Thermal and performance analysis of a gasification boiler and its energy efficiency optimization

The purpose of this study was to determine a method for multi-parametric output regulation of a gasification boiler especially designed for heating or for hot water heating in buildings. A new method of regulation is offered, namely more parametric regulation via proportional-integral-derivative (PID) controllers that are capable of controlling the calculated values of pressure, temperature and fan speed. These values of pressure, temperature and fan speed are calculated in a completely new way, and calculations of setpoints for determination of optimal parameters lead to an increase in boilers efficiency and power output. Results of measurements show that changes at the mouth of the stack draft due atmospheric influences occur in times with high intensity and high frequency, while power parameters, or boiler power output amplitudes and fan speed automatically "copy" those changes proportionally due to instantaneous fan speed changes. The proposed method of regulation of the gasification boiler power output according to the technical solution enables a simple, cheap, express and continuous maintenance of high power output at low concentrations of the exhaust gases of the gasification boilers from the viewpoint of the boiler user, as well as from the perspective of development and production it allows a continuous control monitoring of these parameters.Web of Science107art. no. 106

Approximation Possibilities of Fuzzy Control Surfaces for Purpose of Implementation into Microcontrollers

The main contribution of the paper is the simplification of the computational process of fuzzy control of a mobile robot controlled by a microcontroller. We present a way to implement this control method with a reduced computation time of control actions and memory demand. Our way to accomplish this, was to replace the fuzzy controller with the approximation of its resulting control surfaces. In the paper, we use the previously presented approximation by the table and describe other methods of approximation of the control area through polynomial and exponential function. We tested all approximation methods in simulations and with a real mobile robot. Based on the measured trajectory of the EN20 mobile robot, we found that approximation through the table is the most accurate in terms of the fuzzy surface but delivers noticeable oscillations of mobile robot control in real conditions. Polynomial and exponential functions fuzzy surface approximations were less accurate than the table, but provide smoother control based on robot trajectories and are much more appropriate in terms of microcontroller implementation due to lower demand on memory

Radial Basis Function Neural Network-Based Modeling of the Dynamic Thermo-Mechanical Response and Damping Behavior of Thermoplastic Elastomer Systems

The presented work deals with the creation of a new radial basis function artificial neural network-based model of dynamic thermo-mechanical response and damping behavior of thermoplastic elastomers in the whole temperature interval of their entire lifetime and a wide frequency range of dynamic mechanical loading. The created model is based on experimental results of dynamic mechanical analysis of the widely used thermoplastic polyurethane, which is one of the typical representatives of thermoplastic elastomers. Verification and testing of the well-trained radial basis function neural network for temperature and frequency dependence of dynamic storage modulus, loss modulus, as well as loss tangent prediction showed excellent correspondence between experimental and modeled data, including all relaxation events observed in the polymeric material under study throughout the monitored temperature and frequency interval. The radial basis function artificial neural network has been confirmed to be an exceptionally high-performance artificial intelligence tool of soft computing for the effective predicting of short-term viscoelastic behavior of thermoplastic elastomer systems based on experimental results of dynamic mechanical analysis

Navigation Algorithm Using Fuzzy Control Method in Mobile Robotics

The issue of navigation methods is being continuously developed globally. The aim of this article is to test the fuzzy control algorithm for track finding in mobile robotics. The concept of an autonomous mobile robot EN20 has been designed to test its behaviour. The odometry navigation method was used. The benefits of fuzzy control are in the evidence of mobile robot’s behaviour. These benefits are obtained when more physical variables on the base of more input variables are controlled at the same time. In our case, there are two input variables - heading angle and distance, and two output variables - the angular velocity of the left and right wheel. The autonomous mobile robot is moving with human logic