Comparison of backstepping, sliding mode and PID regulators for a voltage inverter

<p><span>In the present paper, an efficient and performant nonlinear regulator is designed for the control of the pulse width modulation (PWM) voltage inverter that can be used in a standalone photovoltaic microgrid. The main objective of our control is to produce a sinusoidal voltage output signal with amplitude and frequency that are fixed by the reference signal for different loads including linear or nonlinear types. A comparative performance study of controllers based on linear and non-linear techniques such as backstepping, sliding mode, and proportional integral derivative (PID) is developed to ensure the best choice among these three types of controllers. The performance of the system is investigated and compared under various operating conditions by simulations in the MATLAB/Simulink environment to demonstrate the effectiveness of the control methods. Our investigation shows that the backstepping controller can give better performance than the sliding mode and PID controllers. The accuracy and efficiency of the proposed backstepping controller are verified experimentally in terms of tracking objectives.</span></p>

Practical Tracking Control Under Actuator Saturation for a Class of Flexible-Joint Robotic Manipulators Driven by DC Motors

This paper is devoted to the practical tracking control for a class of flexible-joint robotic manipulators driven by DC motors. Different from the related literature where control constraint is neglected and the disturbances are excluded or only exist in one subsystem, actuator saturation is considered in this paper while the disturbances are present in all the three subsystems. This leads to the incapability of the traditional schemes on this topic. For this, a novel control design scheme is proposed by skillfully incorporating adaptive dynamic compensation technique, constructive methods of command filters and an auxiliary system for the actuator saturation into the backstepping framework, and in turn to design a practical tracking controller which ensures that all the states of the resulting closed-loop system are bounded and the system output practically tracks the reference signal. It is worthwhile strengthening that a more wider class of reference signals can be tracked since they are only first order continuously differentiable but twice or more in the related literature. Finally, a numerical example is provided to validate the effectiveness of the proposed theoretical results.

SIMULATION OF A CLOSED SYSTEM OF A DC ELECTRIC DRIVE WITH A WIDTH-PULSE CONVERTER

This article investigates the regulation of the angular speed of an electric drive (ED) with a pulse-width converter (PWC) and a direct current motor (DC motor) of independent excitation (NV) when controlled in a closed-loop system. A proportional-integral (PI) -regulator was used as a regulator of the angular velocity. To analyze the processes in the closed-loop SHIP-DPT system, the methods of simulation are used. The principle of operation of an electric drive with control from a PWM is described. Developed and modeled EP circuits with PWM in the Matlab environment using blocks from the Simulink / SimPowerSystem library. A model block has been modeled that calculates the static and dynamic power losses of the PWP IGBT. To calculate the static and dynamic losses, the method of approximating the loss graphs was used. The obtained mathematical dependences describe quite accurately the graphs of the power losses of the IGBT transistor. It is shown that when using a PI-controller, the angular speed of the electric drive is set according to a given speed reference signal.

Fourier spotting: a novel setup for single-color reflectometry

Single-color reflectrometry is a sensitive and robust detection method in optical biosensor applications, for example for bioanalysis. It is based on the interference of reflected monochromatic radiation and is label free. We present a novel setup for single-color reflectometry based on the patented technology of Berner et al. from 2016. Tilting areas of micro-mirrors allow us to encode the optical reflection signal of an analyte and reference channel into a particular carrier frequency with the amplitude being proportional to the local reflection. Therefore, a single photodiode is sufficient to collect the signals from both channels simultaneously. A 180∘ phase shift in the tilt frequency of two calibrated micro-mirror areas leads to a superposition of the analyte and reference signal which enables an efficient reduction of the baseline offset and potential baseline offset drift. A performance test reveals that we are able to detect changes of the refractive index n down to Δn < 0.01 of saline solutions as regents. A further test validates the detection of heterogeneous binding interaction. This test compromises immobilized testosterone-bovine serum albumin on a three-dimensional layer of biopolymer as ligand and monoclonal anti-testosterone antibodies as analyte. Antibody/antigen binding induces a local growth of the biolayer and change in the refractive index, which is measured via the local change of the reflection. Reproducible measurements enable for the analysis of the binding kinetics by determining the affinity constant KA = 1.59 × 10− 7 M− 1. In summary, this work shows that the concept of differential Fourier spotting as novel setup for single-color reflectometry is suitable for reliable bioanalysis.

Design of a SIMO Deep Learning-Based Chaos Shift Keying (DLCSK) Communication System

This paper brings forward a Deep Learning (DL)-based Chaos Shift Keying (DLCSK) demodulation scheme to promote the capabilities of existing chaos-based wireless communication systems. In coherent Chaos Shift Keying (CSK) schemes, we need synchronization of chaotic sequences, which is still practically impossible in a disturbing environment. Moreover, the conventional Differential Chaos Shift Keying (DCSK) scheme has a drawback, that for each bit, half of the bit duration is spent sending non-information bearing reference samples. To deal with this drawback, a Long Short-Term Memory (LSTM)-based receiver is trained offline, using chaotic maps through a finite number of channel realizations, and then used for classifying online modulated signals. We presented that the proposed receiver can learn different chaotic maps and estimate channels implicitly, and then retrieves the transmitted messages without any need for chaos synchronization or reference signal transmissions. Simulation results for both the AWGN and Rayleigh fading channels show a remarkable BER performance improvement compared to the conventional DCSK scheme. The proposed DLCSK system will provide opportunities for a new class of receivers by leveraging the advantages of DL, such as effective serial and parallel connectivity. A Single Input Multiple Output (SIMO) architecture of the DLCSK receiver with excellent reliability is introduced to show its capabilities. The SIMO DLCSK benefits from a DL-based channel estimation approach, which makes this architecture simpler and more efficient for applications where channel estimation is problematic, such as massive MIMO, mmWave, and cloud-based communication systems.

Kalman Filter Implementation of Subglottal Impedance-Based Inverse Filtering to Estimate Glottal Airflow during Phonation

Subglottal Impedance-Based Inverse Filtering (IBIF) allows for the continuous, non-invasive estimation of glottal airflow from a surface accelerometer placed over the anterior neck skin below the larynx. It has been shown to be advantageous for the ambulatory monitoring of vocal function, specifically in the use of high-order statistics to understand long-term vocal behavior. However, during long-term ambulatory recordings over several days, conditions may drift from the laboratory environment where the IBIF parameters were initially estimated due to sensor positioning, skin attachment, or temperature, among other factors. Observation uncertainties and model mismatch may result in significant deviations in the glottal airflow estimates; unfortunately, they are very difficult to quantify in ambulatory conditions due to a lack of a reference signal. To address this issue, we propose a Kalman filter implementation of the IBIF filter, which allows for both estimating the model uncertainty and adapting the airflow estimates to correct for signal deviations. One-way analysis of variance (ANOVA) results from laboratory experiments using the Rainbow Passage indicate an improvement using the modified Kalman filter on amplitude-based measures for phonotraumatic vocal hyperfunction (PVH) subjects compared to the standard IBIF; the latter showing a statistically difference (p-value =0.02, F=4.1) with respect to a reference glottal volume velocity signal estimated from a single notch filter used here as ground-truth in this work. In contrast, maximum flow declination rates from subjects with vocal phonotrauma exhibit a small but statistically difference between the ground-truth signal and the modified Kalman filter when using one-way ANOVA (p-value =0.04, F=3.3). Other measures did not have significant differences with either the modified Kalman filter or IBIF compared to ground-truth, with the exception of H1-H2, whose performance deteriorates for both methods. Overall, both methods (modified Kalman filter and IBIF) show similar glottal airflow measures, with the advantage of the modified Kalman filter to improve amplitude estimation. Moreover, Kalman filter deviations from the IBIF output airflow might suggest a better representation of some fine details in the ground-truth glottal airflow signal. Other applications may take more advantage from the adaptation offered by the modified Kalman filter implementation.

Optimization of Low Site Density Area for 4G Network in Urban City

The development of telecommunications is currently growing rapidly, especially in urban areas. To obtain optimal data services for users, the performances of 4G network services must continue to be optimized. It is known that many users are scattered in urban areas, but sometimes it is not balanced with an even distribution of the site in this area. This condition occurs because the distribution of the site is not evenly optimal distributed, either due to licensing constraints, limited land access for site development, or in terms of plans that have not been made. Balanced with the requirement of a 4G network, which is required, this "empty space" condition or low site density condition must find a solution or optimize it. Many optimization methods can optimize the area with low site density possibility. This study will optimize the area by adding a new site proposal based on coverage planning. We need to analyze Reference Signal Received Power (RSRP) coverage signal distribution using Atoll Planning Software. After optimization, the RSRP level below or equal -80 dBm increased from 75.195% to 94.08%. Furthermore, the percentage calculation for inadequate coverage (below -80 dBm) decreased from 24.816% to 5.931%. This RSRP signal level also shows that the condition after optimization with a new site can improve the signal level condition from areas with low site density possibility.

Downlink Transmission And Channel Estimation For Cell-Free Massive MIMO-OFDM With Symbol Time Offset

In a cell-free massive MIMO system, multiple users arrive at multiple access points at separate times, while in an OFDM system, different delays can be equivalent to symbol timing offsets (STOs). Since symbol timing offsets are not all the same, in the downlink transmission process, it is necessary to consider its impact on transmission techniques, such as channel estimation and downlink precoding. In this paper, aiming at the performance loss caused by STO in cell-free massive MIMO-OFDM system, we propose a multi-RB precoding optimization algorithm that maximizes the downlink sum rate. We derive the sum rate maximization problem into an iterative second-order cone programming (SOCP) form to achieve convex approximation. Then, considering the impact of STO on the accuracy of cell-free massive MIMO-OFDM channel estimation, we propose a downlink channel estimation method, which jointly uses channel state information reference signal (CSI-RS) and demodulation reference signal (DMRS). Simulation results show that the proposed multi-RB optimal precoding can effectively improve the downlink sum rate, and the proposed downlink channel estimation can obtain accurate multi-RB frequency domain channel parameters.

Co-Channel Interference Suppression for LTE Passive Radar Based on Spatial Feature Cognition

Passive radars based on long-term evolution (LTE) signals suffer from sever interferences. The interferences are not only from the base station used as the illuminator of opportunity (BS-IoO), but also from the other co-channel base stations (CCBS) working at the same frequency with the BS-IoO. Because the reference signals of the co-channel interferences are difficult to obtain, cancellation performance degrades seriously when traditional interference suppression methods are applied in LTE-based passive radar. This paper proposes a cascaded cancellation method based on the spatial spectrum cognition of interference. It consists of several cancellation loops. In each loop, the spatial spectrum of strong interferences is first recognized by using the cyclostationary characteristic of LTE signal and the compressed sensing technique. A clean reference signal of each interference is then reconstructed according to the spatial spectrum previously obtained. With the reference signal, the interferences are cancelled. At the end of each loop, the energy of the interference residual is estimated. If the interference residual is still strong, then the cancellation loop continues; otherwise it terminates. The proposed method can get good cancellation performance with a small-sized antenna array. Theoretical and simulation results demonstrate the effectiveness of the proposed method.