Single-input Single-output Systems Research Articles

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.

A Learning-Inspired Strategy to Design Binary Sequences With Good Correlation Properties: SISO and MIMO Radar Systems

In this paper, the design of binary sequences exhibiting low values of aperiodic/periodic correlation functions, in terms of Integrated Sidelobe Level (ISL), is pursued via a learning-inspired method. Specifically, the synthesis of either a single or a burst of codes is addressed, with reference to both Single-Input Single-Output (SISO) and Multiple-Input Multiple-Output (MIMO) radar systems. Two optimization machines, referred to as two-layer and single-layer Binary Sequence Correlation Network (BiSCorN), able to learn actions to design binary sequences with small ISL/Complementary ISL (CISL) for SISO and MIMO systems are proposed. These two networks differ in terms of the capability to synthesize Low-Correlation-Zone (LCZ) sequences and computational cost. Numerical experiments show that proposed techniques can outperform state-of-the-art algorithms for the design of binary sequences and Complementary Sets of Sequences (CSS) in terms of ISL and, interestingly, of Peak Sidelobe Level (PSL).

Data-driven IQC-Based Uncertainty Modelling for Robust Control Design

A new approach is presented in the paper for modelling uncertainty as an elliptical set for robust controller synthesis. The method involves finding the best linear nominal model and the corresponding elliptical uncertainty set that is consistent with a set of frequency response functions of linear time-invariant (LTI) single-input single-output (SISO) systems. The uncertainty set is then converted into an equivalent integral quadratic constraint (IQC) using a novel split representation of uncertainty. Finally, the IQC is integrated into a data-driven frequency-domain controller synthesis method through convex optimization. The simulation and experimental results demonstrate that the proposed method yields a “tighter” uncertainty set and improved stability margins compared to classical methods that use disk uncertainty.

Data-Driven Model-Reference Control With Closed-Loop Stability: The Output-Feedback Case

We generalize a recently introduced data-driven approach for model-reference control design with closed-loop stability guarantees to the case of single-input single-output systems with inaccessible state. By considering a dynamic controller with fixed structure and leveraging a data-based description of the closed-loop dynamics, we propose a two-stage strategy for the optimization of the controller’s parameters to match the desired closed-loop behavior. By means of a benchmark simulation example, we show the potential of the proposed approach and the impact of a simple strategy to handle noisy measurements.

Control and Stability Analysis of Current-Controlled Grid-Connected Inverters in Asymmetrical Grids

In symmetrical grids, single-input single-output (SISO) analysis/design tools are applicable for the analysis and design of grid-tied inverter systems as their average <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">αβ</i> - or <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dq</i> -frame models are to a high extent decoupled (in the high-frequency range). In this way, designing the control system could be done in a straightforward manner. However, this is not the case under asymmetrical grids. In this condition, the interaction between different phases makes the average model of the grid-tied inverter a multi-input multioutput (MIMO) system, and therefore, complicated to analyze and design. To cope with this challenge, this article deals with deriving the MIMO control system considering the impact of the asymmetrical grid. Then, the MIMO system turns into two decoupled SISO systems. Thus, a simple yet accurate model is developed which intuitively demonstrates the effect of the grid asymmetry on creating coupling between current control loops. In this way, the stability analysis could be carried out irrespective of the MIMO system difficulties. The experimental results validate the accuracy of the proposed approach in asymmetrical grid conditions.

Performance analysis and precoder design for IRS-assisted MIMO system with non-linear power amplifiers

In this work, a point-to-point intelligent-reflecting-surface (IRS) assisted single input single output (SISO) model is first developed and later modified to the multiple-input multiple-output (MIMO) case. For the SISO case, the transmitter or the access point (AP) is assumed to be equipped with a non-linear memory-less power amplifier (PA). A PA is assumed to be present for each data stream at the AP or base station (BS) side for the MIMO case. For both cases, three different types of PAs (A) Soft envelope limiter (SEL), (B) Solid-state power amplifier (SSPA), and (C) Travelling wave tube amplifier (TWTA) are considered. A Bussgang decomposition of the transmitted signal is then utilized for further analysis. A modified channel model is conceived for the AP-IRS-User equipment (UE) link based on the reflecting IRS elements’ radar cross-section (RCS). For the SISO system, both perfect and imperfect geometries of IRS elements with uniformly distributed element size errors are considered. An approximate closed-form expression for the upper bound on the above system’s spectral efficiency (SE) with ideal IRS elements is derived. The expression of the SE for two special cases of (A) Infinitely large IRS and (B) Ideal PA is deduced. Approximate closed-form expressions of various quality parameters for the IRS-assisted MIMO system with ideal and non-ideal PAs are also derived and verified numerically. Maximum ratio transmission (MRT) based precoder for this system is designed assuming that the information about the BS-UE link, BS-IRS-UE link, and the non-linear PA statistics is available at the BS. A closed-form expression for the SE of this system with this precoder is then derived and verified for various parametric situations.

Frequency Response Data-Based LPV Controller Synthesis Applied to a Control Moment Gyroscope

Control of systems with operating condition-dependent dynamics, including control moment gyroscopes (CMGs), often requires operating condition-dependent controllers to achieve high control performance. The aim of this brief is to develop a frequency response data-driven linear parameter-varying (LPV) control design approach for single-input single-output (SISO) systems, which allows improved performance for a CMG. A stability theory using a closed-loop frequency response function (FRF) data is developed, which is subsequently used in a synthesis procedure that guarantees local stability and performance. Experimental results on a CMG demonstrate the performance improvements.

Reconfigurable Intelligent Surface-Aided Cooperative NOMA with p-CSI Fading Channel toward 6G-Based IoT System.

Addressing the challenges of internet-based 5G technology, namely increasing density through micro-cell systems, frequency spectrum, and reducing resource costs, is needed to meet the use of IoT-based 6G technology with the goal of high-speed, high-capacity, and low-latency communication. In this research, we considered the coverage performance and ergodic capacity of the Reconfigurable Intelligent Surface (RIS)-aided cooperative nonorthogonal multiple-access network (NOMA) of an IoT system. This enables the upgrading of 5G- toward 6G-technology-based IoT systems. We developed a closest-form formula of near and far user coverage probabilities as a function of perfect channel statistical information (p-CSI) using only a single-input single-output (SISO) system with a finite number of RIS elements under the Nakagami-m fading channel. We also define ergodic capacity as a simple upper limit by simplifying the use of symbolic functions and it could be used for a sustained period. The simulation findings suggest that RIS-assisted NOMA has a reduced risk of outage than standard NOMA. All of the derived closed-form formulas agree with Monte Carlo simulations, indicating that the distant user’s coverage probability outperforms the nearby user. The bigger the number of RIS parts, however, the greater the chance of coverage. They also disclose the scaling law of the number of phase shifts at the RIS-aided NOMA based on the asymptotic analysis and the upper bound on channel capacity. In both arbitrary and optimum phase shifts, the distant user’s ergodic capacity outperforms the near user.

Neural network-based event-triggered data-driven control of disturbed nonlinear systems with quantized input

This paper is devoted to design an event-triggered data-driven control for a class of disturbed nonlinear systems with quantized input. A uniform quantizer reconstructed with decreasing quantization intervals is employed to reduce the quantization error. A neural network-based estimation strategy is proposed to estimate both the pseudo partial derivative and disturbances. Consequently, an input triggering rule for single-input single-output systems is provided by incorporating the estimated disturbances, the quantization error bound and tracking errors. Resorting to the Lyapunov method, sufficient conditions for synthesized error systems to be uniformly ultimately bounded are presented. The validity of the proposed scheme is demonstrated via a simulation example.

Stability Evaluation of Grid-Connected Microgrid Clusters in Asymmetrical Grids

Stability of grid-connected microgrids could be to a high extent guaranteed by designing a robust control system for inverters. However, this is not necessarily the case when microgrids are connected to an asymmetrical grid, where the grid impedance could have a different value in each phase. In this condition, the asymmetry of the grid impedance causes couplings between <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">αβ</i> - or <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dq</i> -frames in the average model, and therefore, the control system could not be simplified as a single-input single-output system anymore. In this case, the system turns into a multi-input multi-output system, and therefore, stability evaluation of such a system consisting of several microgrids that form microgrid clusters with multiparallel inverters could be a challenging task, which needs heavy mathematical derivations. In this article, a straightforward method is used for modeling the grid-connected microgrid clusters, in which the asymmetry of the grid impedance has been considered. Based on this approach, all the inverters in a microgrid are lumped in a frequency-domain-based model using the inverters’ Norton equivalent models. Then, based on the derived model, the generalized Nyquist criterion is used to evaluate the stability of the whole system. The proposed method considerably reduces the mathematical burden, while accurately predicts the system stability. The experimental results in a small-scale test bench in the laboratory validate the accuracy of the proposed method.

Design and Performance Analysis of Intra-Vehicle VLC System With Random Receiver Orientation

Visible light communication is a promising technology for communication in an intra-vehicle scenario which can support high throughput without causing any electromagnetic interference. In contrast to RF link, the VLC link is not isotropic, i.e., it highly depends on the line of sight links (LOS). Therefore, it is important to understand the impact of receiver orientation and user mobility on the performance of VLC system. In the first part of the work, the effect of receiver orientation on the LOS channel is explored. The receiver orientation is modeled as a truncated Gaussian distribution. Based on the statistics of receiver orientation, channel and received signal to noise ratio (SNR) statistics are obtained for both the single input single output (SISO) and multiple input single output (MISO) systems. For the SISO system, closed-form expression for the bit error rate (BER) and outage probability are obtained. For the MISO VLC system, the BER and outage probability are evaluated numerically. The impact of Field of View (FOV) which corresponds to the aperture on the receiver from the transmitter on the performance metrics such as outage probability and BER are analyzed. To capture the impact of mobility on the performance of the system, random way-point mobility model is considered. Closed-form expression for the PDF of the LOS channel gain and BER is derived under the condition of angular variations are more dominant than the overall radial-gain spread for a coherence-period. The derived results help to explore the joint impact of random receiver orientation and mobility on the performance.

Error analysis of SISO and dual-branch communications with generalized Gaussian noise over FTR fading channels

In this paper, we present error probability analysis for single-input single-output (SISO) and asymmetric dual-branch networks with additive white generalized Gaussian noise (AWGGN) over millimeter-wave (mmW) fluctuating two-ray (FTR) fading channels. Then, we examine the error probability evaluation of a SISO system with imperfect phase errors over mmW FTR fading channels. The probability density function (PDF) approach is employed for the error probability performance evaluation and the novel PDF of the asymmetric dual-branch system over Nakagami-m/mmW FTR fading channels is obtained. Specifically, closed-form expressions are derived for the error probability of the SISO and asymmetric dual-branch networks. The derived error expressions facilitate in effectively evaluating the performance of considered networks in the presence of AWGGN and imperfect phase noise with optimal fading parameters and modulation type. The theoretical derivations are extensively confirmed through exact simulations.

A novel hybrid of Nonlinear Sine Cosine Algorithm and Safe Experimentation Dynamics for model order reduction

ABSTRACT The current study introduces the hybridization of the Nonlinear Sine Cosine Algorithm (NSCA) and Safe Experimentation Dynamics (SED) as a novel optimization method for model order reduction of high-order single-input single-output (SISO) systems. Reciprocated synergism between both meta-heuristic algorithms is achieved by appropriating the nonlinear position-updated mechanism of NSCA for enhanced exploration/exploitation competencies and proficiency of SED in maximizing stagnation avoidance within the local optima. Named the NSCA-SED algorithm, the applicability of the proposed method is assessed by scholastic adoption of a sixth-order numerical transfer function towards two independent high-order systems enclosing Double-Pendulum Overhead Crane and Flexible Manipulator. Experimentation results further suggested NSCA-SED as the superior alternative in terms of execution robustness and consistency excellence against other available optimization-based methods for tackling model order reduction. Exemplified simulations sequentially demonstrated considerable improvements by the employment of NSCA-SED over conventional SCA following respective enhanced proportions of 97.17%, 13.17% and 29.03% for Example 1, Example 2 and Example 3.

Novel Approximate Distribution of the Sum of Lognormal-Rician Turbulence Channels With Pointing Errors and Applications in MIMO FSO Links

In this paper, an approximate closed-form probability density function expression for the sum of lognormal-Rician turbulence channels with Rayleigh pointing errors is developed. The results of Kolmogorov-Smirnov goodness-of-fit statistical tests show that the proposed approximation is highly accurate across a wide range of channel conditions. Also, the analysis of approximation error is presented in detail, and it indicates that a more efficient approximation can be achieved for larger coherence parameter <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$r$</tex-math></inline-formula> and smaller variance <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\sigma _{z}^{2}$</tex-math></inline-formula> . To reveal the importance of proposed approximation, the closed-form expressions for the ergodic capacity, outage probability, and bit-error rate are derived in terms of Meijer’s G-function. The performance of multiple-input multiple-output (MIMO) free-space optical (FSO) systems with equal gain combining (EGC) diversity technique are analyzed in detail under different scenarios, including the number of transmit and receive apertures, turbulence channels, and presence of pointing errors. It is observed that MIMO technology can offer a significant improvement in FSO performance when compared with the single-input single-output (SISO) systems. The ergodic capacity and BER performance at high signal-to-noise ratio are also obtained to provide further insights. Numerical results demonstrate the accuracy of the proposed approach.

Fractional Order KDHD Impedance Control of the Stewart Platform

In classical impedance control, KD, the steady-state end-effector forces are imposed to be proportional to the end-effector position errors through the stiffness matrix, K, and a proper damping term is added, proportional to the first-order derivatives of the end-effector position errors according to the damping matrix, D. This paper presents a fractional-order impedance control scheme, named KDHD, in which an additional damping is added, proportional to the half-order derivatives of the end-effector position errors according to the half-derivative damping matrix, HD. Since the finite-order digital filters which implement in real-time the half-order derivatives modify the steady-state stiffness of the end-effector—which should be defined exclusively by the stiffness matrix—a compensation method is proposed (KDHDc). The effectiveness of this approach is validated by multibody simulation on a Stewart platform. The proposed impedance controller represents the extension to multi-input multi-output robotic systems of the PDD1/2 controller for single-input single-output systems, which overperforms the PD scheme in the transient behavior.