Single-input Single-output Research Articles

Photonic-aided W-band dual-vector RF signal generation and detection enabled by bandpass delta-sigma modulation and heterodyne detection.

We propose a photonic-aided dual-vector radio-frequency (RF) signal generation and detection scheme enabled by bandpass delta-sigma modulation and heterodyne detection. With the aid of the bandpass delta-sigma modulation, our proposed scheme is transparent to the modulation format of the dual-vector RF signals and can support the generation, wireless transmission, and detection of both single-carrier (SC) and orthogonal-frequency-division-multiplexing (OFDM) vector RF signals with high-level quadrature-amplitude-modulation (QAM) modulation. With the aid of the heterodyne detection, our proposed scheme can support up to W-band (75-110 GHz) dual-vector RF signal generation and detection. For the validation of our proposed scheme, we experimentally demonstrate the simultaneous generation of a SC-64QAM signal at 94.5 GHz and a SC-128QAM signal at 93.5 GHz and their error-free high-fidelity transmission over a 20-km single-mode fiber 28 (SMF-28) and a 1-m single-input single-output (SISO) wireless link at the W-band. To the best of our knowledge, this is the first time that delta-sigma modulation has been introduced into a W-band photonic-aided fiber-wireless integration system to achieve flexible and high-fidelity dual-vector RF signal generation and detection.

On the zeros of three-DoF damped flexible systems

This paper presents an investigation of the non-minimum phase (NMP) zeros in the single input single output (SISO) transfer function of three-DoF (degrees of freedom) damped flexible linear time-invariant (LTI) systems under the assumption of classical damping. It is well-known that when all the modal residue signs of any multi-DoF damped flexible LTI system are the same, NMP zeros never occur in the system dynamics for any value of system parameters including modal residue, modal frequency and modal damping ratio. However, when all the modal residue signs are not the same, then additional conditions in terms of the system parameters are required to guarantee the elimination of NMP zeros. In this paper, the zero loci of a three-DoF damped flexible LTI system are developed to derive the sufficient and necessary conditions for the elimination of all NMP zeros. These conditions can be employed in the robust physical design of flexible systems, i.e., as long as these conditions are satisfied, the elimination of NMP zeros is guaranteed even when the system parameters undergo variations.

DISCRETE-TIME MODEL-BASED SLIDING MODE CONTROLLERS FOR TOWER CRANE SYSTEMS

This paper applies three classical and very popular discrete-time model-based sliding mode controllers, namely the Furuta controller, the Gao controller, and the quasi-relay controller due to Milosavljević, to the position control of tower crane systems. Three single input-single output (SISO) control systems are considered, for cart position control, arm angular position control and payload position control, and separate SISO controllers are designed in each control system. Experimental results are included to support the comparison of the three plus three plus three sliding mode controllers.

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.

Performance Analysis of RIS-Assisted Communications With Element Grouping and Spatial Correlation

We investigate the performance of a reconfigurable intelligent surface (RIS) assisted single-input single-output (SISO) communication system where RIS elements are narrowly spaced so that the channels between the RIS elements and receiver are spatially correlated. Adjacent RIS elements are grouped together to reduce the channel estimation overhead. The statistical properties of the optimal received SNR are analytically derived and these are used to characterize the coverage probability of the system. An analytical upper bound for the average achievable rate is also derived. This analysis provides insight into the impact of the grouping strategy and element spatial channel correlation level on the coverage probability and the achievable rate of the system. Numerical results validate the tightness of the closed-form expressions. Our results show that the average achievable rate for a given group size is higher for the spatially correlated RIS elements as compared to the uncorrelated configuration.

Time-delay metric for TDE of SISO delay systems

The time-delay intrinsic in the time series sampled from dynamic systems results in the chaotic correspondence between the elements of the time series. Therefore, accurate estimation of the time-delay is essential in time series-based tasks. In this paper, we propose two time-delay metrics for time-delay estimation (TDE) of single-input single-output (SISO) delay systems with unknown structures. The two proposed metrics are based on the ellipse shape ratio (ESR) and called the linear ellipse shape ratio (LESR), and the nonlinear ellipse shape ratio (NESR). In the devised TDE process employing the proposed metrics, an iteratively updated ellipse is used to filter out the outliers from the system input and output samples. Simulation experiments confirm the efficiency of the proposed time-delay metrics.

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 New Approach to Nonlinear State Observation for Affine Control Dynamical Systems

In this work, a Nonlinear Higher Order Extended State Observer (NHOESO) is presented to replace the Linear Extended State Observer (LESO) used in Conventional Active Disturbance Rejection Control (C-ADRC) solutions. In the NHOESO, the standard LESO is completed with a two-term smooth nonlinear function with saturation-like characteristics. The proposed novel NHOESO enables precise observation of the generalized disturbances with higher-order derivatives. The stability of the NHOESO is examined with the aid of the Lyapunov method. A simulation of an uncertain nonlinear Single-Input–Single-Output (SISO) system with time-varying external disturbances confirms that the proposed NHOESO copes well with the generalized disturbance, which is not true for other ESOs.

Dynamic data reconciliation to enhance the performance of model free adaptive control

As a novel data-driven control method, model-free adaptive control (MFAC) has a high requirement for the accuracy of the feedback signal. However, the sensor used to obtain the output inevitably contains measurement noise due to its own error or external interference, which may lead to an adverse effect on the control performance. The dynamic data reconciliation (DDR) is proposed and combined with MFAC to improve the control performance in this paper, which uses predicted output and measured data to suppress measurement noise considering Gaussian and non-Gaussian distributed measurement noise. The effectiveness of the DDR combined with MFAC (DDR-MFAC) is illustrated in the single-input single-output and multiple-input multiple-output systems with Gaussian and non-Gaussian distributed measurement noise. DDR-MFAC is also successfully applied to DC–AC converter, which improves its conversion precision.

An Enhanced Interference Alignment Strategy With MIL Criterion and RCG Algorithm for IRS-Assisted Multiuser MIMO

An enhanced interference alignment strategy with minimum interference leakage (MIL) criterion and Riemannian conjugate gradient (RCG) algorithm is proposed for intelligent reflecting surface (IRS)-assisted multiuser multiple-input multiple-output (MIMO). In this letter, the maximum sum rate is formulated as the optimization objective, with alternate optimization of phase shift vector at IRS as well as precoding and interference suppression vectors at transceivers respectively. MIL interference alignment criterion is used to iteratively solve the precoding vector and the interference suppression vector via channel reciprocity property. RCG algorithm is further applied to derive the IRS phase shift vector and maximize sum rate with the condition of ensuring a given minimum interference leakage threshold to eliminate system interference. Simulation results reveal that the proposed strategy effectively enhances sum rate performance compared with the scheme using random IRS phase shift vector and random precoding/interference suppression vectors as well as “AP + RCG” scheme in IRS-assisted multiuser single-input single-output (SISO) scenario. In addition, compared with “MMSE + RCG” strategy in the case of same multi-antenna transceiver pairs and antenna numbers, the proposed strategy could make a tradeoff between sum rate performance and computational complexity.

Outage Performance and AoI Minimization of HARQ-IR-RIS Aided IoT Networks

In this paper, reconfigurable intelligent surface (RIS) and hybrid automatic repeat request with incremental redundancy (HARQ-IR) are amalgamated to lower power expenditure, shorten latency and strengthen reliability of the internet of things (IoT) communications. By considering Rician fading channels and multiple RISs, the outage probability of single-input single-output (SISO) HARQ-IR-RIS aided IoT networks is derived in closed-form, with which the asymptotic outage analysis is carried out. The asymptotic results are further extended to single-input multiple-output (SIMO)/multiple-input multiple-output (MIMO) HARQ-IR-RIS aided IoT networks by using random matrix theory. Thereafter, the asymptotic expressions are invoked to reduce the design complexity of the phase shifts, transmit powers, and rate, which aims at minimizing the age of information (AoI) while ensuring the power and outage constraints. Particularly, the optimal phase shifts are firstly determined. The alternating optimization technique is then applied to solve the transmit rate and powers, which are iteratively updated based on majorization-minimization (MM) principle and geometric programming (GP) approximation, respectively. The numerical results consequently corroborate our theoretical analysis. More interestingly, the HARQ-IR-aided scheme with fixed power is found to provide a comparable performance as the proposed scheme with variable power especially for numerous reflecting elements at RIS.

Robust Fixed-Order Controller Design for Uncertain Systems With Generalized Common Lyapunov Strictly Positive Realness Characterization

This article investigates the design of a robust fixed-order controller for single-input–single-output (SISO) polytopic systems with interval uncertainties, with the aim that the closed-loop stability is appropriately ensured and the performance specifications on sensitivity shaping are conformed in a specific finite frequency range. Utilizing the notion of generalized common Lyapunov strictly positive realness (CL-SPRness), the equivalence between strictly positive realness (SPRness) and strictly bounded realness (SBRness) is established; and then, the specifications on robust stability and performance are transformed into the SPRness of newly constructed systems and further characterized in the framework of linear matrix inequality (LMI) conditions. The proposed methodology avoids the tedious yet mandatory evaluations of the specifications on all vertices of the uncertain polytopic system in an explicit form. Instead, solving five LMIs exclusively suffices for ensuring the robust stability and performance regardless of the number of vertices, and thus, the typically heavy computational burden is considerably alleviated. It is also noteworthy that the proposed methodology additionally provides the necessary and sufficient conditions for this robust controller design with the consideration of a prescribed finite frequency range, and therefore, significantly less conservatism is attained in the system performance.

Soft Sensor Design via Switching Observers.

The goal of the paper is the design of soft sensors for single input single output (SISO) nonlinear processes. This goal is of essential importance for process monitoring, fault detection and fault isolation. The observer-based technique, being a fruitful direction in soft sensor design, is followed to develop soft sensors for nonlinear processes with known dynamics and unknown physical parameters. A new and general approach, based on the identified I/O linear approximant system descriptions, around prespecified operating points, and a bank of switching linear observers, will be developed. The system property of the I/O reconstructability of the state space linear approximant of a nonlinear model is presented. The design of each observer is based on the I/O measurements and structural characteristics of the nonlinear process. Observer-oriented target areas are introduced, and the respective dense web principle is formulated. The design is completed by the design of a data-driven rule-based system, providing stepwise switching among the observers of the bank. The number of observers of the bank is equal to the number of the linear approximants of the nonlinear process model and is equal to the number of the respective target operating areas. The target operating areas are required to satisfy the dense web principle. The information provided by the soft sensor is the estimation of the non-measured variables of the process. The information used by the soft sensor is the identified I/O approximants of the process as well as the real time values of the measurement variables. The efficiency of the design scheme is illustrated through symbolic and numerical simulation results for a chemostat. The nonlinear model of the chemostat is initially approximated by a set of ten linear approximants. After, the I/O approximants are identified, the respective observers are designed and the target operating areas are determined, where several cases of the satisfaction of the dense web principle are investigated. The soft sensor is composed in terms of the designed observers. Simulation results illustrate the satisfactory performance of the designed soft sensor.

An improved model-free adaptive control for nonlinear systems: An LMI approach

This paper proposes two model-free adaptive control (MFAC) schemes by using the linear matrix inequality (LMI) approach for the single-input single-output (SISO) and multi-input multi-output nonlinear (MIMO) systems, respectively. For each control scheme, with the aid of the dynamic linearization technique, the nonlinear system is transformed into an equivalent linear data model. In such a transformation, the nonlinear characteristic of systems is compressed into a time-varying parameter. Then, with the help of the introduction of the observer method, the tracking control problem can be converted into an optimization problem and the controller parameters can be obtained by using the LMI technique. This conversion cannot only reduce the complexity of the stability analysis but also find the appropriate controller parameters, especially for the MIMO case. Finally, three examples with comparisons are provided to illustrate the validity of the devised MFAC schemes.

Balancing a Stick With Eyes Shut: Inverted Pendulum on a Cart Without Angle Measurement

Abstract We consider linear time-invariant dynamic systems in the single-input, single-output (SISO) framework. In particular, we consider stabilization of an inverted pendulum on a cart using a force on the cart. This system is easy to stabilize with pendulum angle feedback. However, with cart position feedback it cannot be stabilized with stable and proper compensators. Here, we demonstrate that with an additional compensator in a parallel feedforward loop, stabilization is possible with such compensators. Sensitivity to noise seems to be about three times worse than for the situation with angle feedback. For completeness, discussion is presented of compensator parameter choices, robustness, fragility, and comparison with another control approach.

A Fast 3-D Chirp Scaling Imaging Technique for Millimeter-Wave Near-Field Imaging

In this article, a novel 3-D imaging method based on the chirp scaling algorithm (CSA) is proposed for millimeter-wave near-field imaging. We deduce the theoretical formula of CSA applied to multiple-input–multiple-output (MIMO)/single-input–single-output (SISO) array imaging and then analyze the computational complexity and phase error. Compared to the classical Fourier-based algorithm, such as range migration algorithm (RMA), they can replace the redundant interpolation with the phase multiplication. Meanwhile, it can handle the large relative bandwidth system compared with frequency scaling algorithm (FSA). It greatly improves imaging speed and broadens the application scenarios. The rearrangement operation of the MIMO wavenumber spectrum is also accelerated by the sparse matrix multiplication. To further reduce the computation time, we perform the direct rearrangement of the MIMO wavenumber spectrum before phase compensation. It works well but also sacrifices part of the signal-to-noise ratio (SNR), so it may not be suitable for the weakly scattering targets. The simulation data of a 2-D uniform array with the large number of antennas and a published dataset are used to verify the effect of the proposed algorithm. The simulation and experiment results show that the proposed method can effectively improve the computational efficiency.

Rate-Splitting Multiple Access for Short-Packet Uplink Communications: A Finite Blocklength Analysis

In this letter, we investigate the performance of Rate-Splitting Multiple Access (RSMA) for an uplink communication system with finite blocklegnth (FBL). Considering a two-user Single-Input Single-Output (SISO) Multiple Access Channel (MAC), we study the impact of blocklength and target rate on the throughput and error probability performance of RSMA where one user message is split. We demonstrate that RSMA can outperform Non-Orthogonal Multiple Access (NOMA) in terms of throughput and error probability performance.

Theoretical and Algorithmic Study of Inverses of Arbitrary High-Dimensional Multi-Input Multi-Output Linear-Time-Invariant Systems

Nowadays, systems need to be built and/or characterized to handle exceptional circumstances or adapt to a world itself more complex. A typical phenomenon can often be found that systems are required to accommodate high-dimensional inputs and outputs. Although the theories and methods for inverting a single-input single-output (SISO) linear-time-invariant (LTI) system have been well established, the generalized framework (consisting of theories and algorithms) for extending to arbitrary high-dimensional multi-input multi-output (MIMO) scenarios is still unsubstantial in the existing literature as this extension is far from trivial. In this work, we would like to develop such a new framework for governing the inversion of arbitrary high-dimensional discrete-time MIMO LTI systems, where any individual transfer function from a certain input to a certain output may have the infinite-impulse-response (IIR) characteristics. We propose two new inversion algorithms to invert the transfer-function tensors (TFTs) of arbitrary MIMO LTI systems. The pertinent computational complexities are also investigated for our proposed two TFT-inversion algorithms. The approximation of the inverse of an arbitrary TFT by a finite-impulse-response (FIR) TFT is studied and the corresponding approximation-error analysis is derived as well. Finally, numerical evaluations are presented to study the computational complexities with respect to different TFT dimensions and ranks.

Deep-Implanted MIMO Antenna Sensor for Implantable Medical Devices

A compact multiple-input–multiple-output (MIMO) implantable antenna is proposed in this article for deep-implanted medical devices. The suggested antenna enables high-data-rate telemetry as well as sensing the inner conditions of the tissues. It consists of two semicirc- ular patches that are excited with coaxial cables. The miniaturization in the suggested design is achieved using multiple slots in the patches, shorting pins, and high-permittivity substrate. Consequently, the antenna maintains a compact dimensions of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\pi \,\,\times6\,\,^{\mathrm{ 2}}\,\,\times0.13$ </tex-math></inline-formula> mm 3. Both elements of the antenna resonate at 0.915 GHz, possess a peak realized gain of −23.23 dBi, and maintain a low mutual coupling of −21.77 dB at 0.915 GHz. The effectiveness of the suggested antenna is verified using the specific absorption rate (SAR) and link budget analysis. Moreover, the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${2} \times {2}$ </tex-math></inline-formula> MIMO channel parameters such as the envelope correlation coefficient (ECC), diversity gain (DG), and channel capacity (CC) are calculated. In fact, CC using the suggested antenna reaches to 9.6 bps/Hz at a fixed SNR of 20 dB, which is almost two times more than that of the single-input–single-output (SISO) antenna (CC = 5.89 bps/Hz at SNR = 20 dB). The sensing ability of this antenna is demonstrated in addition to high-data-rate performance. The simulated and measured results confirm that it has almost similar radiation performance, impedance matching, and bandwidths for all dielectric properties of human tissues. Therefore, the proposed antenna is suitable for high-data-rate communication and monitoring pathological changes in deep tissues.