Steady State Error High loop gains were shown advantageous to reduce the sensitivity to modeling accuracy, parameter variations, and disturbance inputs. They will now prove equally desirable from the point of view of the reduction of steady-state errors in feedback systems. Consider the unity feedback system in Figure 1. The …

Read More »## Laplace Transform Properties in Signal and Systems

The Laplace transform fulfills a number of properties that are quite valuable in various applications. In particular, by using these properties, it is possible to derive many new transform pairs from a basic set of pairs. In this tutorial, we state most fundamental properties of the Laplace transform. Linearity If …

Read More »## Laplace Transform:Introduction and Example

Laplace Transform Definition The Laplace transform X(s) is a complex-valued function of the complex variable s. In other words, given a complex number s, the value X(s) of the transform at the point s is, in general, a complex number. Given a function x (t) of the continuous-time variable t, …

Read More »## Z Transform Introduction | Z Transform Properties

INTRODUCTION TO Z-TRANSFORM For the sake of analyzing continuous-time linear time-invariant (LTI) system, Laplace transformation is utilized. And z-transform is applied for the analysis of discrete-time LTI system. Z-transform is fundamentally a numerical tool applied for a transition of a time domain into frequency domain and is a mathematical function …

Read More »## Continuous Time Graphical Convolution Example

This is the continuation of the PREVIOUS TUTORIAL. Steps for Graphical Convolution First of all re-write the signals as functions of τ: x(τ) and h(τ) Flip one of the signals around t = 0 to get either x(-τ) or h(-τ) Best practice is to flip the signal with shorter interval …

Read More »## Continuous Time Convolution Properties | Continuous Time Signal

Continuous Time Convolution For linear time-invariant (LTI) systems, the convolution is being utilized in order to achieve output response from the knowledge of input and impulse response. Given two continuous-time signals x(t) and h(t), the convolution is defined as $y\left( t \right)=\sum\limits_{\tau =-\infty }^{\infty }{x\left( \tau \right)h\left( t-\tau \right)d\tau }~~~~~~~~~~~~~~~~~~~~~~~~\left( …

Read More »## Discrete Time Graphical Convolution Example

This is the continuation of the PREVIOUS TUTORIAL. This example is provided in collaboration with Prof. Mark L. Fowler, Binghamton University. You May Also Read: Discrete-Time Convolution Properties

Read More »$A=\left[ \begin{matrix} -1 & 0 \\ 0 & -5 \\\end{matrix} \right]$ $~b=\left[ \begin{matrix} 1.25 \\ -1.25 \\\end{matrix} \right]$ $u=e$

Read More »## Discrete Time Convolution Properties | Discrete Time Signal

Discrete-Time Convolution Convolution is such an effective tool that can be utilized to determine a linear time-invariant (LTI) system’s output from an input and the impulse response knowledge. Given two discrete time signals x[n] and h[n], the convolution is defined by $x\left[ n \right]*h\left[ n \right]=y\left[ n \right]=\sum\limits_{i=-\infty }^{\infty }{{}}x\left[ …

Read More »## Basic System Properties

Definition of a System A common way of viewing a system is in terms of a “black box” with terminals, as illustrated in the following figure: In the figure, x1(t), x2(t)… xp(t) are the signals applied to the p input terminals of the system and y1 (t), y2 (t)… yq …

Read More »## Linear Difference Equations

Consider the single–input single –output discrete time system given by the input/output difference equation. $y\left( kT+nT \right)+\underset{i=0}{\overset{n-1}{\mathop \sum }}\,{{a}_{i}}y\left( kT+iT \right)=\underset{i=0}{\overset{m}{\mathop \sum }}\,{{b}_{i}}x\left( kT+iT \right)~~~~~~~~~~~~\left( 1 \right)$ In (1), T is a fixed real number, k is a variable that takes its values from the set of integers, and the …

Read More »## Source Transformation Example Problems with Solutions

A highly valuable byproduct of Thevenin’s and Norton’s theorem is the technique of source transformation. Source transformation is based on the observation that if a Thevenin’s network and Norton’s network are both equivalent to a particular source network, then they must also equivalent to each other. This observation allows you …

Read More »## Voltage divider Circuits and Current divider Circuits

In analyzing a series circuit, it becomes necessary to find voltage drop across one or more of the resistances. A simple voltage drop relationship may be obtained by referring to the following figure. The total current is given by, $I=\frac{E}{{{R}_{1}}+{{R}_{2}}+{{R}_{3}}}$ And the voltage drop are given by, ${{V}_{1}}=I{{R}_{1}}=E\frac{{{R}_{1}}}{{{R}_{1}}+{{R}_{2}}+{{R}_{3}}}~~~~\text{ }~~~\left( 1 …

Read More »## Inductive and Capacitive Reactance | Definition & Formula

Basically, there are three types of elements that may be found in ac circuits. These may be classified as resistive, inductive, and capacitive. The value of resistance is independent of frequency, but the value of both an inductive circuit and a capacitive circuit is dependent on voltage frequency. If a …

Read More »## Power Factor Correction using Capacitor Bank

Power factor Ideally, all the supply voltage and current should be converted into true power in a load. When this is not a case, a certain kind of inefficiency occurs. The ratio of true power to apparent power is called the power factor of the load, \[\begin{matrix} Power\text{ }Factor=\frac{true\text{ }Power}{Apparent\text{ …

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