Single-input Single-output Systems Research Articles

Harnessing the power of ML for robust SISO and MIMO FSO communication systems in fog weather

This study examines Free Space Optical (FSO) communication’s performance in different fog conditions, focusing on Single-Input Single-Output (SISO) and Multiple-Input Multiple-Output (MIMO) setups. In low fog, SISO handles signal degradation well. MIMO improves link robustness in moderate fog. High fog challenges traditional FSO, leading to ML integration to optimize communication parameters. For weather channel classification, a preprocessing scheme reduces features from 12 to 2 given that the 12 features are Bit Error Rate (BER), Quality Factor (Q-factor) and Received Optical Power (ROP) for different 4 users. A Gaussian Process Classifier (GPC) achieves an accuracy greater than 99%, surpassing SVM, Decision Tree, and Random Forest. GPC’s fit and predict functions execute in 0.15 s, outperforming NuSVM (0.2 s). This study highlights FSO, SISO, MIMO, and Machine Learning (ML) practicality in enhancing communication resilience in adverse weather, especially in fog-prone areas.

Online learning of stable robust adaptive controllers design based on data-dependent feedback linearization with application to rotary inverted pendulum

AbstractThis study introduces an online (supervised) learning method to design nonlinear auto-regressive moving average (NARMA) controllers for feedback-linearized nonlinear single-input single-output (SISO) systems. The algorithm ensures Schur stability of the overall closed-loop system and provides adaptiveness and robustness for the NARMA controllers. The first stage of the method derives, in a data-dependent way, a feedback-linearized model of the nonlinear plant by using its input and output sample pairs. The method’s second stage, which constitutes the novel part of the presented study, builds up an online learning scheme for the linear auto-regressive moving average (ARMA) controller based on an already learned feedback-linearized model of the nonlinear plant. During online supervised learning, ARMA parameters of the feedback-linearized SISO plant model and the closed-loop ARMA model are computed by minimizing the plant identification and the closed-loop system tracking errors. Both errors are defined as $${{\ell}}_{1,{\varvec{\varepsilon}}}$$ ℓ 1 , ε , namely ε-insensitive loss functions that provide NARMA controller the robustness against noise and outliers. The proposed online learning control algorithm is applied to a rotary inverted pendulum model and to a real rotary inverted pendulum setup. The tracking performance of the developed controller is compared with those of the linear quadratic regulator and coupled sliding mode controller in terms of mean square error.

Closed-Form Global Optimization of Beyond Diagonal Reconfigurable Intelligent Surfaces

Reconfigurable intelligent surfaces (RISs) allow controlling the propagation environment in wireless networks by tuning multiple reflecting elements. RISs have been traditionally realized through single connected architectures, mathematically characterized by a diagonal scattering matrix. Recently, beyond diagonal RISs (BD-RISs) have been proposed as a novel branch of RISs whose scattering matrix is not limited to be diagonal, which creates new benefits and opportunities for RISs. Efficient BD-RIS architectures have been realized based on group and fully connected reconfigurable impedance networks. However, a closed-form solution for the global optimal scattering matrix of these architectures is not yet available. In this paper, we provide such a closed-form solution proving that the theoretical performance upper bounds can be exactly achieved for any channel realization. We first consider the received signal power maximization in single-user single-input single-output (SISO) systems aided by a BD-RIS working in reflective or transmissive mode. Then, we extend our solution to single-user multiple-input multiple-output (MIMO) and multi-user multiple-input single-output (MISO) systems. We show that our algorithm is less complex than the iterative optimization algorithms employed in the previous literature. The complexity of our algorithm grows linearly (resp. cubically) with the number of RIS elements in the case of group (resp. fully) connected architectures.

Single input-single output coupled resonators with nonlinear self-excitation for multiple mass sensing

A theoretical formulation and an experimental investigation into multiple mass sensing using self-excited coupled resonators is discussed. To construct a single input-single output (SISO) system, multiple resonators with different natural frequencies (frequency-mistuned resonators) are connected to a common shuttle mass, with resonators individually functionalized to absorb a specific analyte/mass. To measure the natural frequency shift of each resonator, we propose using the response frequency in the shuttle mass under the self-excitation, rather than the peak of the frequency response to the external harmonic excitation. Consequently, the method is applicable even in viscous environments where the frequency response curve does not exhibit a clear peak. The application of velocity feedback compensates for viscosity and selectively produces the self-excited oscillation, with one of the eigenfrequencies of the overall system corresponding to the natural frequency of the resonator absorbing the target analyte with the aid of band-pass filter. From the shift of the eigenfrequency corresponding to each resonator, changes in the masses absorbed to that resonator can be identified. A discrete mathematical model for the proposed sensing system is formulated and a nonlinear analysis was carried out to theoretically validate the control method. Furthermore, additional nonlinear feedback was introduced to prevent the infinite growth of the self-excited oscillation by ensuring that the sensing system behaves as a van der Pol oscillator. We experimentally investigated the efficiency of the method using a simple macro-scale apparatus with two resonators connected to a shuttle mass.

Retracted: Single-Input Single-Output System with Multiple Time Delay PID Control Methods for UAV Cluster Multiagent Systems

Retracted: Single-Input Single-Output System with Multiple Time Delay PID Control Methods for UAV Cluster Multiagent Systems

Achievable Spectral Efficiency of Line-of-Sight MIMO Fixed Links with Compact Planar Antenna Arrays and Power Amplifier Limitations

Fixed Point-to-Point microwave wireless systems with high spectral efficiency are needed to meet the pervasive and increasing demand for capacity in back-haul networks of mobile radio systems. In this context, spatially multiplexed LoS-MIMO (Line-of-Sight Multiple Input Multiple Output) systems have been studied for about twenty years, particularly in the millimeter wave frequency bands (above 15 GHz). However, their deployment in real networks has been really limited, to the authors’ knowledge. This has been due to several factors, i.e. the practical possibility of using extremely high-level modulation formats (nowadays up to 8192-QAM), the joint use of co-channel dual polarization, and the availability of wider channel bands in the new high frequency ranges (e.g. E-Band). In addition, a crucial reason has been the difficulty of installing multiple antennas spaced apart in order to maximize the MIMO spatial multiplexing so providing the maximum capacity gain. This optimal antenna separation, even for the classical MIMO M×N\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$M \ imes N$$\\end{document} with M = 2 antennas at the receiver and N = 2 antennas at the transmitter, can be several meters, e.g. 5.71 m at 23 GHz on a 5 km link. In this article, we analyze the performance of LoS-MIMO systems where antenna separation is highly sub-optimal, for limiting the array size, and a satisfactory performance is made possible by the exploitation of specific bit loading and power allocation strategies and the setting of the working region of the RF transmitter power amplifiers to operate at a given Signal-to-Inter Modulation Distortion Ratio (SIMDR). The result is an overview of the advantages and drawbacks of compact LoS-MIMO from a wider perspective than in the existing literature, including fundamental aspects for the practical implementation of these systems. Performance is discussed in many cases of interest and compared with the state of the art SISO (Single Input Single Output) system.

Performance Evaluation of Maximum Ratio Combining Diversity Technology and Traditional System Based on Comprehensive Noise Analysis in Underwater Wireless Optical Communication

The maximum ratio combining (MRC) diversity technology has shown outstanding performance in overcoming the adverse effects of underwater wireless optical communication (UWOC) systems. However, its actual performance gain will be affected by the detection area and noise, which requires an in-depth analysis. In this paper, on the basis of fully considering the noises in the UWOC system, the performance of the MRC diversity technology is fairly and comprehensively studied by comparing it with two single-input–single-output (SISO) systems using a small aperture detection (SAD) scheme or a large-aperture detection (LAD) scheme through a Monte Carlo simulation and a formula analysis. The results show that the traditional belief that the MRC diversity scheme has consistently outperformed SISO systems may be misleading. When the thermal noise is dominant and the background noise is small, the LAD scheme performs better than the MRC diversity scheme with the same detection area. And in other cases, the MRC diversity scheme with the same detection area is always superior to the SISO systems. The conclusions obtained in this paper have a guiding significance for the practical application of UWOC.

A Decoupling Control Method for Converting DIDO Sequence Admittance Model of Grid-Tied Converter System Into SISO

This paper proposes a decoupling control method to eliminate frequency coupling in three-phase grid-tied system. Firstly, the admittance model of three-phase <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LCL</i> -type three-phase grid-tied converter (GTC) considering DC-bus voltage control (DVC) loop and phase-locked loop (PLL) is established in <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dq</i> -domain frame, and the influence of asymmetrical DVC and PLL control structure on frequency coupling oscillation is analyzed. Then decoupling factors are added to the DVC loop and current control (CC) loop to achieve that the off-diagonal elements of the sequence admittance matrix of the GTC are 0, which means the frequency coupling in the GTC is eliminated. Therefore, the GTC system can be regarded as a single input single output (SISO) system, and the stability can be analyzed by the classic Nyquist criterion in the sequence-domain frame. Compared with the double input double output (DIDO) system, the resulted SISO system convenient for calculating the stability margin of the system and guiding parameter design. In addition, the SISO system is easier to be analyzed on the oscillation and resonance mechanism, and the analysis results can be used to optimize the design of the converter controller, grid planning and operation. Finally, simulation and experiment verify the feasibility and effectiveness of the proposed decoupling control method.

Theoretical Model and Experiments of Focused Phased Array for Cross-Medium Communication in Misaligned Transmitter/Receiver Scenarios

Direct communication across the water-air interface has attracted wide attention because of its potential applications in integrated air-sea networking. In this article, three different cross-medium communication systems have been proposed, including line-of-sight (LOS) optical links, laser-induced acoustic (LIA) systems, and translational acoustic radio frequency (TARF) systems. However, LOS optical links are sensitive to turbid water, misalignment of the transmitters/receivers, and the influence of surface waves. LIA systems are unstable with poor repeatability. TARF systems require the alignment of transmitters/receivers. Moreover, in situations where the location of detection points is required to be frequently moved for flexible communication, LOS optical links, and TARF systems both failed. This article proposes a cross-medium focused phased array (CMFPA) model, which is a multiple-input single-output system, to enlarge the detection area and increase the overall wave amplitude at the water surface. Theoretical analyses and experimental results indicate that the CMFPA can relax the requirement of precise alignment between communication nodes and improve performance in cross-medium communication when compared to a single-input single-output system. The study is expected to provide a foundation for cross-medium communication between underwater and airborne nodes in misaligned transmitters/receivers scenarios.

A low-complexity algorithm based on variational Bayesian inference for MIMO channel estimation

With an increase in the number of transmitters in multiple-input multiple-output (MIMO) communication systems, there is a cubic rise in the computational complexity of the traditional sparse Bayesian learning (SBL) channel estimation algorithm. While various algorithms are effective for single-input single-output (SISO) systems, they are not suitable for the MIMO scenario. This paper introduces a MIMO channel estimation algorithm based on variational Bayesian inference (VBI) by assuming the independence of the variational distribution among different channels. The high-dimensional channel vectors estimated in the conventional MIMO-SBL algorithm are decomposed into multiple parallel low-dimensional channel vectors with different sparsity using VBI. Consequently, the complexity exhibits a linear relationship with the number of transmitters, as demonstrated through numerical analysis. Simulations confirm the improved estimation accuracy of the MIMO-VBI algorithm. Experimental results reveal that MIMO systems can achieve lower bit error rates using the MIMO-VBI algorithm, with reduced runtime for channel lengths exceeding 100 symbols.

Disturbance Observer-Based Terminal Sliding Mode Tracking Control for a Class of Nonlinear SISO Systems with Input Saturation

This paper focuses on the trajectory tracking control for general nonlinear single-input single-output (SISO) systems in which the output is not directly related to the control input. To address the tracking problem with the consideration of possible model uncertainty, external disturbance, and control input saturation, we employ the input-output feedback linearization technique and design a finite-time disturbance observer-based terminal sliding mode controller to improve the tracking performance and enhance the robustness. The stability analysis is carried out by using the Lyapunov method. To alleviate the chattering while achieving an acceptable control performance, a boundary layer method is adopted for the trade-off between the high-frequency control actions and the bounded unavoidable nonzero steady-state error. The proposed method is evaluated on the two typical nonlinear systems, which are fully linearizable and partially linearizable, respectively, and compared to the state-of-the-art method in terms of tracking and robustness through comprehensive numerical simulations. The results show that the proposed method not only renders the estimated disturbance error tends to be zero in finite time, but also has superiority in the fast reaction to disturbance and small tracking error without high-frequency chattering.

Forward Action to Stabilize multiple Time-Delays MIMO Systems

In this paper, the problem of closed-loop stability of linear time-invariant systems with multiple time-delays is studied. We prove that stability of closed-loop configurations of such systems with unitary feedback can be guaranteed by means of a forward control action. The case of single-input single-output (SISO) systems is first considered, and then, an extension to the more general case of multi-input multi-output (MIMO) systems with multiple time-delays is dealt with. Numerical examples illustrating the theoretical results are also discussed.

Nonlinear Dynamic Response of Nanocomposite Microbeams Array for Multiple Mass Sensing.

A nonlinear MEMS multimass sensor is numerically investigated, designed as a single input-single output (SISO) system consisting of an array of nonlinear microcantilevers clamped to a shuttle mass which, in turn, is constrained by a linear spring and a dashpot. The microcantilevers are made of a nanostructured material, a polymeric hosting matrix reinforced by aligned carbon nanotubes (CNT). The linear as well as the nonlinear detection capabilities of the device are explored by computing the shifts of the frequency response peaks caused by the mass deposition onto one or more microcantilever tips. The frequency response curves of the device are obtained by a pathfollowing algorithm applied to the reduced-order model of the system. The microcantilevers are described by a nonlinear Euler-Bernoulli inextensible beam theory, which is enriched by a meso-scale constitutive law of the nanocomposite. In particular, the microcantilever constitutive law depends on the CNT volume fraction suitably used for each cantilever to tune the frequency bandwidth of the whole device. Through an extensive numerical campaign, the mass sensor sensitivity estimated in the linear and nonlinear dynamic range shows that, for relatively large displacements, the accuracy of the added mass detectability can be improved due to the larger nonlinear frequency shifts at resonance (up to 12%).

Application of Elliptic Jerk Motion Profile to Cartesian Space Position Control of a Serial Robot

The paper discusses the application of a motion profile with an elliptic jerk to Cartesian space position control of serial robots. This motion profile is obtained by means of a kinematic approach, starting from the jerk profile and then calculating acceleration, velocity and position by successive integrations. Until now, this profile has been compared to other motion laws (trapezoidal velocity, trapezoidal acceleration, cycloidal, sinusoidal jerk, modified sinusoidal jerk) considering single-input single-output systems. In this work, the comparison is extended to nonlinear multi-input multi-output systems, investigating the application to Cartesian space position control of serial robots. As case study, a 4-DOF SCARA-like architecture with elastic balancing is considered; both an integer-order and a fractional-order controller are applied. Multibody simulation results show that, independently of the controller, the behavior of the robot using the elliptic jerk profile is similar to the case of adopting the sinusoidal jerk and modified sinusoidal jerk laws, but with a slight reduction in the position error (−3.8% with respect to the sinusoidal jerk law and −0.8% with respect to the modified sinusoidal jerk law in terms of Integral Square Error) and of the control effort (−8.2% with respect to the sinusoidal jerk law and −1.3% with respect to the modified sinusoidal jerk law in terms of Integral Control Effort).

Computer-Aided Design, Multibody Dynamic Modeling, and Motion Control Analysis of a Quadcopter System for Delivery Applications

This paper elaborates on the modeling and control of an Unmanned Aerial Vehicle (UAV) for delivery purposes, thereby integrating computer-aided design, multibody dynamic modeling, and motion control analysis in a unified framework. The UAV system designed in this study and utilized for item delivery has a quadcopter structure composed of four arms connected to a central trunk. In this investigation, the proposed design of the delivery drone is systematically modeled employing the multibody approach, while SIMSCAPE MULTIBODY is the software used for performing the dynamic analysis and for devising the final design of the control system. To this end, starting from the CAD model designed using SOLIDWORKS, the control system of the quadcopter is developed by performing dynamic simulations in the MATLAB/SIMULINK environment. Additionally, another fundamental contribution of this paper is the analytical derivation of the nonlinear set of algebraic constraint equations peculiar to the present multibody system, which characterizes the kinematics of the delivery drone and describes the relative angular velocity imposed between two rigid bodies as nonholonomic constraints. Furthermore, as discussed in detail in this paper, the choice of the propulsion system and the design of the individual components heavily depends on the structural and functional needs of the UAV under study. On the other hand, the control system devised in this work is based on cascaded Proportional-Integral-Derivative (PID) controllers, which are suitable for achieving different maneuvers that are fundamental for the motion control of the delivery drone. Therefore, the final performance of the UAV system is a consequence of the regulation of the feedback parameters that characterize the PID controllers. In this respect, the paper presents the refining of the parameters characterizing the PID controllers by using both an internal MATLAB tool, which automatically tunes the controller gains of single-input single-output systems, and by observing the resulting transient behavior of the UAV system, which is obtained through extensive dynamical simulations. The set of numerical results found in this investigation demonstrates the high performance of the dynamical behavior of the UAV system designed in this work.

Synthesizing an adaptive control Singleinput-Singleoutput system for unstable and deterministic chaotic processes

The paper proposes a solution to the problem of synthesizing an adaptive control system from a reference model with the desired dynamics of unstable and deterministic chaotic processes in the class of “dovetail” catastrophes for single input-single output objects. The task of selecting a reference model with the desired dynamics, the synthesis of the main circuit, and the adaptation circuit are solved by the gradient-speed method of the Lyapunov vector functions. From the conditions of aperiodic robust stability of the reference model with the desired dynamics, the main control loop, and the generalized tunable object, tunable coefficients are calculated, and the control goal is achieved.

Unified gain formula for control diagrams with matrix-based transfer functions

The conventional Mason’s gain formula is limited to single-input single-output (SISO) systems and is inadequate for coupled multi-input multi-output (MIMO) systems as it does not consider matrix operations. To fill this gap, this paper introduces a novel unified gain formula for control diagrams with matrix-based transfer functions. The formula is developed using partitioned matrix theory and feature extraction methods. Applying the partitioned matrix concept, the transfer function between any input and output of three type control diagrams is derived. A unified gain formula for input u to output y of the control diagram is then proposed based on feature extraction. Subsequently, the unified gain formula for any input and output of the control system is proposed based on the deduced equivalent relationship between the original and moved disturbance input nodes. Lastly, case studies demonstrate the effectiveness of the proposed unified gain formula, verifying its potential for use in both SISO and MIMO systems.

A convex optimization approach to multi-objective design of two-stage compensators for MIMO linear systems

The previous design of two-stage compensators with multi-objectives concerns the closed-loop stability, the low-sensitivity, and the satisfactory time-domain performance. However, the design only considers the single-input single-output system. This paper aims to present the design of two-stage compensators for multi-input multi-output (MIMO) linear systems which contain dynamical interaction between inputs and outputs. When Youla parameterization is applied to the MIMO linear system, the design criteria can be cast as a nonlinear optimization. In addition, the infinite dimension optimization problem is approximated to a finite dimension problem with Ritz approximation. The suitable form of design parameters is proposed to ensure the low sensitivity of the MIMO system. The two-stage compensator design is formulated as convex optimization which is efficiently solved using available solvers. Finally, the two-stage compensators are designed for Wood and Berry’s model of binary distillation column. The numerical results indicate that all design objectives of frequency domain and time domain can be achieved by the two-stage compensators.

Delayed-based controller for fully actuated systems

In this work, a new control structure for fully actuated systems that solve the regulation and tracking of trajectories problem is proposed. This controller stands out for its ease of implementation and its ability to attenuate disturbances caused by parametric uncertainties and external forces. The control structure is based on the estimation of the delayed disturbances. Then, the current disturbance is canceled with the delayed disturbance, via the control input. The way in which the dynamics of the system is affected by the residual of these disturbances is analyzed. Also, the necessary conditions for establishing a reduced overshoot, settling time, and an attenuation factor of the disturbance are obtained. The performance of the proposed control structure is illustrated numerically by analyzing the behavior of different second-order single-input–single-output systems and also in the case of a RR-type robot. The control structure was also experimentally implemented in the case of a birotor type drone.

A Brief Review of Massive MIMO Technology for the Next Generation

Massive Multiple Input Multiple Output (MIMO) is an evolving technology based on the principle of spatial multiplexing winch consisting in using at the same time the same radio frequencies to send different signals. The several transmitting antennas from a base station can transmit different signals and several receiving antennas from a device can receive and divide them simultaneously. Due to the physically difficult of installing antennas close to each other, standard MIMO networks generally limit four antenna-side transmitters and receivers for data transmission while it could be more. The study aims to review the traditional MIMO different types as well as investigates the SNR between Single Input Single Output (SISO) and MIMO to ensure the best wireless connection functionality. In addition to that, a simple comparison to distinguish between SISO, SIMO, MISO, and MIMO in term of capacity and data rate to provide an indication for the quality of the wireless connection. The work's contribution is to illustrate technological benefits like MIMO, which boosts data speeds and increases the reliability of wireless networks. The outcome shows a SISO system would have a lower data rate than other systems because it only has one antenna at the transmitter and receiver, whereas a MISO system would typically have a greater Signal-to-Noise Ratio (SNR) than a SISO or SIMO system because it uses several transmit antennas. MIMO, however, took advantage of all the positive characteristics and emerged as the best solution overall.