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IEEE Conference on Emerging Technologies and Factory Automation

作者： A. Sanchez-Fernandez M. J. Fuente G. I. Sainz-Palmero Department of System Engineering and Automatic Control EII University of Valladolid

ISBN: (纸本)9781467379304

This paper proposes a distributed fault detection and diagnosis method based on Principal Component Analysis (PCA) in a whole plant monitoring scheme. The method is based on the decomposition of the plant into multiple blocks using plant topology. A local PCA based fault detection method is applied in each block and the results are sent to the central node to fuse the information and to detect and diagnose faults in the global plant. This method is compared with the centralized PCA method and some distributed principal component analysis (DPCA) methods in a wastewater treatment plant (WWTP). The objective is to check which of the distributed methods implemented is the best one in terms of detecting faults and minimizing the communication cost between the blocks. Empirical results on the WWTP show that the DPCA method based on local models has very good results.

关键词： Defect detection Sewage treatment plants principal components analysis Passive Cutaneous Anaphylaxis Set of central axillary lymph nodes dichlormid Distribute faults plants

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Derivative-Free Data-Driven control of Continuous-Time Linear Time-Invariant systems

arXiv

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arXiv 2024年

作者： Bosso, Alessandro Borghesi, Marco Iannelli, Andrea Notarstefano, Giuseppe Teel, Andrew R. Department of Electrical Electronic and Information Engineering University of Bologna Italy Institute for System Theory and Automatic Control University of Stuttgart Germany Department of Electrical and Computer Engineering University of California Santa BarbaraCA United States

This paper develops a data-driven stabilization method for continuous-time linear time-invariant systems with theoretical guarantees and no need for signal derivatives. The framework, based on linear matrix inequalities (LMIs), is illustrated in the state-feedback and single-input single-output output-feedback scenarios. Similar to discrete-time approaches, we rely solely on input and state/output measurements. To avoid differentiation, we employ low-pass filters of the available signals that, rather than approximating the derivatives, reconstruct a non-minimal realization of the plant. With access to the filter states and their derivatives, we can solve LMIs derived from sample batches of the available signals to compute a dynamic controller that stabilizes the plant. The effectiveness of the framework is showcased through numerical examples. © 2024, CC BY.

关键词： Continuous time systems

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Modeling, control and robustness analysis for a road sector

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IFAC Proceedings Volumes 2010年第17期43卷 307-312页

作者： Catalin Dimon Genevieve Dauphin-Tanguy Dumitru Popescu Department of Automatic Control and System Engineering University Politehnica of Bucharest 313 Splaiul Independentei 060042 Bucharest Romania LAGIS Ecole Centrale de Lille Cité Scientifique - BP 48 - 59651 Villeneuve d'Ascq Cedex

When modeling a real process the effects of nonlinearities must be taken into account, especially when designing a control algorithm. Such is the case of a road traffic sector, which will be considered from a macroscopic point of view. An input-output model is proposed, based on experimental data, and then a control algorithm is used to obtain imposed performances for the closed loop system. The robustness of control is taken into account, by assessing the modulus margin. Based on this indicator the robustness of the control law is analyzed in order to find what nonlinearities it can cope with. Following, we try to prove that the system can be controlled using the same algorithm, when different types of perturbations affect the system.

关键词： modeling control robustness sampling time traffic

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State of the art of hybrid excitation permanent magnet synchronous machines

State of the art of hybrid excitation permanent magnet synch...

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2010 International Conference on Electrical Machines and systems, ICEMS2010

作者： Wang, Shanming Xia, Yonghong Wang, Xiangheng Su, Pengsheng Huang, Shaogang Zhang, Anming State Key Laboratory of Control and Simulation of Power System and Generation Equipments Department of Electrical Engineering Tsinghua University Beijing 100084 China Department of Electrical and Automatic Engineering Nanchang University Nanchang Jiangxi 330031 China Military Deputy Department Dalian 426 Factory No.1 Yanhai Jie Xigang Qu Dalian Liaoning 116005 China

The hybrid excitation permanent magnet machine (HEPMM) combines two kinds of excitation: permanent magnet (PM) and electrical excitation, so it possesses the advantages of PM machines and overcomes the incapability of regulating the excitation field. By now many HEPMM schemes have been presented. In this paper the operation principle, structure, advantages and disadvantages of these HEPMMs have been reviewed and compared in detail. These HEPMMs are classified into three types by new classification method - placement of PM and iron poles. At last novel harmonic excitation HEPMM is proposed and discussed.

关键词： Iron Magnetic fields Windings Stator cores Rotors Stator windings Magnetic circuits

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CARS setup for exhaust gas and combustion analysis

CARS setup for exhaust gas and combustion analysis

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IEEE Conference on Vehicle Power and Propulsion (VPPC)

作者： Hu Zhang Jing-min Dai Zhao Jin Chun-suo Xin Institute of Automatic Detecting and Process Control System (D&CS) Harbin Institute of Technology Harbin China Department of Electrical Engineering Harbin Institute of Technology Harbin China

ISBN: (纸本)9781424418480

Coherent anti-stokes Raman spectroscopy (CARS) is introduced, and several existing CARS methods are discussed and compared. Application in vehicle research is attempted through necessary modification on the basis of classical CARS theory. Classical theoretical spectrum calculation model is still suitable for the new situation. The design of CARS setup, which provides solutions for not only exhaust gas analysis but also engine combustion evaluation, is put forward. As the typical probe molecule, N 2 is modeled for combustion evaluation while CO 2 is emphasized on exhaust gas analysis. For multi-species analysis, several advanced CARS methods are introduced and expanded setup design using dual-pump CARS is shown. Elementary analysis has demonstrated that CARS has the capabilities of combustion evaluation and exhaust gas analysis. Temperature measurement accuracy can be plusmn10 K or higher and spatial resolution can be 1 cm or higher according to the instrument performance. Despite of some drawbacks the setup we developed can be useful for vehicle detection.

关键词： Combustion Vehicles Plasma measurements Raman scattering Plasma temperature Engines Instruments Frequency Spectroscopy Nonlinear optics

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Investigation of Genetic Algorithms On-Line Application for Aero Engine Modelling and Condition Monitoring

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IFAC Proceedings Volumes 2004年第6期37卷 1043-1047页

作者： T.V. Breikin G.G. Kulikov V.Y. Arkov H.A. Thompson P.J. Fleming Automatic Control and System Engineering Department The University of Sheffield Mappin Str. Sheffield SI 3JD. UK Department of Automated Control Systems Ufa State Aviation Technical University K. Marx Street 12 Ufa 450000 Russia.

In this paper an application of genetic algorithms for on-line multi-objective optimisation is considered. Two different multi-objective evolutionary computational techniques are implemented for optimal selection of gas turbine engine real-time model structure. The real engine data was used for identification and optimisation of the engine model parameters. The results of genetic algorithm application for engine model on-line optimisation are discussed.

关键词： aerospace optimisation genetic algorithms

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Axially and Radially Expandable Modular Helical Soft Actuator for Robotic Implantables

Axially and Radially Expandable Modular Helical Soft Actuato...

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IEEE International Conference on Robotics and Automation

作者： Eduardo R. Perez-Guagnelli Sarunas Nejus Jian Yu Shuhei Miyashita YanQiang Liu Dana D. Damian Automatic Control and System Engineering Department University of Sheffield UK School of Mechanical Engineering and Automation Beihang University China Department of Electronic Engineering University of York UK Centre of Assistive Technology and Connected Healthcare University of Sheffield UK

Soft robotics has advanced the field of biomedical engineering by creating safer technologies for interfacing with the human body. One of the challenges in this field is the realization of modular soft basic constituents and accessible assembly methods to increase the versatility of soft robots. We present a soft pneumatic actuator composed of two elastomeric strands that provide interdependent axial and radial expansion due to the modularity of the components and their helical arrangement. The actuator reaches 35% of elongation with respect to its initial height and both chambers achieve forces of 1N at about 19kPa. We describe the design, fabrication, modeling and benchtop testing of the soft actuator towards realizing 3D functional structures with potential medical applications. An example of application for soft medical robots is tissue regenerative for the long-gap esophageal atresia condition.

关键词： Actuators Implants Soft robotics Esophagus Surgery Mathematical model

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An effective PSO-TLBO algorithm for multi-objective optimization

An effective PSO-TLBO algorithm for multi-objective optimiza...

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Congress on Evolutionary Computation

作者： Tingli Cheng Minyou Chen Peter J. Fleming Zhile Yang Shaojun Gan School of Electrical Engineering Chongqing University Chongqing China Department of Automatic Control & System Engineering University of Sheffield Sheffield UK School of Electronics Electrical Engineering and Computer Science Queens University Belfast Belfast UK

In this study, we present an effective hybrid algorithm based on particle swarm optimization (PSO) and teaching-learning-based optimization (TLBO), called PSO-TLBO, to solve multi-objective optimization (MOO) problems. In PSO-TLBO, teacher phase and learner phase in TLBO are incorporated to a PSO to improve the exploration and exploitation ability. Another feature of PSO-TLBO is the improved circular crowed sorting (CCS) to truncate the external archive which stores the nondominated solutions found during the search. Moreover, the polynomial mutation is used only when the velocities of all solutions are very small. The performance of PSO-TLBO algorithm for MOO is tested on ZDT and DTLZ benchmarks functions and compared with some powerful MOO algorithms in terms of both convergence and spread performance. Also, the contribution of CCS is compared with crowded sorting in NSGA-II. Comparison results reveal the powerful ability of PSO-TLBO to obtain remarkable solutions in terms of inverted generational distance (IGD) metrics.

关键词： Optimization Sociology Statistics Sorting Particle swarm optimization Benchmark testing Convergence

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Subspace-Based Blind Identification of IIR systems

Subspace-Based Blind Identification of IIR Systems

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IEEE Workshop on Machine Learning for Signal Processing

作者： Juan C. Gomez Enrique Baeyens Laboratory for System Dynamics and Signal Processing FCEIA Universidad Nacional de Rosario Rosario Argentina Department of Systems Engineering and Automatic Control Universidad de Valladolid Valladolid Spain

A new subspace method for the blind identification of infinite impulse response (IIR), single input-multiple output (SIMO) systems represented using orthonormal bases with fixed poles, is presented in this paper. Basis coefficients are estimated in closed form, up to a scalar factor, by first computing the column space of the output Hankel matrix using singular value decomposition (SVD), and then solving a least squares problem also resorting to an SVD. The performance of the proposed algorithm is illustrated through a simulation example.

关键词： Finite impulse response filter Stability Sensor arrays Signal processing Matrix decomposition Singular value decomposition Least squares approximation Signal processing algorithms Computational modeling Digital communication

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Discovering Stop and Parking Behaviors of Last Mile Delivery Vehicles for Urban Areas Based on Not Well Conditioned Gps Traces, Expert Knowledge and Machine Learning

SSRN

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SSRN 2023年

作者： Galende-Hernández, Marta Sainz-Palmero, Gregorio I. Fuente, Maria J. Department of System Engineering and Automatic Control School of Industrial Engineering Universidad de Valladolid Valladolid47011 Spain CARTIF Centro Tecnologico Parque Tecnologico de Boecillo Valladolid Boecillo47151 Spain

Nowadays urban traffic is one of the most serious challenges for local authorities around the world. This challenge implies issues regarding health, energy, safety, environment and quality of life. Achieving a fair traffic outcome is a key priority for city traffic managers while maintaining city’s attractiveness for citizens and travellers and those carrying out commercial activities. As a part of this challenge, delivery and similar companies are relevant stakeholders in optimizing their routes, deliveries, and operational services. It is in this respect that urban traffic and its regulations play a key *** conditions in which urban traffic takes place thus have to be known and one way to deal with this is based on available and accessible data. In the IoT age, there could be huge amounts of available data generated by countless sensors and systems involved in our lives, cities, infrastructures, etc.... Taking advantage of such data, when the accessibility and quality is good enough, can help us to achieve the desired goals concerning the urban traffic and its consequences. However, in practice, the availability and access to such data is currently a very serious *** on with this, data generated from the ever-increasing number of sensors on board vehicles could be very useful, not only for checking the vehiclecondition, but also to gain a better of the "real-time" traffic situation or to discover traffic behaviors/patterns from the said *** this work, a realcase based study has been carried out gathering basic real GPS information regarding delivery vehicles in a city environment and OpenData to "discover" where, when and how long time delivery vehicles use the regulated parking zones for loading/unloading in the city center. Based on Expert Rules, a stop detection criteria is defined and formulated to be applied to real cases in urban areas, focusing on city centers and Machine Learning techniques to discover stop and park behaviors on la

关键词： Parks

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