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A Data Transmission Approach Based on Ant Colony Optimization and Threshold Proxy Re-encryption in WSNs

Journal of Artificial Intelligence and Technology 2022年第1期2卷 23-31页

作者： Jing Liu Zenghui Liu Chenyu Sun Junxi Zhuang College of Computer Science Faculty of Information TechnologyBeijing University of TechnologyBeijing 100124China Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of EducationBeijing 100124China College of Automation Engineering Beijing PolytechnicBeijing 100176China

Wireless sensor networks(WSNs)have become increasingly popular due to the rapid growth of the Internet of *** open wireless transmission media are easy to attack,security is one of the primary design concerns for *** solutions consider routing and data encryption as two isolated issues,providing incomplete ***,in this paper,we divide the WSN communication process into a data path selection phase and a data encryption *** propose an improved transmission method based on ant colony optimization(ACO)and threshold proxy re-encryption for WSNs,and we named it as *** method resists internal and external attacks and ensures safe and efficient data *** the data path selection stage,the ACO algorithm is used for network *** improvement of the pheromone concentration is *** order to resist attacks from external attackers,proxy re-encryption is extended to WSN in the data encryption *** threshold secret sharing algorithm is introduced to generate a set of re-encryption key fragments composed of random numbers at the source *** confirm the performance of our model via simulation studies.

关键词： wireless sensors network ant colony optimization pheromone proxy re-encryption threshold

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Design of Face Recognition Access Entrance Guard System with Mask Based on Embedded Development 2

Design of Face Recognition Access Entrance Guard System with...

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2021 2nd International Conference on computer Information and Big Data Applications, CIBDA 2021

作者： Ruiqin, Lin Wenan, Tan Zhenyu, Chen Qinqin Faculty of Environmental and Materials Engineering Shanghai Polytechnic University Shanghai201209 China Computer Engineering Shanghai Polytechnic University Shanghai201209 China Department of Measurement and Control and Automation Shanghai Polytechnic University Shanghai201209 China

This paper investigates all kinds of access entrance guard control systems at home and abroad and analyzes their advantages and disadvantages. COVID-19 epidemic has a serious impact on life, travel must wear a mask, so that the access entrance guard control system can not carry out face recognition under the mask. In view of this kind of situation, an embedded face recognition access entrance guard control system with mask based on EAIDK-310 development board is designed. The system can complete face recognition and body temperature measurement without contact, and drive the motor to open the gate. After testing, the system is suitable for deployment in companies, communities, campuses and other small application scenarios. It is convenient to travel and can reduce the impact of the epidemic. © Published under licence by IOP Publishing Ltd.

关键词： Face recognition

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Discrete time minimax tracking control with disturbance estimation 10

Discrete time minimax tracking control with disturbance esti...

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2009 10th European control Conference, ECC 2009

作者： Bauer, Peter Kulcsar, Balazs Bokor, Jozsef Systems and Control Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences BudapestH-1111 Hungary Delft Center for System and Control Faculty of Mechanical Maritime and Materials Engineering Technical University of Delft Mekelweg 2 Delft Netherlands

ISBN: (纸本)9783952417393

The paper proposes an alternative way to solve robust reference tracking problem. Instead of rejecting the effect of the disturbance directly, an intermediate step is built into the state estimation problem. The advantage of the methodology is to elaborate a modified optimal state estimation problem taking the unbiased estimate of the disturbance into account. Henceforward, the solution of the discrete time, optimal LQ minimax tracking problem is modified and subjected to attenuate the disturbance residual. The paper addresses the nominal case for constant reference and disturbance signal showing the asymptotical stability and the tracking performance of the discrete time, optimal min-max control. Suboptimal solution is given for time varying reference and disturbance signal. A linearized hovering quadrotor example demonstrates the importance of the suggested technique. © 2009 EUCA.

关键词： State estimation

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Fuzzy Autopilot for Ships Experiencing Shallow Water Effect in Manoeuvering

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IFAC Proceedings Volumes 1997年第22期30卷 99-104页

作者： Zoran Vukić Edin Omerdić Ljubomir Kuljača University of Zagreb Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering in Automation Unska 3 HR-10000 Zagreb Croatia

A fuzzy autopilot for ship path control is proposed. Nonlinear model of a ship and a steering subsystem is used. The autopilot uses heading signal and yaw rate signal to produce a command rudder angle. The autopilot does not use lateral offset from the nominal track. Input variable fuzzyfication, fuzzy associative memory rules and output set defuzzyfication are described. The influence of the shallow water effect during larger maneuver is analyzed.

关键词： Disturbance rejection Fuzzy control Nonlinear control systems Ship control

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Texture Analysis of Breast US Images Using Morphological Transforms, Hausdorff Dimension and Bagging Ensemble Method 32

Texture Analysis of Breast US Images Using Morphological Tra...

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32nd Mediterranean Conference on control and automation, MED 2024

作者： Tabacaru, Gigi Moldovanu, Simona Barbu, Marian 'Dunarea de Jos' University of Galati Faculty of Automation Computers Electrical Engineering and Electronics Department of Automatic Control and Electrical Engineering Romania 'Dunarea de Jos' University of Galati Computer Science and Information Technology Faculty of Automation Computers Electrical Engineering and Electronics Romania Dunarea de Jos University of Galati The Modelling & Simulation Laboratory Galati800008 Romania

ISBN: (纸本)9798350395440

In this work, an attempt is made for the first time to use the measurement pattern generated by morphological transformation quantified by Hausdorff fractal dimension (HFD) and classified with ensemble learning based on bagging. The proposed work uses three morphological transformations for image preprocessing: hit-and-miss transform (HMT), white (WHT), and black top-hat (BHT). The pattern texture of US breast images is described by extracting the HFD from the regions of interest (ROI) after the ultrasound (US) images have been preprocessed. The main objective of this study was achieved by comparatively analyzing the classification performance of features using the Random Forest (RF), Extra Trees (ET) classifier, and bagging ensemble method based on XGBoot classifier. In presented study, the XGBoost classifier and BHT image processing method give an accuracy of 89.8% in a binary classification, benign versus malignant breast cancer. © 2024 IEEE.

关键词： Fractal dimension

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Supervisory control by using active virtual 3D models in-the-loop

Supervisory control by using active virtual 3D models in-the...

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IEEE International Conference on computer-Aided Design

作者： Tomislav Reichenbach Damjan Miklic Zdenko Kovacic Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering in Automation University of Zagreb Croatia

Virtual 3D models play important role in a today factory layout design, physical modeling, control synthesis, performance analysis, dynamic simulation and visualization of real systems. In this paper, we go one step further and besides visualization, we monitor all measurable states in the real system and use active 3D models in-the-loop for real-time supervisory control. Such concept enables an event detection not possible with conventional sensors, including the ability to predict possible outcomes in the system operation. A virtual environment simulator and the way it can be connected to other simulators (e.g., Matlab/Simulink), is presented. The examples of virtual sensors, and collision free-based trajectory planning for robotic manipulators are demonstrated

关键词： Supervisory control Mathematical model Visualization Production facilities control system synthesis Performance analysis Analytical models Real time systems Event detection Sensor systems

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A reinforcement learning approach to obstacle avoidance of mobile robots

A reinforcement learning approach to obstacle avoidance of m...

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International Workshop on Advanced Motion control (AMC)

作者： K. Macek I. Petrovic N. Peric Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering in Automation University of Zagreb Croatia

One of the basic issues in the navigation of autonomous mobile robots is the obstacle avoidance task that is commonly achieved using a reactive control paradigm where a local mapping from perceived states to actions is acquired. A control strategy with learning capabilities in an unknown environment can be obtained using reinforcement learning where the learning agent is given only sparse reward information. This credit assignment problem includes both temporal and structural aspects. While the temporal credit assignment problem is solved using core elements of the reinforcement learning agent, solution of the structural credit assignment problem requires an appropriate internal state space representation of the environment. In this paper, a discrete coding of the input space using a neural network structure is presented as opposed to the commonly used continuous internal representation. This enables a faster and more efficient convergence of the reinforcement learning process.

关键词： Learning Mobile robots control engineering computing Automatic control Neural networks Fuzzy logic Path planning Robotics and automation Navigation State-space methods

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A self-Tuning decentralized PI control for multivariable plant

A self-Tuning decentralized PI control for multivariable pla...

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2012 IEEE International Conference on control System, Computing and engineering, ICCSCE 2012

作者： Samsudin, S.I. Rahrnat, M.F. Wahab, Norhaliza Abdul Razali, Mashitah Che Gaya, Muhamad Sani Salim, Sy Najib Sy Department of Industrial Electronics Faculty of Electronics and Computer Engineering Universiti Teknikal Malaysia Melaka Hang Tuah Jaya 76100 Durian Tunggal Melaka Malaysia Department of Control and Instrumentation Engineering Faculty of Electrical Engineering Universiti Teknologi Malaysia 81310 Skudai Malaysia Department of Control Instrumentation and Automation Faculty of Electrical Engineering Universiti Teknikal Malaysia Melaka Hang Tuah Jaya 76100 Durian Tunggal Melaka Malaysia

ISBN: (纸本)9781467331432

Tuning of controller is one of the most basic functions in control engineering in obtaining optimal control parameters and hence achieving optimal dynamic responses of the system. The work presents the self-Tuning PI controller that potential to auto-Tune the controller parameters and adapting the changes in controlled process parameter for a MIMO system. The decentralized PI controller with an adaptive interaction algorithm is developed and tested to nonlinear multivariable wastewater treatment plant. It is aims to self-Tune the PI control parameters in regulating the substrate and DO concentrations from a steady state operating point. It was observed that the proposed control structure and the tuning algorithm were successfully tracks the desired set-point with considerable effects in noisy environment. © 2012 IEEE.

关键词： MIMO systems

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Adaptive Prescribed-Time Neural control of Nonlinear Systems via Dynamic Surface Technique

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第10期5卷 4948-4958页

作者： Wang, Ping Yu, Chengpu Lv, Maolong Zhao, Zilong Beijing Institute of Technology School of Automation Beijing100081 China Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China Air Force Engineering University College of Air Traffic Control and Navigation Xi'an710051 China Delft University of Technology Faculty of Electrical Engineering Mathematics and Computer Science Delft2628 CD Netherlands

The adaptive practical prescribed-time (PPT) neural control is studied for multiinput multioutput (MIMO) nonlinear systems with unknown nonlinear functions and unknown input gain matrices. Unlike existing PPT design schemes based on backstepping, this study proposes a novel PPT control framework using the dynamic surface control (DSC) approach. First, a novel nonlinear filter (NLF) with an adaptive parameter estimator and a piecewise function is constructed to effectively compensate for filter errors and facilitate prescribed-time convergence. Based on this, a unified DSC-based adaptive PPT control algorithm, augmented with a neural networks (NNs) approximator, is developed, where NNs are used to approximate unknown nonlinear system functions. This algorithm not only addresses the inherent computational complexity explosion associated with traditional backstepping methods but also reduces the constraints on filter design parameters compared to the DSC algorithm that relies on linear filters. The simulation showcases the effectiveness and superiority of the devised scheme by employing a two-degree-of-freedom robot manipulator. © 2024 IEEE.

关键词： Flexible manipulators

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An anti-slip predictive controller for a V-PRA vehicle

An anti-slip predictive controller for a V-PRA vehicle

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作者： Cochior, Carmen De Keyser, Robin Lazar, Corneliu Electrical Engineering Department Eindhoven University of Technology Eindhoven Netherlands EeSA-Department of Electrical Energy Systems and Automation Ghent University Ghent Belgium Department of Automatic Control and Applied Informatics Faculty of Automatic Control and Computer Engineering Technical University Gh. Asachi Iasi Romania

ISBN: (纸本)9783902661937

In this paper an anti-slip predictive controller is designed and implemented in order to control the rear wheels of a V-PRA (Variable Powered Rear Axle) vehicle. The control algorithm is EPSAC, a Model based Predictive control (MPC) strategy. It uses explicitly a model of the system for the prediction of the future system output, in order to calculate the optimal control input which will bring the system to a required setpoint. The main goals of this predictive controller were setpoint trajectory following, disturbance rejection and maintain overall the stability of the V-PRA vehicle. Although the process is nonlinear, being influenced by several parameters, linear discrete-time ARX models could be obtained based on system linearization around an operating point. An initial SISO controller was developed and tested, based on a Simulink model of the process. The control performances were tested successfully in presence of all kind of disturbances, denoting a robust controller. © 2011 IFAC.

关键词： Vehicles

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