Electrohydraulic Drive with a Flow Valve Controlled by a Permanent Magnet Synchronous Motor

This article presents an electrohydraulic drive with a new electrohydraulic flow valve controlled by a Permanent Magnet Synchronous Motor (PMSM), designed and built by the authors. In comparison to a valve with a proportional electromagnet, the use of a PMSM has enabled significant improvements in the key characteristics of the valve. A theoretical framework and a model of a PMSM are presented; subsequently, a valve with this motor is proposed and tested. Step responses of the real valve and its static and frequency characteristics are measured. The characteristics obtained in the simulation are compared with those obtained in the laboratory investigations, showing their good compliance. The obtained characteristics of the new valve are better than those of a typical proportional valve. The new valve is applied in an electrohydraulic linear actuator. For positioning tasks, two types of controllers are applied and compared: a proportional-derivative controller and a fractional order proportional-derivative controller showing satisfactory parameters

A Contribution to the System-Theoretic Approach to Bandwidth Estimation

The network calculus provides a theoretical background for description of traffic in computer networks. Using this tool in explanation of the so-called pathchirp method of measuring the available bandwidth, the validity and range of application of some relationships exploited are verified in this paper. The derivations are carried out in a wider context than that considered in a recent paper by Liebeherr et al. published in IEEE/ACM Transactions on Networking on network bandwidth estimation, providing thereby new insights and outcomes. These results, summarized in a table, show a means of bounding the service curve, depending upon its convexity or non-convexity property assumed and upon the linearity or non-linearity of a network considered. Moreover, it is shown here that the nonlinear network example analyzed by Liebeherr et al. can be viewed equivalently as a linear parametric network. For this network, the behaviour of the cross traffic is considered in a more detail, too

Real-time event classification in field sport videos

The paper presents a novel approach to real-time event detection in sports broadcasts. We present how the same underlying audio-visual feature extraction algorithm based on new global image descriptors is robust across a range of different sports alleviating the need to tailor it to a particular sport. In addition, we propose and evaluate three different classifiers in order to detect events using these features: a feed-forward neural network, an Elman neural network and a decision tree. Each are investigated and evaluated in terms of their usefulness for real-time event classification. We also propose a ground truth dataset together with an annotation technique for performance evaluation of each classifier useful to others interested in this problem

Nine-Axis IMU sensor fusion using the AHRS algorithm and neural networks

This paper presents data processing method for Attitude Heading and Reference System (AHRS) based on Artificial Neural Networks (ANN). The system consist of MEMS (Micro Electro-Mechanical Systems) based on Inertial Measurement Unit (IMU) consisting of tri-axis gyroscopes, accelerometers and magnetometers providing three dimensional linear accelerations and angular rates. Training data was generated by simulation fusion of samples collected during the flight of Quadcopter. The presented results shows proper functioning of the neural network. Moreover, the presented system provide the possibility to easily add other sensors e.g. GPS, in order to achieve better performance

The Use of a Model-Based Controller for Dynamics Improvement of the Hydraulic Drive with Proportional Valve and Synchronous Motor

Electrohydraulic drives consist of several nonlinear elements, and the use and design of their control system is difficult. One of the most important parameters of the industrial drive is its settling time, which characterizes their dynamics. An interesting control method, which can be used for the improvement of electrohydraulic drive properties, is the model-following control (MFC). This technique enables to ensure the good control parameters of nonlinear systems in quite an easy way. In this paper, a modification consisting of changing the oil flow factor in the reference model is proposed. This improves both the dynamics of the electrohydraulic servo drive and the adaptation to the load forces, and thus energy consumption. The article describes the application of the MFC method to control an electrohydraulic servo drive in which a special proportional valve, with an permanent magnet synchronous motor (PMSM), is used. To verify the effectiveness of this method, a theoretical description of the drive is proposed. The applied MFC control system is then modeled and investigated in simulations. Lastly, laboratory investigations are made and chosen results are presented and described in the paper. The results obtained in simulation are compared with results obtained in laboratory tests. The investigations show that the usage of MFC shortens the drive settling time and, in this way, improves its dynamics

Investigations of applications of smart materials and methods in fluid valves and drives

In the paper the investigations performed at the Division of Mechtronic Devices at Poznan University of Technology in the area of application of both: smart materials in electro-hydraulic and electro-pneumatic valves, and new methods to control of hydraulic servo drives, are presented. In a first part the piezo bender actuator is shortly described and its application in servo valve is proposed. This actuator replaced the torque motor in the available on the market servo valve. The new valve simulation model is proposed. The simulation and investigations results of the servo valve with the piezo bending actuator are included. In the next part of the paper the application of piezo tube actuator in flapper-nozzle pneumatic valve is described. The test stand and investigations results are presented. Later, in the article, the Model Following Control (MFC) and Fractional order Control (FoC) methods are described. Their application in control of electrohydraulic servo drive is proposed. Some investigations results are included in the paper, showing the advantages of those control methods

Smart Asset Management for District Heating Systems in the Baltic Sea Region

The purpose of this review is to provide insight and a comparison of the current status of district heating (DH) systems for selected Baltic Sea countries (Denmark, Germany, Finland, Latvia, Lithuania, Poland, and Sweden), especially from viewpoints of application and solutions of novel smart asset management (SAM) approaches. Furthermore, this paper considers European projects ongoing from 2016, involving participants from the Baltic Sea Region, concerning various aspects of DH systems. The review presents the energy sources with particular attention to renewable energy sources (RES), district heating generations, and the exploitation problems of DH systems. The essential point is a comparison of traditional maintenance systems versus SAM solutions for optimal design, operating conditions, and controlling of the DH networks. The main conclusions regarding DH systems in Baltic Sea countries are commitment towards a transition to 4th generation DH, raising the quality and efficiency of heat supply systems, and simultaneously minimizing the costs. The overall trends show that applied technologies aim to increase the share of renewable energy sources and reduce greenhouse gas emissions. Furthermore, examples presented in this review underline the importance of the implementation of a smart asset management concept to modern DH systems

Time synchronization in distributed sensor network

Time synchronization in a distributed sensor network is a key issue. Data from the sensors are properly synchronized are very good material for further analysis. In the paper a network of medical sensors is presented. It is important to obtain a properly synchronized data from the sensors. This guarantee that the data can be processed to detect correlation between different signals. For the purpose of accurate time synchronization, the simple and efficient algorithm is presented

Gradient method of learning for stochastic kinetic model of neuron

In this paper we are focusing on the kinetic extension [4] of classic model of Hodgkin and Huxley [2]. We are showing the descent gradient method used in the learning process of neuron, which is described with stochastic kinetic model. In comparison with [1] we use only 3 weights instead of 9: gNa; gK and gL: We show that this model behaves equally accurate as the model of Hodgkin and Huxley with slighter system description