios. Moreover, it was observed that the performance benefits were most apparent during challenging driving scenarios, such as during rain or night time, as the tuned controller led to a more assertive driving style. These results demonstrate the value of developing both the neural network and feedback control policies of autonomous driving systems simultaneously, as this can be a simple and methodical way to improve autonomous driving system performance and robustness.

关键词： Machine learning algorithms Neural networks control systems Robustness Feedback control control theory Adaptive control

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Front-Office Management of Service Operations with Robotic Process Automation

Front-Office Management of Service Operations with Robotic P...

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International Conference on control Systems and Computer Science (CSCS)

作者： Radu-Florin Negoiţă Theodor Borangiu Doctoral School of Automatic Control and Computers University Politehnica of Bucharest Bucharest Romania Dept. of Automatic Control and Industrial Informatics University Politehnica of Bucharest Bucharest Romania

Coordinating service capacity with dynamic varying, market-driven customer demand in a service business imposes correlating and synchronizing front-office and back-office processes - the first addressing customer relationship management and the second inventory planning, forecasting demand, analytics, and strategic decision making. Front office management (FOM) contributes substantially in coordinating the services requested by guests, and needs to be integrated in an Operations Management Software system specific for hotel business. Research efforts are currently directed towards automating repetitive, time consuming operations included in front office processes that are in great number, initiated by random events and customer actions with variable timing. The paper presents a solution to automate FOM operations that are kept consistent with the business strategy of the organization, and assist front-office workflows involving customers (service requests, service quality assessment) and front line personnel (registration, check in, check out, taxation and invoicing). The solution is based on the Robotic Process Automation (RPA) technology extended with AI-based functionalities for the intelligent process automation and integration with back-office workflows.

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