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20th IEEE International Conference on Automation, Quality and Testing, Robotics, AQTR 2016

作者： Rezage, Ghasaq Al Tokhi, M.O. Department of Automatic Control and Systems Engineering University of Sheffield Sheffield United Kingdom

ISBN: (纸本)9781467386906

This paper presents investigations into the development of an assistive device for elderly mobility. An exoskeleton is designed as an assistive device, to enhance the lower extremity and provide supporting torque to augment the torque of hip and knee during the walking cycle. A humanoid and actuated exoskeleton frame are designed in solid works and then imported to Visual Nastran 4D virtual environment. Fuzzy PID control algorithm uses to control the actuated exoskeleton. Simulated walking tasks are performed with a humanoid wearing the exoskeleton. It is assumed that the humanoid representing an elderly person, is able to provide 60% of the whole torque required to complete the gait cycle, and the assistive device providing 40% of the overall torque. © 2016 IEEE.

关键词： Virtual reality

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A hybrid multi-objective evolutionary algorithm using an inverse Neural Network for aircraft control system design

A hybrid multi-objective evolutionary algorithm using an inv...

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2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005

作者： Adra, Salem F. Hamody, Ahmed I. Griffin, Ian Fleming, Peter J. Department of Automatic Control and Systems Engineering University of Sheffield Sheffield United Kingdom

ISBN: (纸本)0780393635

This study introduces a hybrid multi-objective evolutionary algorithm (MOEA) for the optimization of aircraft control system design. The strategy suggested here is composed mainly of two stages. The first stage consists of training an Artificial Neural Network (ANN) with objective values as inputs and decision variables as outputs to model an approximation of the inverse of the objective function used. The second stage consists of a local improvement phase in objective space preserving objectives relationships, and a mapping process to decision variables using the trained ANN. Both the hybrid MOEA and the original MOEA were applied to an aircraft control system design application for assessment. © 2005 IEEE.

关键词： Evolutionary algorithms

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POSITIVE REALNESS PRESERVING MODEL-REDUCTION WITH H-INFINITY NORM ERROR-BOUNDS

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IEEE TRANSACTIONS ON CIRCUITS AND systems I-FUNDAMENTAL THEORY AND APPLICATIONS 1995年第1期42卷 23-29页

作者： CHEN, X WEN, JT Control Laboratory for Mechanical Structures Department of ElectricalComputerand Systems Engineering Rensselaer Polytechnic Institute Troy NY USA

Many physical systems that occur in applications are naturally passive, for example, mechanical systems with dual sensors and actuators, and electrical circuits with passive components. Taking advantage of this property, many controller schemes have been proposed with the property that the controller is strictly positive real. Due to design and implementation considerations, the plant or the controller may need to be approximated by a lower-order system. It is highly desirable for the reduced-order system to also possess the positive realness property to guarantee that the resulting closed-loop system remains stable. Motivated by this problem, this paper considers the general model-reduction problem for a positive real system under the constraint that the reduced system is also positive real. We present a solution based on the balanced stochastic truncation. When the higher-order system is strictly positive real, we derive an H(infinity) norm bound on the approximation error. We also consider alternate approaches of approximating the spectral factors with associated H(infinity) norm error bounds. An example is included to show the efficacy of this method and comparison with other approaches.

关键词： Reduced order systems Mechanical sensors Actuators Stochastic processes Binary search trees Sensor systems and applications Circuits control systems Approximation error Riccati equations

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A Hybrid 1DCNN-SVM Model for Bearing Fault Recognition and Classification 27

A Hybrid 1DCNN-SVM Model for Bearing Fault Recognition and C...

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27th International Conference on Automation and Computing, ICAC 2022

作者： Wang, Guoliang Wei, Hua-Liang University of Sheffield Department of Automatic Control and Systems Engineering Sheffield United Kingdom

ISBN: (数字)9781665498074

ISBN: (纸本)9781665498074

Rolling bearings play a significant role in the operation of rotating machinery. Finding bearing faults in the early stage can not only keep machinery running safely but also avoid economic loss. Traditional machine learning (ML) and deep learning (DL) are two important classes of fault diagnosis methods. The process of feature extraction is significant for ML based methods and many signal processing techniques have been used in this process. However, when dealing with massive and complex signals, features extracted by these techniques may not fully describe the characteristics of faults. Convolutional neural network (CNN) models are applied in many areas, including image identification and classification, pattern recognition, and speech processing. In this paper, a novel hybrid model by combining one dimensional CNN (1DCNN) and support vector machine (SVM) is proposed for bearing fault diagnosis and classification, which is called 1DCNN-SVM model or method. The first part of the model, 1DCNN, is used to extract features of raw data, whereas the second part, SVM, is employed to carry out the fault recognition and classification tasks. The evaluation of the proposed method is operated based on a real dataset. The experiment results show that the fault diagnosis accuracy of proposed method based on the hybrid model is highly improved compared to the traditional SVM based methods. © 2022 IEEE.

关键词： Failure analysis

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Efficient Mask Attention-Based NARMAX (MAB-NARMAX) Model Identification 27

Efficient Mask Attention-Based NARMAX (MAB-NARMAX) Model Ide...

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27th International Conference on Automation and Computing, ICAC 2022

作者： Sun, Yiming Wei, Hua-Liang University of Sheffield Department of Automatic Control and Systems Engineering Sheffield United Kingdom

ISBN: (数字)9781665498074

ISBN: (纸本)9781665498074

Model structure selection is crucial in system identification and data-driven modelling. Many spurious candidate variables can influence the determination of model structures due to the lack of prior knowledge of the system of interest. The commonly used method is to test as many possible models as possible and select a set of best models. This study proposes a novel mask attention-based NARMRAX (MAB-NARMAX) modelling method for nonlinear dynamic system identification. The mask attention mechanism comes from the widely used neural network Transformer to reduce the dependency of the features and neurons. The performance of the proposed method is tested on three simulation datasets. Results show that the proposed MAB-NARMAX modelling framework has convincing multistep-ahead prediction performance for nonlinear system identification in that it can produce the precious model structure. Even when the data are polluted with high noise (resulting in low SNR), the proposed method can still generate reliable system models compared with the state-of-the-art machine learning methods, e.g., LASSO and LSTM. © 2022 IEEE.

关键词： Signal to noise ratio

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Uncertainty analysis of camera parameters computed with a 3D pattern

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13th International Conference on Image Analysis and Processing, ICIAP 2005

作者： Ricolfe-Viala, Carlos Sánchez-Salmerón, Antonio-José Department of Systems Engineering and Automatic Control Polytechnic University of Valencia Valencia Spain

ISBN: (纸本)3540288694

Camera calibration is a necessary step in 3D modeling in order to extract metric information from images. Computed camera parameters are used in a lot of computer vision applications which involves geometric computation. These applications use camera parameters to estimate the 3D position of a feature in the image. Depending on the accuracy of the computed camera parameter, the precision of the position of the image feature in the 3D scene vary. Moreover if previously the accuracy of camera parameters is known, one technique or another can be choose in order to improve the position of the feature in the 3D scene. Calibration process consists of a closed form solution followed by a non linear refinement. This non linear refinement gives always the best solution for a given data. For sure this solution is false since input data is corrupted with noise. Then it is more interesting to obtain an interval in which camera parameters are contained more than an accurate solution which is always false. The aim of this paper is to present a method to compute the interval in which the camera parameter is included. Computation of this interval is based on the residual error of the optimization technique. It is know that calibration process consists of minimize an index. With the residual error of the index minimization an interval can be computed in which camera parameter is. This interval can be used as a measurement of accuracy of the calibration process. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Three dimensional computer graphics

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Systematic Design of Flexible Magnetic Wall and Ceiling Climbing Robot for Cargo Screening

Systematic Design of Flexible Magnetic Wall and Ceiling Clim...

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12th Annual Conference on Towards Autonomous Robotic systems, TAROS 2011

作者： Zhang, Yuanming Dodd, Tony Department of Automatic Control and Systems Engineering University of Sheffield Sheffield United Kingdom

ISBN: (纸本)9783642232312

Cargo screening is an important process to inspect illegal contraband, such as drugs, nuclear materials, weapons and explosives at seaports and airports. A great deal of research has been carried out to address the problem of cargo screening to explore new methods and solutions to improve detection accuracy and rates [1]. In some cases, human or sniffer dogs are required to enter the internal cargo to inspect unidentified substances. However, this is time consuming and potentially dangerous. These problems with correct systems have motivated the development of an innovative solution for cargo inspection in this study. It is known that robotic inspection techniques have been applied to many industries in recent years. However, so far, very little work has been done to develop a cargo screening robotic system. According to the literature, only one related piece of work was found to be proposed by Siegel et al [2], who pointed out that robotic systems could be used to detect illegal contraband in cargo. However, the approach was suggested to use sensors for external cargo detection rather than for internal cargo screening. Consequently, this study aims to demonstrate a systematic design approach to develop an autonomous robotic vehicle to enter the cargo container to detect the contraband for cargo screening process. Fundamentally, several types of robotic vehicles might be applied to enter a cargo container, such as miniature unmanned aerial vehicle (UAV), long robotic arm, flexible snake robot and climbing robot equipped with advanced sensing and navigating system. However, UAVs would need more working space whilst long robotic arm might lack mobility and snake robots require complex mechanics. In these cases, one possible solution is to design a wall and ceiling climbing robot (WCCR) to climb along the wall and ceiling of the cargo container to implement the subsequent inspections. © 2011, Springer-Verlag Berlin Heidelberg.

关键词： Antennas

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A Lightweight Target Following Architecture for Indoor Mobile Robot 25

A Lightweight Target Following Architecture for Indoor Mobil...

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25th IEEE International Conference on Industrial Technology, ICIT 2024

作者： Wang, Fuli Hutabarat, Windo Tiwari, Ashutosh The University Of Sheffield Department Of Automatic Control And Systems Engineering Sheffield United Kingdom

ISBN: (纸本)9798350340266

Manufacturing efficiency and transport operations are being significantly improved by mobile robots. As the implementation of a configurable, lightweight, and stateof-the-art robotic system is required for current manufacturing sectors to maximize the use of mobile robots, this paper presents a software architecture comprised of perception and action systems for human following in real time. The perception system uses the YOLOv8 computer vision model to identify and estimate human pose. Additionally, an algorithm is developed using the 3D information from a stereo camera to determine which target and whether to follow. Once the perception system perceives the desired target information, the action system can control and coordinate the robot using the ROS. Experimental results from the physical robot demonstrate the feasibility of the system architecture. © 2024 IEEE.

关键词： Mobile robots

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A hybrid intelligent closed-loop model for exploration of cardiovascular interactions 4

A hybrid intelligent closed-loop model for exploration of ca...

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4th International IEEE EMBS Special Topic Conference on Information Technology Applications in Biomedicine 2003, ITAB 2003

作者： Elsamahy, E. Mahfouf, M. Linkens, D. Department of Automatic Control and Systems Engineering University of Sheffield Sheffield United Kingdom

ISBN: (纸本)0780376676

Blood is a vital source for delivering oxygen and nutrients to trillions of cells in the body;this makes the function of the cardiovascular system essential to our existence. In the last few years, research interests have been directed to exploring its behaviour as well as its interactions with other systems in the human body under different types of stresses, i.e. mental and physical. In this study, we propose a closed-loop model built for the cardiovascular system, and analyse its interactions under physical-stress conditions. In this study, the signals of interest are: blood pressure, heart rate, temperature and respiration;our proposed model is based on the original Luczak model introduced in 1975. An intelligent system based modelling approach was used to represent the interactions between the cardiovascular system and the other control systems involved;based on the use of three neuro-fuzzy models for generating the blood pressure, heart rate, and temperature signals and a fuzzy-ARX model for generating the respiration signal. The interactions between the control systems that generate these signals are identified, and the estimated signals generated during simulation, for different patients, show good fits when compared with the actual measurements. The description of such complex interactions in patients will allow one to carry out diagnosis and prognosis in terms of the influence of stresses on systemic body functions. © 2003 IEEE.

关键词： Blood pressure

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Preference-Inspired co-evolutionary algorithm using weights for many-objective optimization

Preference-Inspired co-evolutionary algorithm using weights ...

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15th Annual Conference on Genetic and Evolutionary Computation, GECCO 2013

作者： Wang, Rui Purshouse, Robin C. Fleming, Peter J. Department of Automatic Control and Systems Engineering University of Sheffield Sheffield United Kingdom

ISBN: (纸本)9781450319645

Decomposition based approaches are known to perform well on many-objective problems when a suitable set of weights is provided. However, providing a suitable set of weights a priori is difficult. This study proposes a novel algorithm: preference-inspired co-evolutionary algorithm using weights (PICEA-w), which co-evolves a set of weights with the usual population of candidate solutions during the search process. The co-evolution enables suitable sets of weights to be constructed along the optimization process, thus guiding the candidate solutions toward the Pareto optimal front. Experimental results show PICEA-w performs better than algorithms embedded with random or uniform weights.

关键词： Multiobjective optimization

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