The aim of this paper is to check whenever usage of sequence based neural networks for predicting compressed air demand can be useful in screw compressor room supervisory control systems. Industrial enterprises freque...
The aim of this paper is to check whenever usage of sequence based neural networks for predicting compressed air demand can be useful in screw compressor room supervisory control systems. Industrial enterprises frequently employ compressed air systems to generate the compressed air needed for daily operations. Data was gathered from three different compressor rooms with different air demand characteristics and configuration over the period of one month. Then data was prepared, analyzed, trained and tested followed by simulation tests which determined usefulness of trained networks. Since nowadays high energy prices force energy saving build of the screw compressor itself the purpose of this text was to check if there is any room for optimization in less modern and also modern applications.
This study addresses the decoupling issue within the Active Disturbance Rejection control (ADRC) framework, taking into account the existence of additional dynamics in the plant input path. These additional dynamics a...
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ISBN:
(数字)9798350362343
ISBN:
(纸本)9798350362350
This study addresses the decoupling issue within the Active Disturbance Rejection control (ADRC) framework, taking into account the existence of additional dynamics in the plant input path. These additional dynamics are not directly incorporated into the observer equations. The paper proposes a compensation strategy that employs a filter to shape the observer’s input signal. The transfer function forms for the structure under analysis, as well as the matching conditions in the input path, have been established. The findings indicate that while the use of an input filter can enhance the stability of the decoupling loop, it may also reduce the disturbance attenuation. The conclusions drawn from analytical studies and numerical simulations are validated by experimental results.
Pedestrian detection algorithms have a wide range of applications: from video surveillance, to driver assistance systems and autonomous vehicles. The performance of these systems must be as high as possible, with mini...
Pedestrian detection algorithms have a wide range of applications: from video surveillance, to driver assistance systems and autonomous vehicles. The performance of these systems must be as high as possible, with minimal response time and, due to the often battery-powered operation (like in electric vehicles), low energy consumption. When designing such solutions, we therefore face challenges typical for embedded vision systems: the problem of fitting algorithms of high memory and computational complexity into small low-power devices. In this paper, we propose a system based on a Dynamic Vision Sensor (DVS), which has low power requirements and operates well in conditions with variable illumination. It is these features that may make event cameras a preferential choice over frame cameras in some applications. To ensure high accuracy, for pedestrian detection we use the YOLO (You Only Look Once) deep network on event data representation. Due to the high complexity of the applied algorithm, we propose a low precision architecture: the weights of the convolution layers are quantized logarithmically to 4 bits powers-of-two values (PoT quantization). Such compression reduces not only the memory complexity by almost 8x, but also the computational complexity by replacing most multiplication operations with bit-shifting, due to use of powers-of-two weights. At the same time, the proposed system achieves the accuracy on par with the floating point baseline, of mAP0.5 0.708.
A high roll rate can decrease the chance of the research-oriented rocket mission success. There is scant information about the effective roll-motion stabilizer solutions for sounding rockets. Thus, a roll-motion stabi...
A high roll rate can decrease the chance of the research-oriented rocket mission success. There is scant information about the effective roll-motion stabilizer solutions for sounding rockets. Thus, a roll-motion stabilizer for a sounding rocket using the active disturbance rejection control (ADRC) methodology is proposed. The presented roll-motion stabilizer is designed for a subsonic sounding rocket. An effectiveness of the designed control system was verified by simulations and experiments in a wind tunnel. Results of the verification show that the designed control system enables robust roll-motion stabilization despite large uncertainty of a rocket model. Practical guidelines for designing of the roll-motion stabilizer are provided.
Recent advances in event camera research emphasize processing data in its original sparse form, which allows the use of its unique features such as high temporal resolution, high dynamic range, low latency, and resist...
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3D object detection from LiDAR sensor data is an important topic in the context of autonomous cars and drones. In this paper, we present the results of experiments on the impact of backbone selection of a deep convolu...
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The error-based active disturbance rejection control (EADRC) structure is investigated to obtain precise tracking control of a mechanical system with one degree of freedom. We formally take into account the uncertaint...
The error-based active disturbance rejection control (EADRC) structure is investigated to obtain precise tracking control of a mechanical system with one degree of freedom. We formally take into account the uncertainty of the input gain, which affects the performance of the controller, and consider stability of the closed-loop system for the full-order and reduced-order extended-state observers (ESOs). Apart from theoretical analysis, we present experimental results, which confirm that the application of the reduction-order observer can improve control performance. We also investigate whether the explicit formulation of the feedforward in EADRC makes it possible to improve the tracking precision under real conditions.
Airborne transmission is a key element in the spread of viral contagion. To prevent this, health organization publish guidelines for every major disease outbreak. However, they are often based on researches carried ou...
Airborne transmission is a key element in the spread of viral contagion. To prevent this, health organization publish guidelines for every major disease outbreak. However, they are often based on researches carried out without access to modern solutions. In this paper, we propose usage of Bayesian inference as an additional, to computationally-intensive methods such as CFD or FEM, way to analyse short - range virus exposure. We build a spatial model, using INLA package, which allows us to optimize the complicated computational process and deal with conundrums of virus exposure modeling.
The presented paper contains comparison two algorithms for searching optimal value of PID controllers: particle swarm optimization (PSO) and fractional-order particle swarm optimization (F-PSO) for the control system ...
The presented paper contains comparison two algorithms for searching optimal value of PID controllers: particle swarm optimization (PSO) and fractional-order particle swarm optimization (F-PSO) for the control system of capsubot robot. A cost function which is used with PSO and F-PSO is presented. At the end, the obtained simulation results are shown and discussed.
Active control of aeroservoelasticity effect is critical for future aircraft. This paper concerns the flutter suppression problem for a benchmark active control technology (BACT) wind-tunnel model, which is subject to...
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