Hasil untuk "Control engineering systems. Automatic machinery (General)"

Li Yating, Muhammad Afzaal, Xiao Shanshan et al.

In large language models (LLMs), the translation quality has limitations in the translation when translated into different languages. This study compares Chinese allusions in human and machine translated corpora translated by OpenAI GPT-3.5, Volctrans, and human translated texts. The framework innovatively combines two automated evaluation metrics, BLEU and METEOR, with a translation quality assessment method derived from Fuzzy Mathematics and Optimality Theory. The findings of the study indicate that the GPT-3.5 translated version exhibits higher quality than the Volctrans version when evaluated by a machine. Similarly, human evaluations indicate that among the three versions, Volctrans is of the lowest quality, while the human version exceeds the GPT-3.5 version in terms of quality. Thus, the study further reveals that Volctrans version is deemed to have the lowest translation quality from both human and machine evaluation perspectives. Finally, this study not only introduces but also validates a novel framework for assessing machine translation quality.

Arslan Ahmed Amin, Ansa Mubarak, Habib Ulla Manzoor

This review paper provides a comprehensive review of Intelligent Vehicular and Sensor Communication Networks (IVSCN), focusing on the design details and recent advancements required to develop modern vehicular systems. It highlights the comprehensive sensor technologies such as Radar, Light Detection and Ranging (LiDAR), Cameras, and Ultrasonic sensors that aim to collect and synchronize data for vehicle operation and safety. The paper also critically assesses sophisticated network designs and architectures that strengthen vehicular communications. Further in-depth analysis is provided about vehicular network communication protocols and navigation systems, which can manage a multitude of traffic scenarios, including signal control, accidents, and congestion, which are invaluable for optimizing vehicle movement and ensuring road safety. Moreover, the review further covers practical applications and cases, demonstrating that these technologies have worked well, from providing sound traffic management systems to improving vehicle safety and environmental sustainability. The review also explores other Artificial Intelligence (AI) techniques used in fault-tolerant and intelligent communication methods, such as Kalman Filters, Particle Filters, and Fuzzy Logic Fusion. This literature review highlights the role of ongoing innovation in routing protocols, navigation systems, and data analytics; it thus has practical implications for both upcoming and well-known researchers.

Eugene T. Hamzezadeh, Andrew J. Petruska

This work highlights the duality between state estimation methods and model predictive control. A predictive controller, observed control, is presented that uses this duality to efficiently compute control actions with linear time-horizon length scalability. The proposed algorithms provide exceptional computational efficiency, adaptive time horizon lengths, and early optimization termination criteria. The use of Kalman smoothers as the backend optimization framework provides for a straightforward implementation supported by strong theoretical guarantees. Additionally, a formulation is presented that separates linear model predictive control into purely reactive and anticipatory components, enabling any-time any-horizon observed control while ensuring controller stability for short time horizons. Finally, numerical case studies confirm that nonlinear filter extensions, i.e., the extended Kalman filter and unscented Kalman filter, effectively extend observed control to nonlinear systems and objectives.

Audrey Blizard, Stephanie Stockar

This paper presents a novel partitioning method designed to minimize control performance degradation resulting from partitioning a system for distributed control while maintaining the computational benefits of these methods. A game-theoretic performance metric, the modified Price of Anarchy, is introduced and is used in a generalizable partitioning metric to quantify optimality losses in a distributed controller. By finding the partition that minimizes the partitioning metric, the best-performing distributed control design is chosen. The presented partitioning metric is control-design agnostic, making it broadly applicable to many control design problems. In this paper, the developed metric is used to minimize the performance losses in the distributed control of a demand-flexible District Heating Network. The final distributed controller is provably feasible and stable. In simulation, this novel partitioning performed similarly to the centralized controller, increasing overall heat losses by only 1.9%, as compared to a similarly-sized baseline partition, which resulted in a 22% increase in losses.

Zhenpeng Chen, Chong Wang, Weisong Sun et al.

Large Language Models (LLMs) are increasingly integrated into software applications, giving rise to a broad class of prompt-enabled systems, in which prompts serve as the primary 'programming' interface for guiding system behavior. Building on this trend, a new software paradigm, promptware, has emerged, which treats natural language prompts as first-class software artifacts for interacting with LLMs. Unlike traditional software, which relies on formal programming languages and deterministic runtime environments, promptware is based on ambiguous, unstructured, and context-dependent natural language and operates on LLMs as runtime environments, which are probabilistic and non-deterministic. These fundamental differences introduce unique challenges in prompt development. In practice, prompt development remains largely ad hoc and relies heavily on time-consuming trial-and-error, a challenge we term the promptware crisis. To address this, we propose promptware engineering, a new methodology that adapts established Software Engineering (SE) principles to prompt development. Drawing on decades of success in traditional SE, we envision a systematic framework encompassing prompt requirements engineering, design, implementation, testing, debugging, evolution, deployment, and monitoring. Our framework re-contextualizes emerging prompt-related challenges within the SE lifecycle, providing principled guidance beyond ad-hoc practices. Without the SE discipline, prompt development is likely to remain mired in trial-and-error. This paper outlines a comprehensive roadmap for promptware engineering, identifying key research directions and offering actionable insights to advance the development of prompt-enabled systems.

Thomas I. Strasser, Filip Pröstl Andrén

A driving force for the realization of a sustainable energy supply is the integration of renewable energy resources. Due to their stochastic generation behaviour, energy utilities are confronted with a more complex operation of the underlying power grids. Additionally, due to technology developments, controllable loads, integration with other energy sources, changing regulatory rules, and the market liberalization, the systems operation needs adaptation. Proper operational concepts and intelligent automation provide the basis to turn the existing power system into an intelligent entity, a cyber-physical energy system. The electric energy system is therefore moving from a single system to a system of systems. While reaping the benefits with new intelligent behaviors, it is expected that system-level developments, architectural concepts, advanced automation and control as well as the validation and testing will play a significantly larger role in realizing future solutions and technologies. The implementation and deployment of these complex systems of systems are associated with increasing engineering complexity resulting also in increased engineering costs. Proper engineering and validation approaches, concepts, and tools are partly missing until now. Therefore, this paper discusses and summarizes the main needs and requirements as well as the status quo in research and development related to the engineering and validation of cyber-physical energy systems. Also research trends and necessary future activities are outlined.

Ervan Kassarian, Francesco Sanfedino, Daniel Alazard et al.

Conventional robust H2/H-infinity control minimizes the worst-case performance, often leading to a conservative design driven by very rare parametric configurations. To reduce this conservatism while taking advantage of the stochastic properties of Monte Carlo sampling and its compatibility with parallel computing, we introduce an alternative paradigm that optimizes the controller with respect to a stochastic criterion, namely the conditional value at risk. We present the problem formulation and discuss several open challenges toward a general synthesis framework. The potential of this approach is illustrated on a mechanical system, where it significantly improves overall performance by tolerating some degradation in very rare worst-case scenarios.

Mohamed Salim Bidou, Laetitia Perez, Sylvain Verron et al.

Abstract This research focuses on the identification of failure times in thermal systems governed by partial differential equations, a task known for its complexity. A new model‐based diagnostic approach is presented that aims to accurately identify failing heat sources and accurately determine their failure times, which is crucial when multiple heat sources fail and there is a delay in detection by distant sensors. To validate the effectiveness of the approach, a comparative analysis is carried out with an established method based on a Bayesian filter, the Kalman filter. The aim is to provide a comprehensive analysis, highlighting the advantages and potential limitations of the methodology. In addition, a Monte Carlo simulation is implemented to assess the impact of sensor measurements on the performance of this new approach.

Chang Yu, Bing Zhu, Jianying Zheng et al.

Abstract In this paper, an optimal distributed guidance law is proposed for cooperatively intercepting a manoeuvering target in three dimensional (3D) framework. Based on the 3D kinematic model of interceptors and the target, the kinematic engagement equations in line‐of‐sight (LOS) coordinate can be obtained. Along the LOS direction, a finite‐time consensus based on directed communication topology is applied to guarantee arrival‐time coordination of multiple interceptors, and sliding mode control is adopted to compensate target manoeuver. In the plane perpendicular to LOS, optimal control is used to design guidance law such that closed‐loop LOS angular rates converge to a tunable small neighbourhood of zero. The proposed cooperative guidance law is proved in theory, and its effectiveness is verified by simulations.

SONG Laijun, WANG Huifang, NI Minmin et al.

In response to the problems of current electromagnetic compatibility testing methods for elevator control cabinets, including low intelligence, cumbersome operation, and lack of elevator system status monitoring, this paper proposes an electromagnetic compatibility testing method for elevator control cabinets and designs a set of electromagnetic compatibility testing and control system for elevator control cabinets. The author constructed an "upper computer+ lower computer" control system architecture, developed an embedded controller based on ARM, designed application software for upper and lower computers of the automatic testing process and control system, implemented such functions as sensor signal acquisition and CAN bus communication for elevator control cabinets, and realized the real-time monitoring of electromagnetic compatibility testing of elevator control cabinets and elevator system status. Then, the author used this system to carry out the conducted immunity, voltage dip, voltage interruption, electrical fast transient pulse group and surge tests on elevator control cabinets, and conducted simulation tests on elevator control cabinets for sensor signal abnormalities, power supply failures, and communication anomalies. The results show that the electromagnetic compatibility testing and control system of the elevator control cabinet operates stably, with accurate data collection and simple operation, accurately and efficiently identifies various types of faults, meets the needs of elevator manufacturers and testing institutions for electromagnetic compatibility testing, and compared with previous testing methods, reduces testing manpower input by about 67%.

Eloy Serrano-Seco, Eduardo Moya-Lasheras, Edgar Ramirez-Laboreo

Electromechanical switching devices such as relays, solenoid valves, and contactors offer several technical and economic advantages that make them widely used in industry. However, uncontrolled operations result in undesirable impact-related phenomena at the end of the stroke. As a solution, different soft-landing controls have been proposed. Among them, feedforward control with iterative techniques that adapt its parameters is a solution when real-time feedback is not available. However, these techniques typically require a large number of operations to converge or are computationally intensive, which limits a real implementation. In this paper, we present a new algorithm for the iterative adaptation that is able to eventually adapt the search coordinate system and to reduce the search dimensional size in order to accelerate convergence. Moreover, it automatically toggles between a derivative-free and a gradient-based method to balance exploration and exploitation. To demonstrate the high potential of the proposal, each novel part of the algorithm is compared with a state-of-the-art approach via simulation.

Andrea Iannelli, Romain Postoyan

We consider the data-driven stabilization of discrete-time linear time-varying systems. The controller is defined as a linear state-feedback law whose gain is adapted to the plant changes through a data-based event-triggering rule. To do so, we monitor the evolution of a data-based Lyapunov function along the solution. When this Lyapunov function does not satisfy a designed desirable condition, an episode is triggered to update the controller gain and the corresponding Lyapunov function using the last collected data. The resulting closed-loop dynamics hence exhibits both physical jumps, due to the system dynamics, and episodic jumps, which naturally leads to a hybrid discrete-time system. We leverage the inherent robustness of the controller and provide general conditions under which various stability notions can be established for the system. Two notable cases where these conditions are satisfied are treated, and numerical results illustrating the relevance of the approach are discussed.

Davide Tebaldi, Roberto Zanasi

Electrical power conversions are common in a large variety of engineering applications. With reference to AC/DC and DC/AC power conversions, a strong research interest resides in multilevel converters, thanks to the many advantages they provide over standard two-level converters. In this paper, we first provide a power-oriented model of Modular Multilevel Converters (MMCs), followed by a detailed harmonic analysis. The model is given in the form of a block scheme that can be directly implemented in the Matlab/Simulink environment. The performed harmonic analysis gives a deep and exact understanding of the different terms affecting the evolution of the voltage trajectories in the upper and lower arms of the converter. Next, we propose a new model-based adaptive control scheme for MMCs. The proposed control allows to determine the optimal average capacitor voltages reference in real-time, thus allowing to properly track the desired load current while minimizing the harmonic content in the generated load current itself.

HAO Hongwei, LI Zixian, HUANG Di et al.

The application of FPGA is becoming wider because of its advantages of reconfigurability, high performance, low power consumption, and strong real-time performance. However, its shortcomings such as high development threshold, low efficiency, and long development cycle become more prominent as the increase of system size and complexity. This paper uses model-based development methods to study the correlation algorithm of FPGA, including Simulink model building, test validation, code generation and simulation. The results of comparison with traditional manual coding show that the FPGA software development cycle using model-based design methods is only one fifth of the original method and the error in calculation results of the correlation coefficient is also under 0.3%. Although the length of generated code far exceeds that of handwritten code, the resource utilization of logic units, register, storage units, and multiplier units, etc. at runtime are less than those of handwritten code after code synthesis. It can be seen that model-based development methods not only meet the accuracy requirements (not exceeding ±5‰), but also greatly shorten the development cycle and lower the coding threshold.

XIE Zeen

In view that the conventional harmonic detection algorithms cannot support analysis on nonlinear and non-stationary harmonics in the traction power supply systems, this paper proposes a harmonic detection algorithm based on the improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) and Teager energy operator (TEO). The first step is to process the signal to be detected into a set of intrinsic mode function (IMF) components through ICEEMDAN, and then obtain the true IMF components by filtering out the false ones. Then, performing TEO demodulation on each IMF component can generate the variation charts of amplitude and frequency of harmonic components over time. It is revealed through analysis that ICEEMDAN, as an improved algorithm for empirical mode decomposition (EMD), an important step in the Hilbert-Huang transform (HHT), has the best effect in suppressing mode aliasing, compared with other improved algorithms of EMD. Thanks to its good adaptability, it also has good performance in processing nonlinear and non-stationary signals. On the other hand, TEO can accurately detect the instantaneous amplitude and frequency of harmonics, and quickly respond to signal changes. The proposed algorithm was simulated and analyzed by constructing harmonic signals of the traction network characteristics. The results show that the average detection errors of amplitude and frequency were 3.56% and 1.74% respectively when analyzing steady-state current harmonics, and 3.39% and 2.44% respectively when analyzing transient current harmonics. This indicates that the algorithm proposed in this paper can accurately detect the amplitude and frequency of harmonics in the traction power supply systems, and can accurately locate harmonic signal singularity.

Masako Kishida

This paper proposes control approaches for discrete-time linear systems subject to stochastic disturbances. It employs Kalman filter to estimate the mean and covariance of the state propagation, and the worst-case conditional value-at-risk (CVaR) to quantify the tail risk using the estimated mean and covariance. The quantified risk is then integrated into a control barrier function (CBF) to derive constraints for controller synthesis, addressing tail risks near safe set boundaries. Two optimization-based control methods are presented using the obtained constraints for half-space and ellipsoidal safe sets, respectively. The effectiveness of the obtained results is demonstrated using numerical simulations.

B. Sakthisudhursun, S. Muralidharan

Switched capacitor based multilevel inverters with boosting capability are emerging as single stage DC–AC conversion in utilizing low voltage DC sources such as solar PV and fuel cell. This paper proposes a single-phase hybrid multilevel inverter topology based on a switched capacitor that is capable of generating 9-levels along with a voltage gain of 2. The components required to construct the basic module of topology are 11 switches, 1 diode and 2 capacitors. The voltage balancing of the switched capacitors is achieved with the help of a modulation strategy, thereby eliminating the need of sensors. The theoretical loss analysis of the inverter is presented and the nearest level control based fundamental switching frequency modulation technique is employed to study the performance of the proposed inverter. The effectiveness of the suggested topology is validated with the help of a prototype built in the laboratory. The superiority of the proposed topology is assessed with the help of comparison with existing topologies.

Sukyoung Won, Hyeongmin Je, Sanha Kim et al.

Miniaturization of polymeric robots leads to difficulties in actuation inside viscous media due to the increased surface drag on the diminutive robot bodies. Herein, agile underwater swimming of polymeric microrobots is presented with the investigation of correlation between the magnetic propulsion and viscous drag on the robot. The polymeric microrobots swim with pivoting and tumbling motions during underwater rotation by in‐plane rotation of two permanent magnets underneath the plane, which results in orbital revolution‐type locomotion with a maximum swimming velocity of 56 body lengths per second (BL s−1). The rotational ability and orbital velocity of the polymeric microrobots are determined by correlated variables, i.e., liquid viscosity and frequency of magnet rotation, as elucidated by experimental results and theoretical analysis. Based on the understanding of underwater orbital maneuvers, the polymeric microrobots achieve agile swimmability at a viscosity similar to that of normal whole blood and self‐correcting maneuverability in diverse vascular‐like environments, including a stenosed tube with a coarse granular hill and a rough‐walled artificial blood vessel. Agile underwater swimming can improve versatile aquatic performances of miniaturized robots in blood vessels with arteriosclerosis or blood clots.

Anastasis Georgiou, Furqan Tahir, Imad M. Jaimoukha et al.

This paper investigates the problem of robust model predictive control (RMPC) of linear-time-invariant (LTI) discrete-time systems subject to structured uncertainty and bounded disturbances. Typically, the constrained RMPC problem with state-feedback parameterizations is nonlinear (and nonconvex) with a prohibitively high computational burden for online implementation. To remedy this, a novel approach is proposed to linearize the state-feedback RMPC problem, with minimal conservatism, through the use of semidefinite relaxation techniques. The proposed algorithm computes the state-feedback gain and perturbation online by solving a linear matrix inequality (LMI) optimization that, in comparison to other schemes in the literature is shown to have a substantially reduced computational burden without adversely affecting the tracking performance of the controller. Additionally, an offline strategy that provides initial feasibility on the RMPC problem is presented. The effectiveness of the proposed scheme is demonstrated through numerical examples from the literature.

Z. Al-Zhour

Abstract In this work, we discuss the controllability and observability behaviors of a non-homogeneous conformable fractional dynamical system (C-FDS) based on the conformable fractional exponential matrix (C-FEM) and fractional Grammian matrix (FGM). Moreover, the nice relationships between controllability, observability, and stability for non-homogeneous C-FDS are derived. To demonstrate the effectiveness of our obtained results, we present the general solutions (GSs), controllability, observabilities and stabilities to three attractive physical and engineering problems related to compatibility with conformable fractional electrical circuits (C-FECs). Finally, the fractional and classical behaviors of each problem have been covered, respectively, when α  =  1 2 and α  =  1 .