Model reduction of SISO systems by Routh expansion and balancing method

The demand for ubiquitous telecommunications services forces operators to have a special concern about signal quality and the coverage area they offer to their customers. This was usually checked by using suitable propagation models for Single Input Single Output (SISO) systems, which are no longer the case for new and future mobile generations, such as 5G and beyond. To guarantee good signal quality coverage, operators started to replace these models with Multiple Input Multiple Output (MIMO) ones. To achieve the best results, these models are usually calibrated with Drive Test (DT) measures; however, the DTs available for MIMO propagation models are sparse, in contrast to SISO ones. The main contribution presented in this paper is a methodology to extend the propagation models of SISO systems so they can be applied in MIMO sytems with Single-Carrier and Frequency-Domain Equalization (SC-FDE), while still using DTs acquired for SISO systems. This paper presents the impact on Bit Error Rate (BER) performance and its coverage area resulting from the application of our proposed method. We consider a MIMO SC-FDE system with an Iterative Block Decision Feedback Equalization (IB-DFE) receiver and we present the improvement expressions for the BER that we illustrate with some simulations.

The design of a multi-level fuzzy-logic control system for the control of turbine engines using type-1 fuzzy-logic is presented in this paper. A Matlab-Simulink model of an advanced turbine engine was used to test and validate the performance of the developed fuzzy control system. The model provided comprehensive and complex model of a turbine engine. As with most modeling of turbine engines, it was assumed that the fundamental dynamic characteristics of a turbine engine can be achieved by control of the engine fuel flow. In this model a single input single output (SISO) system is used to control the engine fuel flow, where the input to the SISO system is the low spool speed error signal and the output is the fuel flow actuator control signal. A fuzzy controller was developed for the SISO system and its performance is compared with that of the existing proportional integral (PI) controller. Both controllers were tested under normal operating conditions and with introduction of engine faults embedded in the model.

Given a SISO (single-input single-output) system with arbitrary poles and zeros in the closed right half plane and having time delay uncertainty, the question arises as to the maximum time delay margin available before the closed-loop system becomes unstable when an arbitrary controller is connected to the SISO system in the closed loop. The authors provide a solution to this problem and show how to derive the controller corresponding to the optimum condition. The method of solution is based on general framework of P.P. Khargonekar and R. Tannenbaum (1985) for the robust stabilization of SISO systems with parameter uncertainty using Nevanlinna-Pick interpolation theory and the theory of conformal mapping. >

This paper strives to present a model order reduction (MOR) method for complex high order linear time-invariant (LTI) single input-single output (SISO) systems. The recommended method utilises the benefits of pole clustering method and differential evolution algorithm. In this suggested method, approximated denominator polynomial is obtained by pole clustering method whereas; approximated numerator is obtained using differential evolution algorithm. To indicate the effectiveness of the suggested method over existing MOR techniques, a comparison on the basis of a performance index known as integral square error (ISE) is depicted in this paper by using simulation graphs and in tabular form. Further, the suggested method is extended for MIMO systems also. Numerical examples are solved to give better understanding of the propound technique for SISO and MIMO systems. The recommended method derives and guarantees a stable approximated ROM if the original higher order system (HOS) is stable.

We have developed a loop-shaping methodology for robust control design in single-input single-output (SISO) systems with structured and unstructured uncertainties. This design method employs visualization tools that are modifications of the classical Bode plot. Using the proposed method control engineers can easily consider the effects of the structured and unstructured uncertainties without the need for transfer-function models of the plant, the sensitivity function performance, or the uncertainty. The method simultaneously can avoid excessive conservativeness and excessively high order controllers while improving controller performance and robustness. We show utility of the proposed method by applying it to a head-positioning control system in a hard disk drive.

The channel capacity of multiple-input multiple-output (MIMO) wideband CDMA system with coherent RAKE receiver is considered. General multi-path intensity Nakagami fading and multiple-access near/far interference channel are assumed. The analysis for system performance shows that the error of channel estimation significantly degrades BER performance and can be effectively suppressed by RAKE receiver and MIMO schemes. Also, an attempt for comparing the channel capacity on different performance improvement schemes has been made. In particular, the channel capacity of MIMO system is compared with single-input single-output (SISO) system. The MIMO complex spreading CDMA system with path correlation yields better performance with respect to channel capacity than a SISO system with i.i.d. input and output. And a discussion on the multiple-access near/far interference is also included, which illustrates that it can be effectively limited by power control and channel estimation schemes.KeywordsChannel EstimationChannel CapacityPilot SymbolInterference ModelCDMA SystemThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

In this paper, we derive the analytical expressions for the secure outage probability in a single-input single-output (SISO) system over fading, in which both the main and eavesdropper channels are subject to κ-μ fading. Many authors have analyzed the secrecy performance of such a SISO system over various fading models. More recently, a lower bound on the secure outage probability over κ-μ fading has been reported. However, the exact analytical expression of secure outage probability over κ-μ fading has not been obtained. The problem with using the lower bound is that we are not sure about the tightness of the bound. Our result is an exact expression which is verified by Monte-Carlo simulations. Furthermore, it enables us to examine the behavior of the secure outage probability as a function of the fading parameters of both the main and eavesdropper channels for given values of the average signal-to-noise power ratio (SNR) over these channels. Exact expressions for the case of Nakagami-m and Rician fading models for both the main and eavesdropper channels are also obtained and verified by simulations.

This paper proposes a model predictive controller for multivariable systems with time-delays. The design method is derived by the following way, first to consider a design for single input single output(SISO) systems and to modify the control problem for the SISO systems with no time-delays by shifting the outputs with time-delay steps and a design method with no time-delays is applied to the modified systems. Then the SISO case is extended to multi-input multi-output(MIMO) case by replacing time-delay steps in SISO case with an interactor matrix of MIMO plants.

In this paper the Routh Approximation method is explored for getting the reduced order model of a higher order model. The reduced order modeling of a large system is necessary to ease the analysis of the system. The approach is examined and compared to single-input single-output (SISO) and multi-input multi-output (MIMO) systems. The response comparison is considered in terms of step response parameters and graphical comparisons. It is reported that the reduced order model using proposed Routh Approximation (RA) method is almost similar in behavior to that of with original systems.

<p style='text-indent:20px;'>We consider model order reduction of a nonlinear cable-mass system modeled by a 1D wave equation with interior damping and dynamic boundary conditions. The system is driven by a time dependent forcing input to a linear mass-spring system at one boundary. The goal of the model reduction is to produce a low order model that produces an accurate approximation to the displacement and velocity of the mass in the nonlinear mass-spring system at the opposite boundary. We first prove that the linearized and nonlinear unforced systems are well-posed and exponentially stable under certain conditions on the damping parameters, and then consider a balanced truncation method to generate the reduced order model (ROM) of the nonlinear input-output system. Little is known about model reduction of nonlinear input-output systems, and so we present detailed numerical experiments concerning the performance of the nonlinear ROM. We find that the ROM is accurate for many different combinations of model parameters.

Nature has the key to solve every single problem that exists. This paper strives to propose a method which is based on flower pollination algorithm to acquire a stable reduced order model (ROM) of a higher order linear time-invariant (LTI) system. The suggested method utilizes Pade-based moment matching technique to deduce denominator approximants for the reduced order system, whereas the reduced order approximants of numerator polynomial are obtained using flower pollination (FP) algorithm. To prove the viability of the suggested method, numerical examples are solved considering single-input single-output (SISO) systems. A comparison has been drawn between suggested method and existing methods which are available in the current literature and is presented in this paper. This comparison is founded on a performance index which is known as integral square error (ISE).

Simplified dead-time compensator for multiple delay SISO systems

In this paper, the problem of designing a tracking controller for uncertain nonlinear second-order SISO (single input single output) systems which can suppress the effects of both the model uncertainty and noisy measurements is considered. Based on the framework of linear systems with nonlinear uncertainties whose norm-bounds are known we construct not only a sliding mode controller but a sliding observer for uncertain nonlinear second-order SISO systems, and we show the robust stability of the closed-loop control system. >

Mission critical narrow-band wireless communications standards such as IEEE 802.15.4g Smart Utility Network (SUN), Project 25, TETRA, ZigBee and custom SCADA systems were defined as Single Input Single Output (SISO) systems. As a result they lack built in provisions for smart multiport transceivers and associated antennas. These and other standards often lack channel coding techniques and may implement non-coherent modulation. Yet these systems are increasingly overwhelmed by interference in the form of network congestion, secondary users and out of band induced receiver intermodulation products. These networks operate in highly scattered environments that include multipath fading and Polarization Dependent Loss (PDL). This paper reviews multi-polarized antenna arrays and algorithms that exploit polarization scattering in the channel to mitigate both PDL and interference. These antennas and algorithms can be overlaid in new and replacement equipment providing Dynamic Spectrum Access (DSA) and an average 23dB Signal to Interference plus Noise Ratio (SINR) link budget improvement for mission critical SISO communication standards.

A time domain model reduction technique based on balanced realization has been applied to a single machine power system model i.e., a synchronous machine connected to an infinite bus through transmission line. The controllability and observability grammians have been computed by solving the Lyapunov equations. The high order system is transformed into balanced form by using the similarity transformation matrix to bring the grammian matrices to the balanced format, which is used to formulate the reduced order model in state space form. The results have also been compared with the Routh and Pade approximation methods, the two well-known frequency domain techniques. The comparison of time and frequency responses shows that, the reduced order models satisfactorily approximate the original system.