DYNAMICS OF THE TEMPERATURE SENSOR OF THE «SMART HOME» HEATING SYSTEM

The article deals with the issues of modeling the control of room heating. The dynamics of the object-the heating system of a residential building-is obtained. The equation of the dynamics of the temperature sensor is derived. Dynamic errors are determined by the dynamic characteristics of the temperature sensor. The dynamic error is determined for a stepwise change in the input signal.

Stability and control of the nonlinear system for tractor with N trailer in the presence of slip

In many engineering systems, it is not enough to merge the system paths to zero at infinite time, but the speed of moving these paths to zero is very important. Estimating this speed can be done using exponential functions. This concept is used in exponential stability definition. The purpose of this paper is to design a controller for problem inputs and implement a system of a car with N to a trailer connected to it. This approach is based on the analysis of the Lyapunov stability method. In the given problem, the purpose of conducting and converging the system considering the slip phenomenon as a primitive uncertainty in the system is toward the desired point. Since the trailer tractor system has limitation constraints in the modeling structure, it is difficult to guarantee the stability of a non-holonomic system. Because no controller designed by the control feedback method can continuously and stable ensure the convergence of the system. If this possibility almost dynamic errors, even adaptive controls do not versatile with the operation of the Lyapunov function, especially in the presence of uncertainties, which is a very important factor in system instability, which requires the development of controllers designed to deal with these disturbances. In the simulated results, this paper not only examines the convergence properties, but also shows the ability to control the system by designing a controller in the presence of a slip phenomenon to strengthen the system in the stability debate.

About the dynamic error of strain gauge torque measuring devices

The dynamic error of devices belongs to the number of errors that are difficult to estimate. The mechanism for forming this error on the example of torsional torque dynamometersis briefly considered as the most common in the practice of research on the energy of agricultural machines. The limiting ratios of frequencies of external influences and natural vibrations of strain-measuring devices are given. Recommendations are made to reduce dynamic error in torque strain analysis. The present review and the accumulated experience of strain gauge research allows us to recommend some directions for reducing dynamic errors in torque measurements. In order for a strain gauge to keep up with changes in torque in its inertial characteristics, it must have the smallest torque inertia. In order to reduce the probability of high-frequency harmonics from the elastic vibrations of the strain gauge, it must be sufficiently rigid. From this point of view, strain rods, strain sprockets, etc., having a moment of inertia greater than that of the same gear parts, are irrational. Based on modern micromodules and power supplies, the system can have a small mass and have no significant effect on the inertial characteristic of the strain gauge.

Photoplethysmography Analysis with Duffing–Holmes Self-Synchronization Dynamic Errors and 1D CNN-Based Classifier for Upper Extremity Vascular Disease Screening

Common upper limb peripheral artery diseases (PADs) are atherosclerosis, embolic diseases, and systemic diseases, which are often asymptomatic, and the narrowed arteries (stenosis) will gradually reduce blood flow in the right or left upper limbs. Upper extremity vascular disease (UEVD) and atherosclerosis are high-risk PADs for patients with Type 2 diabetes or with both diabetes and end-stage renal disease. For early UEVD detection, a fingertip-based, toe-based, or wrist-based photoplethysmography (PPG) tool is a simple and noninvasive measurement system for vital sign monitoring and healthcare applications. Based on time-domain PPG analysis, a Duffing–Holmes system with a master system and a slave system is used to extract self-synchronization dynamic errors, which can track the differences in PPG morphology (in amplitudes (systolic peak) and time delay (systolic peak to diastolic peak)) between healthy subjects and PAD patients. In the preliminary analysis, the self-synchronization dynamic errors can be used to evaluate risk levels based on the reflection index (RI), which includes normal condition, lower PAD, and higher PAD. Then, a one-dimensional convolutional neural network is established as a multilayer classifier for automatic UEVD screening. The experimental results indicated that the self-synchronization dynamic errors have a positive correlation with the RI (R2 = 0.6694). The K-fold cross-validation is used to verify the performance of the proposed classifier with recall (%), precision (%), accuracy (%), and F1 score.

Soil Salinization Level Monitoring and Classifying by Mixed Chaotic Systems

Soil salinization process is a complex non-linear dynamic evolution. To classify a system with this type of non-linear characteristic, this study proposed a mixed master/slave chaotic system based on Chua’s circuit and a fractional-order Chen-Lee chaotic system to classify soil salinization level. The subject is the soil in Xinjiang with different levels of human interference. A fractional-order Chen-Lee chaotic system was constructed, and the spectral signal processed by the Chua’s non-linear circuit was substituted into the master/slave chaotic system. The chaotic dynamic errors with different fractional orders were calculated. The comparative analysis showed that 0.1-order has the largest chaotic dynamic error change, which produced two distinct and divergent results. Thus, this study converted the chaotic dynamic errors of fractional 0.1-order into chaotic attractors to build an extension matter-element model. Finally, we compared the soil salt contents (SSC) from the laboratory chemical analysis with the results of the extension theory classification. The comparison showed that the combination of fractional order mixed master/slave chaotic system and extension theory has high classification accuracy for soil salinization level. The results of this system match the result of the chemical analysis. The classification accuracy of the calibration set data was 100%, and the classification accuracy of the validation set data was 90%. This method is the first use of the mixed master/slave chaotic system in this field and can satisfy certain soil salinization monitoring needs as well as promote the application of the chaotic system in soil salinization monitoring.

Simulation of a heating automation system for a «smart» residential building

The article deals with the issues of constructive, structural modeling and automatic control of room heating. The dynamics of the object-the heating system of a residential building-is obtained. Dynamic errors are determined by the dynamic characteristics of the temperature sensor. The design scheme of the object is presented. The heating control system contains three temperature controllers. Using structural modeling, various methods of automatic control of the heating system are evaluated. The technical structure of the automatic temperature control system (ACS) in a residential building is implemented by a cascade three-circuit control with two executive elements. Experimental studies of transients in a closed ACS with three types of regulators are presented. The results obtained make it possible to implement adaptive control of the heating system on a real object.

Dynamic error of multiaxis machine tools considering position dependent structural dynamics and axis coupling inertial forces

During the working process of high-speed multiaxis machine tools, inertial forces can cause vibration and deformation of mechanical structure, which lead to the dynamic error of tool center point (TCP) relative to worktable and can adversely affect the machining performance. Considering the varying feed positions and accelerations during machining, a parameter-varying multi-rigid-body dynamic model of a 3-axis gantry machine tool is proposed. This model represents the position dependent structural dynamics and inertial forces, which can simulate the dynamic error of TCP relative to worktable within the entire workspace. The results show that the dynamic error in one direction is affected by the feed motions of multiple feed axes. The magnitudes of the dynamic error significantly vary with the position of Z-axis. And the dynamic errors in Y- and Z-direction show different varying trends. Then the theoretical model is used to discuss the dynamic error and position dependency. The expressions of TCP dynamic response and inertial forces reveal the reason why the dynamic errors in Y- and Z-direction show different varying trends.