Mr. C.S.Satheesh, M.E.,
Frequency response analysis
Frequency Domain Specifications
Resonant Peak Mr
Resonant Frequency ωr
Bandwidth ωh
Cut – off Rate
Gain margin Kg
Phase margin γ
POLAR PLOT
Bode PLOT
Chapter 7 Controls Systems Analysis and Design by the frequency response analysis . From the book (Ogata Modern Control Engineering 5th).
7-1 introduction.
7-2 Bode diagrams.
This Presentation explains about the introduction of Frequency Response Analysis. This video clearly shows advantages and disadvantages of Frequency Response Analysis and also explains frequency domain specifications and derivations of Resonant Peak, Resonant Frequency and Bandwidth.
ppt on Time Domain and Frequency Domain Analysissagar_kamble
in this presentation, you will be able to know what is this freq. and time domain analysis.
At last one example is illustreted with video, which distinguishes these two analysis
Modern Control - Lec 05 - Analysis and Design of Control Systems using Freque...Amr E. Mohamed
The document discusses frequency response analysis and Bode plots. It begins with an introduction to frequency response and how the steady state response of a linear time-invariant system to a sinusoidal input is another sinusoid at the same frequency with a different magnitude and phase. The complex ratio of the output to input is called the frequency response. It then discusses Bode plots which show the magnitude and phase of the frequency response on logarithmic scales. Key features of components in open-loop transfer functions and how they affect the Bode plot shapes are explained. An example demonstrates drawing the Bode plots for a sample transfer function.
This document discusses frequency domain analysis and creating Bode plots. Frequency domain analysis examines a system's frequency response by using sinusoidal inputs rather than impulse inputs used in time domain analysis. A Bode plot graphs the magnitude and phase of a system's frequency response on logarithmic and linear scales. It can be used to determine stability margins like gain margin and phase margin. The document provides steps for sketching a Bode plot from a transfer function including identifying poles, zeros and gain. Key aspects of a Bode plot like bandwidth, resonant frequency and cut-off frequency are also defined. Examples of Bode plots for two transfer functions are included.
This document discusses the time response of a first order system to different input functions.
It describes how a first order system responds to a unit step input, with the output reaching 63.2% of its final value after one time constant. For a unit ramp input, the steady state error is equal to the time constant.
For a unit impulse input, the output is an exponential decay that returns the system to its initial state. The responses are related as the unit step is the derivative of the ramp, and the impulse is the derivative of the step, demonstrating the property of linear time-invariant systems.
Root locus is a graphical representation of the closed-loop poles as a system parameter is varied.
It can be used to describe qualitatively the performance of a system as various parameters are changed.
It gives graphic representation of a system’s transient response and also stability.
We can see the range of stability, instability, and the conditions that cause a system to break into oscillation.
Time domain specifications of second order systemSyed Saeed
This document discusses time domain specifications of second order systems, including delay time, rise time, peak time, maximum overshoot, settling time, and steady state error. It provides equations to calculate these specifications for a unit step response. It also includes three examples of determining damping ratio, natural frequency, and percentage overshoot for different second order systems.
Chapter 7 Controls Systems Analysis and Design by the frequency response analysis . From the book (Ogata Modern Control Engineering 5th).
7-1 introduction.
7-2 Bode diagrams.
This Presentation explains about the introduction of Frequency Response Analysis. This video clearly shows advantages and disadvantages of Frequency Response Analysis and also explains frequency domain specifications and derivations of Resonant Peak, Resonant Frequency and Bandwidth.
ppt on Time Domain and Frequency Domain Analysissagar_kamble
in this presentation, you will be able to know what is this freq. and time domain analysis.
At last one example is illustreted with video, which distinguishes these two analysis
Modern Control - Lec 05 - Analysis and Design of Control Systems using Freque...Amr E. Mohamed
The document discusses frequency response analysis and Bode plots. It begins with an introduction to frequency response and how the steady state response of a linear time-invariant system to a sinusoidal input is another sinusoid at the same frequency with a different magnitude and phase. The complex ratio of the output to input is called the frequency response. It then discusses Bode plots which show the magnitude and phase of the frequency response on logarithmic scales. Key features of components in open-loop transfer functions and how they affect the Bode plot shapes are explained. An example demonstrates drawing the Bode plots for a sample transfer function.
This document discusses frequency domain analysis and creating Bode plots. Frequency domain analysis examines a system's frequency response by using sinusoidal inputs rather than impulse inputs used in time domain analysis. A Bode plot graphs the magnitude and phase of a system's frequency response on logarithmic and linear scales. It can be used to determine stability margins like gain margin and phase margin. The document provides steps for sketching a Bode plot from a transfer function including identifying poles, zeros and gain. Key aspects of a Bode plot like bandwidth, resonant frequency and cut-off frequency are also defined. Examples of Bode plots for two transfer functions are included.
This document discusses the time response of a first order system to different input functions.
It describes how a first order system responds to a unit step input, with the output reaching 63.2% of its final value after one time constant. For a unit ramp input, the steady state error is equal to the time constant.
For a unit impulse input, the output is an exponential decay that returns the system to its initial state. The responses are related as the unit step is the derivative of the ramp, and the impulse is the derivative of the step, demonstrating the property of linear time-invariant systems.
Root locus is a graphical representation of the closed-loop poles as a system parameter is varied.
It can be used to describe qualitatively the performance of a system as various parameters are changed.
It gives graphic representation of a system’s transient response and also stability.
We can see the range of stability, instability, and the conditions that cause a system to break into oscillation.
Time domain specifications of second order systemSyed Saeed
This document discusses time domain specifications of second order systems, including delay time, rise time, peak time, maximum overshoot, settling time, and steady state error. It provides equations to calculate these specifications for a unit step response. It also includes three examples of determining damping ratio, natural frequency, and percentage overshoot for different second order systems.
Ch5 transient and steady state response analyses(control)Elaf A.Saeed
Chapter 5 Transient and steady-state response analyses. From the book (Ogata Modern Control Engineering 5th).
5-1 introduction.
5-2 First-Order System.
5-3 second-order system.
5-6 Routh’s stability criterion.
5-8 Steady-state errors in unity-feedback control systems.
Dcs lec03 - z-analysis of discrete time control systemsAmr E. Mohamed
The document discusses discrete time control systems and their mathematical representation using z-transforms. It covers topics such as impulse sampling, the convolution integral method for obtaining the z-transform, properties of the z-transform, inverse z-transforms using long division and partial fractions, and mapping between the s-plane and z-plane. Examples are provided to illustrate various concepts around discrete time systems and their analysis using z-transforms.
Modern Control - Lec 03 - Feedback Control Systems Performance and Characteri...Amr E. Mohamed
The document summarizes key concepts about feedback control systems including:
- It defines the order of a system as the highest power of s in the denominator of the transfer function. First and second order systems are discussed.
- Standard test signals like impulse, step, ramp and parabolic are introduced to analyze the response of systems.
- The time response of systems has transient and steady-state components. Poles determine the transient response.
- For first order systems, the responses to unit impulse, step, and ramp inputs are derived. The step response reaches 63.2% of its final value after one time constant.
- For second order systems, the natural frequency, damping ratio, and poles are defined.
This document discusses linear time-invariant (LTI) systems and convolution. Convolution is a fundamental concept in signal processing that is used to determine the output of an LTI system given its impulse response and an input signal. The convolution of two signals is obtained by decomposing the input signal into scaled and shifted impulses, taking the scaled and shifted impulse response for each impulse, and summing them to find the overall output. Convolution amplifies or attenuates different frequency components of the input independently. It plays an important role in applications like image processing and edge detection. Examples are provided to demonstrate evaluating convolution of periodic sequences.
EC8352- Signals and Systems - Unit 2 - Fourier transformNimithaSoman
This document discusses Fourier transforms and their applications. It begins by introducing Fourier transforms and noting that they are used widely in optics, image processing, speech processing, and medical signal processing. It then covers key topics such as:
- When periodic and aperiodic signals can be represented by Fourier series versus Fourier transforms
- Properties of continuous-time and discrete-time Fourier transforms
- Applications of Fourier transforms in filtering ECG signals, modeling diffractive gratings in optics, speech processing, and image processing
- Limitations of Fourier transforms in representing non-stable systems
The document provides an overview of Fourier transforms and their significance in decomposing signals into constituent frequencies, as well as examples of where they are applied in
This document provides an overview of transfer functions and stability analysis of linear time-invariant (LTI) systems. It discusses how the Laplace transform can be used to represent signals as algebraic functions and calculate transfer functions as the ratio of the Laplace transforms of the output and input. Poles and zeros are introduced as important factors for stability. A system is stable if all its poles reside in the left half of the s-plane and unstable if any pole resides in the right half-plane. Examples are provided to demonstrate calculating transfer functions from differential equations and analyzing stability based on pole locations.
Modern Control - Lec 04 - Analysis and Design of Control Systems using Root L...Amr E. Mohamed
The document provides an overview of root locus analysis and design of control systems. It begins with an introduction to root locus including motivation, definition, and the basic feedback control system model. It then covers the key rules and steps for constructing and interpreting root loci, including determining asymptotes, breakaway/break-in points, and imaginary axis crossings. Three examples are worked through step-by-step to demonstrate how to apply the rules and steps to sketch root loci for different open-loop transfer functions. The document emphasizes that root locus allows choosing controller parameters to place closed-loop poles in desired performance regions.
This document provides an introduction and syllabus for a signals and systems course taught by Prof. Satheesh Monikandan.B at the Indian Naval Academy. The syllabus covers topics such as signal classification, system properties, sampling, and transforms. It defines key concepts like signals, systems, continuous and discrete time signals, and linear and nonlinear systems. Elementary signals like sinusoidal, exponential, unit step, and impulse are also introduced.
This document discusses the root locus technique for analyzing control systems. It describes the 7 step procedure for constructing a root locus plot: (1) locate poles and zeros, (2) determine the real axis path, (3) find asymptote angles, (4) identify breakaway points, (5) calculate departure and arrival angles, (6) find imaginary axis intersections, (7) sketch the root locus using test points. The root locus technique allows observing how closed-loop poles move in the s-plane as the system gain varies, helping to achieve desired performance.
This document discusses signals and their classification. It defines signals, analog and digital signals, periodic and aperiodic signals. It also discusses representing signals in Matlab and Simulink. Key signal types covered include exponential, sinusoidal, unit impulse and step functions. Matlab is presented as a tool for programming and analyzing discrete signals while Simulink can be used to model and simulate continuous systems.
Mr. C.S.Satheesh, M.E.,
Time Response in systems
Time Response
Transient response
Steady-state response.
Delay Time (td)
Rise Time (tr)
Peak Time (tp)
Maximum Overshoot (Mp)
Settling Time (tS)
Standard Test Signals
Impulse signal
Step signal
Ramp signal
Parabolic signal
1. The document discusses time domain analysis of second order systems. It defines key terms like damping ratio, natural frequency, and describes the four categories of responses based on damping ratio: overdamped, underdamped, undamped, and critically damped.
2. An example shows how to determine the natural frequency and damping ratio from a given transfer function. The poles of a second order system depend on these parameters.
3. The time domain specification of a second order system's step response is explained, including definitions of delay time, rise time, peak time, settling time, and overshoot.
The document discusses polar plots, which graph the magnitude and phase of a transfer function G(jω)H(jω) as ω varies from 0 to infinity. It provides rules for drawing polar plots, such as substituting s=jω into the transfer function, finding the starting and ending magnitude and phase, and checking for intersections with the real and imaginary axes. An example is shown of creating a polar plot for a first order system, including determining the magnitude and phase expressions and values at specific ω points and drawing the resulting plot.
The document discusses time domain analysis and standard test signals used to analyze dynamic systems. It describes the impulse, step, ramp, and parabolic signals which imitate characteristics of actual inputs such as sudden shock, sudden change, constant velocity, and constant acceleration. The time response of first order systems to these standard inputs is expressed mathematically. The impulse response directly provides the system transfer function. Step response reaches 63% of its final value within one time constant.
Digital controllers have several advantages over analog controllers, including flexibility, decision-making capability, and high performance for a lower cost. They can also be easily designed and tested through simulations. A digital control system uses analog to digital converters to digitize sensor signals and digital to analog converters to generate control signals. It samples continuous sensor signals and holds the values constant between samples, introducing quantization error that can be reduced by increasing the number of quantization levels.
This document contains lecture notes on signals and systems for a course at Chadalawada Ramanamma Engineering College. It includes:
1. An introduction to signals, systems, and some common elementary signals like the unit step, unit impulse, ramp, sinusoid, and exponential signals.
2. A classification of signals as continuous/discrete, deterministic/non-deterministic, even/odd, periodic/aperiodic, energy/power, and real/imaginary.
3. A discussion of basic operations on signals like amplitude scaling, addition, and subtraction.
The Nyquist stability criterion examines the stability of a linear control system by analyzing the contour of the open-loop transfer function G(s)H(s) in the complex plane. If the contour encircles the point -1+j0 in an anticlockwise direction the same number of times as the number of poles of G(s)H(s) in the right half plane, then the closed-loop system is stable. If there is no encirclement of -1+j0, the system is stable if there are no right half plane poles, and unstable if there are. Clockwise encirclement of -1+j0 always results in an unstable system. The criterion can be used
This document provides an overview of time domain analysis techniques for control systems. It discusses common test inputs like impulse, step, and ramp functions used to characterize system performance. It describes how to determine a system's poles and zeros from its transfer function and use a pole-zero plot to understand system dynamics. Standard forms are presented for first and second order systems. Transient performance metrics like rise time, peak time, settling time, and overshoot are defined for characterizing step responses. The effects of poles and zeros on the system response are explained.
This document discusses frequency domain analysis and Bode plots. It introduces key concepts in frequency domain analysis including frequency response, transfer function, resonant frequency, resonant peak, cutoff frequency, bandwidth, gain margin, and phase margin. It explains that a Bode plot consists of magnitude and phase plots which show how the gain and phase of a system change over frequency. The document provides instructions for sketching a Bode plot from a transfer function including identifying poles, zeros and gains. It includes examples of Bode plots for two sample transfer functions.
This document discusses time domain and frequency domain analysis for measurement systems. Time domain analysis examines how a signal changes over time, allowing the system's transient response to be modeled through equations. Frequency domain analysis represents a signal as a combination of sinusoids, allowing characteristics like bandwidth and stability to be examined from the system's transfer function. Key specifications for both domains are defined, such as rise time, settling time, and bandwidth. Frequency response plots like Bode and Nyquist diagrams provide a graphical way to analyze stability. An example of measuring solar panel output is given to demonstrate these analytical techniques.
Ch5 transient and steady state response analyses(control)Elaf A.Saeed
Chapter 5 Transient and steady-state response analyses. From the book (Ogata Modern Control Engineering 5th).
5-1 introduction.
5-2 First-Order System.
5-3 second-order system.
5-6 Routh’s stability criterion.
5-8 Steady-state errors in unity-feedback control systems.
Dcs lec03 - z-analysis of discrete time control systemsAmr E. Mohamed
The document discusses discrete time control systems and their mathematical representation using z-transforms. It covers topics such as impulse sampling, the convolution integral method for obtaining the z-transform, properties of the z-transform, inverse z-transforms using long division and partial fractions, and mapping between the s-plane and z-plane. Examples are provided to illustrate various concepts around discrete time systems and their analysis using z-transforms.
Modern Control - Lec 03 - Feedback Control Systems Performance and Characteri...Amr E. Mohamed
The document summarizes key concepts about feedback control systems including:
- It defines the order of a system as the highest power of s in the denominator of the transfer function. First and second order systems are discussed.
- Standard test signals like impulse, step, ramp and parabolic are introduced to analyze the response of systems.
- The time response of systems has transient and steady-state components. Poles determine the transient response.
- For first order systems, the responses to unit impulse, step, and ramp inputs are derived. The step response reaches 63.2% of its final value after one time constant.
- For second order systems, the natural frequency, damping ratio, and poles are defined.
This document discusses linear time-invariant (LTI) systems and convolution. Convolution is a fundamental concept in signal processing that is used to determine the output of an LTI system given its impulse response and an input signal. The convolution of two signals is obtained by decomposing the input signal into scaled and shifted impulses, taking the scaled and shifted impulse response for each impulse, and summing them to find the overall output. Convolution amplifies or attenuates different frequency components of the input independently. It plays an important role in applications like image processing and edge detection. Examples are provided to demonstrate evaluating convolution of periodic sequences.
EC8352- Signals and Systems - Unit 2 - Fourier transformNimithaSoman
This document discusses Fourier transforms and their applications. It begins by introducing Fourier transforms and noting that they are used widely in optics, image processing, speech processing, and medical signal processing. It then covers key topics such as:
- When periodic and aperiodic signals can be represented by Fourier series versus Fourier transforms
- Properties of continuous-time and discrete-time Fourier transforms
- Applications of Fourier transforms in filtering ECG signals, modeling diffractive gratings in optics, speech processing, and image processing
- Limitations of Fourier transforms in representing non-stable systems
The document provides an overview of Fourier transforms and their significance in decomposing signals into constituent frequencies, as well as examples of where they are applied in
This document provides an overview of transfer functions and stability analysis of linear time-invariant (LTI) systems. It discusses how the Laplace transform can be used to represent signals as algebraic functions and calculate transfer functions as the ratio of the Laplace transforms of the output and input. Poles and zeros are introduced as important factors for stability. A system is stable if all its poles reside in the left half of the s-plane and unstable if any pole resides in the right half-plane. Examples are provided to demonstrate calculating transfer functions from differential equations and analyzing stability based on pole locations.
Modern Control - Lec 04 - Analysis and Design of Control Systems using Root L...Amr E. Mohamed
The document provides an overview of root locus analysis and design of control systems. It begins with an introduction to root locus including motivation, definition, and the basic feedback control system model. It then covers the key rules and steps for constructing and interpreting root loci, including determining asymptotes, breakaway/break-in points, and imaginary axis crossings. Three examples are worked through step-by-step to demonstrate how to apply the rules and steps to sketch root loci for different open-loop transfer functions. The document emphasizes that root locus allows choosing controller parameters to place closed-loop poles in desired performance regions.
This document provides an introduction and syllabus for a signals and systems course taught by Prof. Satheesh Monikandan.B at the Indian Naval Academy. The syllabus covers topics such as signal classification, system properties, sampling, and transforms. It defines key concepts like signals, systems, continuous and discrete time signals, and linear and nonlinear systems. Elementary signals like sinusoidal, exponential, unit step, and impulse are also introduced.
This document discusses the root locus technique for analyzing control systems. It describes the 7 step procedure for constructing a root locus plot: (1) locate poles and zeros, (2) determine the real axis path, (3) find asymptote angles, (4) identify breakaway points, (5) calculate departure and arrival angles, (6) find imaginary axis intersections, (7) sketch the root locus using test points. The root locus technique allows observing how closed-loop poles move in the s-plane as the system gain varies, helping to achieve desired performance.
This document discusses signals and their classification. It defines signals, analog and digital signals, periodic and aperiodic signals. It also discusses representing signals in Matlab and Simulink. Key signal types covered include exponential, sinusoidal, unit impulse and step functions. Matlab is presented as a tool for programming and analyzing discrete signals while Simulink can be used to model and simulate continuous systems.
Mr. C.S.Satheesh, M.E.,
Time Response in systems
Time Response
Transient response
Steady-state response.
Delay Time (td)
Rise Time (tr)
Peak Time (tp)
Maximum Overshoot (Mp)
Settling Time (tS)
Standard Test Signals
Impulse signal
Step signal
Ramp signal
Parabolic signal
1. The document discusses time domain analysis of second order systems. It defines key terms like damping ratio, natural frequency, and describes the four categories of responses based on damping ratio: overdamped, underdamped, undamped, and critically damped.
2. An example shows how to determine the natural frequency and damping ratio from a given transfer function. The poles of a second order system depend on these parameters.
3. The time domain specification of a second order system's step response is explained, including definitions of delay time, rise time, peak time, settling time, and overshoot.
The document discusses polar plots, which graph the magnitude and phase of a transfer function G(jω)H(jω) as ω varies from 0 to infinity. It provides rules for drawing polar plots, such as substituting s=jω into the transfer function, finding the starting and ending magnitude and phase, and checking for intersections with the real and imaginary axes. An example is shown of creating a polar plot for a first order system, including determining the magnitude and phase expressions and values at specific ω points and drawing the resulting plot.
The document discusses time domain analysis and standard test signals used to analyze dynamic systems. It describes the impulse, step, ramp, and parabolic signals which imitate characteristics of actual inputs such as sudden shock, sudden change, constant velocity, and constant acceleration. The time response of first order systems to these standard inputs is expressed mathematically. The impulse response directly provides the system transfer function. Step response reaches 63% of its final value within one time constant.
Digital controllers have several advantages over analog controllers, including flexibility, decision-making capability, and high performance for a lower cost. They can also be easily designed and tested through simulations. A digital control system uses analog to digital converters to digitize sensor signals and digital to analog converters to generate control signals. It samples continuous sensor signals and holds the values constant between samples, introducing quantization error that can be reduced by increasing the number of quantization levels.
This document contains lecture notes on signals and systems for a course at Chadalawada Ramanamma Engineering College. It includes:
1. An introduction to signals, systems, and some common elementary signals like the unit step, unit impulse, ramp, sinusoid, and exponential signals.
2. A classification of signals as continuous/discrete, deterministic/non-deterministic, even/odd, periodic/aperiodic, energy/power, and real/imaginary.
3. A discussion of basic operations on signals like amplitude scaling, addition, and subtraction.
The Nyquist stability criterion examines the stability of a linear control system by analyzing the contour of the open-loop transfer function G(s)H(s) in the complex plane. If the contour encircles the point -1+j0 in an anticlockwise direction the same number of times as the number of poles of G(s)H(s) in the right half plane, then the closed-loop system is stable. If there is no encirclement of -1+j0, the system is stable if there are no right half plane poles, and unstable if there are. Clockwise encirclement of -1+j0 always results in an unstable system. The criterion can be used
This document provides an overview of time domain analysis techniques for control systems. It discusses common test inputs like impulse, step, and ramp functions used to characterize system performance. It describes how to determine a system's poles and zeros from its transfer function and use a pole-zero plot to understand system dynamics. Standard forms are presented for first and second order systems. Transient performance metrics like rise time, peak time, settling time, and overshoot are defined for characterizing step responses. The effects of poles and zeros on the system response are explained.
This document discusses frequency domain analysis and Bode plots. It introduces key concepts in frequency domain analysis including frequency response, transfer function, resonant frequency, resonant peak, cutoff frequency, bandwidth, gain margin, and phase margin. It explains that a Bode plot consists of magnitude and phase plots which show how the gain and phase of a system change over frequency. The document provides instructions for sketching a Bode plot from a transfer function including identifying poles, zeros and gains. It includes examples of Bode plots for two sample transfer functions.
This document discusses time domain and frequency domain analysis for measurement systems. Time domain analysis examines how a signal changes over time, allowing the system's transient response to be modeled through equations. Frequency domain analysis represents a signal as a combination of sinusoids, allowing characteristics like bandwidth and stability to be examined from the system's transfer function. Key specifications for both domains are defined, such as rise time, settling time, and bandwidth. Frequency response plots like Bode and Nyquist diagrams provide a graphical way to analyze stability. An example of measuring solar panel output is given to demonstrate these analytical techniques.
The document discusses frequency response and Bode plots. It begins by defining the sinusoidal transfer function and frequency response. The frequency response consists of the magnitude and phase functions of the transfer function. Bode plots graphically display the magnitude and phase functions versus frequency on logarithmic scales. The document then provides procedures for constructing Bode plots, including determining individual component responses, combining them, and reading off gain and phase margins. Examples are given to demonstrate the procedures.
Optimization channal contral power in live umts networkThananan numatti
Abstract— The proposed approach to improvement on the
UMTS (Universal Mobile Telecommunications System)
network radio, there are many ways we propose another way of
reducing power control channel slightly to provide improved
signal quality, which is a measure of quality is EcIo (energy per
bit) / (Own cell interference +. Noise density) principle when the
power control channel down a bit to make the quality better,
because the denominator less energy than ever before, and open
the extra capacity in the network in the body, this is the reason
for the optimization this principle can be applied in a live
network.
It is important to maintain signal quality are durable and
resistant to interference. Probability to the good benefits for
imply network must be physical tuning coverage complete before
and area dense urban or urban is good to the imply this
parameter. For area rural should not imply because the cell edge
a foot print coverage is too large . However this paper presents a science so that the results can be applied to real work.
This document discusses methods for detecting and classifying disturbances in a hybrid distributed power system using wavelet transform and artificial neural networks. It begins by introducing the motivation for distributed generation and some challenges like unintentional islanding. It then describes using the wavelet transform on voltage signals to detect islanding and compares this to using total harmonic distortion. Statistical indices from the wavelet transform are used as inputs to an artificial neural network classifier to identify different disturbances like islanding, faults, and load changes with over 95% accuracy. The study concludes the wavelet transform approach provides better detection and classification than conventional techniques. Future work could explore improving performance under noisy conditions and different feature selection.
Satellite communications systems allow communication between two points on Earth via satellites. A signal is transmitted from an earth station to a satellite, which then relays the signal to another earth station. Satellites provide large area coverage and can bypass terrestrial networks. They are used for voice calls, television, radio, internet access, and more. Higher frequency bands like Ku-band provide more flexibility than C-band but are more susceptible to rain fade. Modern systems use modulation techniques like QPSK and 8-PSK along with error correction coding to optimize bandwidth use on satellites.
This document describes the design of a 2.4GHz CMOS power amplifier for wireless communication using a 130nm technology. It begins with an introduction to power amplifiers and their importance in wireless transmitters for amplifying transmitted signals. It then reviews previous work on power amplifier design using different technologies. The document proposes a class-B power amplifier design using a 130nm technology to achieve a gain of more than 15dB. Simulation results show the designed class-B power amplifier meets the frequency response requirement at 2.4GHz with a gain of 67.321dB. The power amplifier is designed to operate with a power supply voltage range of 1.3-3V, making it suitable for battery-powered portable electronics and wireless communication
Mitigation of Noise in OFDM Based Plc System Using Filter Kernel DesignIJERA Editor
Power line communication is a technology that transforms power line in to pathway for conveyance of
broadband data. It is cost less than other communication approach and for better bandwidth efficiency OFDM
based PLC system is used. In real PLC environment some electrical appliances will produce noise. To mitigate
this noise filter kernel design is used, so periodic impulsive noise and Gaussian noises are removed from PLC
communication system by using this filter kernel design. MATLAB is used for the simulation and the result
shows that filter kernel is simple and effective noise mitigation technique. Further in future, interference due to
obstacles also wants to be mitigated for the better data transmission without noise.
This document discusses several topics related to optical fiber communication systems including:
1. Factors that limit the performance of amplified fiber links such as transmission distance, data rate, and component costs.
2. System requirements including transmission distance, data rate, fiber type, and receiver sensitivities.
3. Key components of fiber optic systems and their specifications including lasers, detectors, and other elements.
4. Performance limiting factors for terrestrial and undersea lightwave systems.
5. Physical phenomena that degrade receiver sensitivity in realistic lightwave systems including modal noise and dispersion broadening.
Bode plots provide a graphical representation of a system's frequency response by plotting magnitude and phase response against frequency. They are useful engineering tools for analyzing and designing control systems. Key features like gain and phase margin, bandwidth, resonance frequencies, and stability can be determined from a system's Bode plots. An example Bode plot is shown for a simple low-pass filter.
Feedback systems are used to stabilize amplifiers and control systems. Negative feedback reduces the gain of an amplifier, making it less sensitive to variations and more stable. While feedback stabilizes systems, it can also cause oscillations if the loop gain exceeds 1. Researchers like Bode and Nyquist analyzed stability and developed criteria to determine when feedback amplifiers will become unstable. Oscillators are designed to produce stable oscillations by ensuring the feedback is positive. Frequency domain analysis using Fourier techniques can be used to analyze linear and time-invariant systems. Design specifications for control systems include parameters for time response, steady state error, and gain/phase margins.
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
Bit error rate analysis of miso system in rayleigh fading channeleSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Bode plots provide a graphical representation of a system's frequency response by plotting magnitude and phase response against frequency. They are useful engineering tools for analyzing and designing control systems. The key aspects shown are magnitude response in dB, phase response in degrees, corner frequencies, bandwidth, gain margin, phase margin, and stability. An example Bode plot is given for a simple low-pass filter.
Performance Analysis of Acoustic Echo Cancellation TechniquesIJERA Editor
Mainly, the adaptive filters are implemented in time domain which works efficiently in most of the applications. But in many applications the impulse response becomes too large, which increases the complexity of the adaptive filter beyond a level where it can no longer be implemented efficiently in time domain. An example of where this can happen would be acoustic echo cancellation (AEC) applications. So, there exists an alternative solution i.e. to implement the filters in frequency domain. AEC has so many applications in wide variety of problems in industrial operations, manufacturing and consumer products. Here in this paper, a comparative analysis of different acoustic echo cancellation techniques i.e. Frequency domain adaptive filter (FDAF), Least mean square (LMS), Normalized least mean square (NLMS) &Sign error (SE) is presented. The results are compared with different values of step sizes and the performance of these techniques is measured in terms of Error rate loss enhancement (ERLE), Mean square error (MSE)& Peak signal to noise ratio (PSNR).
This document summarizes key concepts about antennas and propagation. It discusses antenna types and properties like radiation patterns, gain, and effective area. It also covers propagation modes including ground wave, sky wave, and line-of-sight. Impairments like attenuation, noise, multipath, and fading are explained. Error compensation techniques like forward error correction, equalization, and diversity are also introduced.
The document provides instructions for experiments to be conducted in the Control Systems Lab course at BTL Institute of Technology and Management in Bangalore, India. It lists 11 experiments involving designing and analyzing compensating networks, studying controller performance, and using MATLAB/SCILAB for simulations. The experiments are divided into two cycles, with the first cycle focusing on hardware implementations and the second on software simulations. Specific procedures are given for designing and characterizing lead and lag compensators.
This document provides an overview and agenda for an oscilloscope fundamentals workshop. The agenda covers choosing an oscilloscope, probing basics including passive probe compensation and ground lead effects, vertical system components like input coupling and scale, sampling and acquisition concepts like aliasing and rate, horizontal system parameters, trigger systems including runt triggering, and using an oscilloscope for EMI debugging. Hands-on workshops are included to demonstrate various topics like probe compensation, ground loop effects, input coupling, aliasing, display update rate, and using near-field probes for EMI analysis. The goal is to review important oscilloscope concepts and allow participants to experiment with the effects of different settings and probe techniques.
Mathematical Modeling of Class B Amplifire Using Natural and Regular Sampled ...ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
Amplitude and frequency response (2).pptxGomathi454280
The document discusses amplitude frequency response (AFR), which measures the amplitude of a system's output at different frequencies. AFR provides insights into a system's behavior and characteristics by identifying resonant frequencies, damping effects, and frequency-dependent amplification or attenuation. It is measured using techniques like sine sweeps and frequency response analyzers and displayed in graphs with amplitude on the y-axis and frequency on the x-axis. Understanding AFR is important for fields like acoustics, electronics, and engineering as it aids in system optimization and design.
Linear Integrated Circuits and Its Applications Unit-V Special ICsSatheeshCS2
Linear Integrated Circuits and Its Applications
Unit-V Special ICs
Mr. C.S.SATHEESH, M.E.(Control Systems),
Assistant Professor, Department of EEE, Muthayammal Engineering College, (Autonomous) Namakkal (Dt), Rasipuram – 637408
First & second order of the control systemsSatheeshCS2
This document summarizes key concepts about first and second order control systems. It discusses:
- The characteristics of a first order system, which has one pole and is defined by its DC gain (K) and time constant (T).
- Examples of first order systems and how to determine their DC gain and time constant.
- That a second order system can have different responses depending on its parameters, such as damped or undamped oscillations.
- How to determine the undamped natural frequency and damping ratio of a second order system by comparing its transfer function to the general second order transfer function.
The document then provides example problems for determining properties of first and second order systems. It concludes by
State variable analysis (observability & controllability)SatheeshCS2
Mr. C.S.Satheesh, M.E.,
State Variable Analysis
Observability
Controllability
Concept of state variables
State models for linear and time invariant Systems
Solution of state and output equation in controllable canonical form
Concepts of controllability and observability
Effect of state feedback.
Mr. C.S.Satheesh, M.E.,
Servomotor
Control motors
Two Phase AC Servo Motor
Three Phase AC Servo Motor
DC Servo Motor
AC Servo Motor
Control Type Synchro.
Torque Transmission Type Synchro
Synchros
Mr. C.S.Satheesh, M.E.,
Routh Array Hurwitz Criterion
determining whether all the roots of a polynomial have negative real part or not.
characteristic equation.
the coefficients of the polynomial be positive.
coefficients are zero or negative
purely imaginary roots so the system is limitedly or marginally stable.
remaining roots lies on left half of S plane.
Root locus & nyquist stability criterionSatheeshCS2
This document discusses root locus analysis and the Nyquist stability criterion. It provides an overview of root locus, including that it was introduced by W.R. Evans to analyze control systems and is used to adjust closed-loop pole locations. It also discusses the characteristic equation, root locus paths as gain varies from 0 to infinity, and Evans magnitude and angle criteria for determining points on the root locus. Construction of the root locus using rules to sketch it is also covered.
Mechanical translational rotational systems and electrical analogous circuit...SatheeshCS2
Mr. C.S.Satheesh, M.E.,
Mechanical Translational and Rotational Systems and Electrical analogous Circuits in control systems
Spring
Dash-pot
Analogous electrical elements in torque current analogy for the elements of mechanical rotational system.
Electrical systems
This document discusses block diagram reduction techniques and signal flow graphs. It defines a block diagram as a pictorial representation of the functions and signal flows in a control system. Block diagram reduction techniques can be used to simplify block diagrams and find closed loop transfer functions. Signal flow graphs further simplify block diagrams by removing blocks and using branches and nodes instead, with transfer functions called transmittances. Examples are given of representing equations as block diagrams and signal flow graphs. Problems are presented and solved as examples of using these techniques.
Mr. C.S.Satheesh, M.E.,
Basic elements in control systems
System
Types of Control Systems
Open Loop Control Systems
Closed Loop Control Systems
Difference Between Open loop & Closed loop Control Systems
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
Literature Review Basics and Understanding Reference Management.pptxDr Ramhari Poudyal
Three-day training on academic research focuses on analytical tools at United Technical College, supported by the University Grant Commission, Nepal. 24-26 May 2024
Batteries -Introduction – Types of Batteries – discharging and charging of battery - characteristics of battery –battery rating- various tests on battery- – Primary battery: silver button cell- Secondary battery :Ni-Cd battery-modern battery: lithium ion battery-maintenance of batteries-choices of batteries for electric vehicle applications.
Fuel Cells: Introduction- importance and classification of fuel cells - description, principle, components, applications of fuel cells: H2-O2 fuel cell, alkaline fuel cell, molten carbonate fuel cell and direct methanol fuel cells.
TIME DIVISION MULTIPLEXING TECHNIQUE FOR COMMUNICATION SYSTEMHODECEDSIET
Time Division Multiplexing (TDM) is a method of transmitting multiple signals over a single communication channel by dividing the signal into many segments, each having a very short duration of time. These time slots are then allocated to different data streams, allowing multiple signals to share the same transmission medium efficiently. TDM is widely used in telecommunications and data communication systems.
### How TDM Works
1. **Time Slots Allocation**: The core principle of TDM is to assign distinct time slots to each signal. During each time slot, the respective signal is transmitted, and then the process repeats cyclically. For example, if there are four signals to be transmitted, the TDM cycle will divide time into four slots, each assigned to one signal.
2. **Synchronization**: Synchronization is crucial in TDM systems to ensure that the signals are correctly aligned with their respective time slots. Both the transmitter and receiver must be synchronized to avoid any overlap or loss of data. This synchronization is typically maintained by a clock signal that ensures time slots are accurately aligned.
3. **Frame Structure**: TDM data is organized into frames, where each frame consists of a set of time slots. Each frame is repeated at regular intervals, ensuring continuous transmission of data streams. The frame structure helps in managing the data streams and maintaining the synchronization between the transmitter and receiver.
4. **Multiplexer and Demultiplexer**: At the transmitting end, a multiplexer combines multiple input signals into a single composite signal by assigning each signal to a specific time slot. At the receiving end, a demultiplexer separates the composite signal back into individual signals based on their respective time slots.
### Types of TDM
1. **Synchronous TDM**: In synchronous TDM, time slots are pre-assigned to each signal, regardless of whether the signal has data to transmit or not. This can lead to inefficiencies if some time slots remain empty due to the absence of data.
2. **Asynchronous TDM (or Statistical TDM)**: Asynchronous TDM addresses the inefficiencies of synchronous TDM by allocating time slots dynamically based on the presence of data. Time slots are assigned only when there is data to transmit, which optimizes the use of the communication channel.
### Applications of TDM
- **Telecommunications**: TDM is extensively used in telecommunication systems, such as in T1 and E1 lines, where multiple telephone calls are transmitted over a single line by assigning each call to a specific time slot.
- **Digital Audio and Video Broadcasting**: TDM is used in broadcasting systems to transmit multiple audio or video streams over a single channel, ensuring efficient use of bandwidth.
- **Computer Networks**: TDM is used in network protocols and systems to manage the transmission of data from multiple sources over a single network medium.
### Advantages of TDM
- **Efficient Use of Bandwidth**: TDM all
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
International Conference on NLP, Artificial Intelligence, Machine Learning an...gerogepatton
International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
1. Frequency Response Analysis
(Bode & Polar Plot)
Presented by
Mr. C.S.Satheesh, M.E.,
Assistant Professor, Department of EEE,
Muthayammal Engineering College (Autonomous),
Namakkal (Dt), Rasipuram – 637408
MUTHAYAMMAL ENGINEERING COLLEGE
(An Autonomous Institution)
(Approved by AICTE, New Delhi, Accredited by NAAC, NBA & Affiliated to Anna University),
Rasipuram - 637 408, Namakkal Dist., Tamil Nadu, India.
2. Introduction - Frequency-Response Analysis
-By the term frequency response, we mean the steady-
state response of a system to a sinusoidal input.
- In frequency-response methods, we vary the frequency
of the input signal over a certain range and study the
resulting response.
5. Advantages of the frequency-response approach
1. We can use the data obtained from measurements on the
physical system without deriving its mathematical model.
2. Frequency-response tests are, in general, simple and can be
made accurately by use of readily available sinusoidal signal
generators and precise measurement equipment.
3. The transfer functions of complicated components can be
determined experimentally by frequency-response tests.
4. A system may be designed so that the effects of undesirable
noise are negligible and that such analysis and design can be
extended to certain nonlinear control systems.
6. The performance characteristics of a system in frequency domain are
measured in terms frequency domain specifications
Frequency domain specifications are
Resonant Peak Mr
Resonant Frequency ωr
Bandwidth ωh
Cut – off Rate
Gain margin Kg
Phase margin γ
Frequency Domain Specifications
7. Resonant Peak Mr
The maximum value of magnitude of closed loop transfer
function is called resonant peak.
A large resonant peak corresponds to a large overshoot in
transient response
For second order system
Frequency Domain Specifications
8. Resonant Frequency ωr
The frequency at which the resonant peak occurs is Resonant
Frequency .
This is related to frequency of oscillation in step response.
Indicative of speed of transient response for second order system
Frequency Domain Specifications
9. Bandwidth ωh
Range of frequencies for which normalized gain of the system is more
than -3dB
Frequency at which gain is -3dB is called cut-off frequency
Bandwidth is defined for closed loop system and transmit signals
whose frequency are less than cut – off frequency
Measure of ability of feedback system to reproduce i/p signal, noise
rejection characteristics & rise time
Large BW corresponds to small rise time or fast response
Frequency Domain Specifications
10. Cut – off Rate
•The slope of the log-magnitude curve near the cut off frequency is called
Cut – off Rate
•It Indicates the ability of the system to distinguish the signal from noise
Frequency Domain Specifications
11. Gain Margin Kg
The value of gain, to be added to system, in order to bring the
system to the verge of instability
•Gain Margin Kg is given by reciprocal of magnitude of open loop
transfer function at phase crossover frequency
•The frequency at which the phase of open loop transfer function is
180° is called the phase crossover frequency ωpc
Frequency Domain Specifications
12. The gain margin in dB is given by negative of dB magnitude of G(jω) at phase
crossover frequency Indicates the additional gain that can be provided to system
without affecting the stability of the system
EC8391
Frequency Domain Specificatins
13. Phase Margin γ
The additional phase lag to be added to the gain cross over frequency in
order to bring the system to the verge of instability
The gain cross over frequency ωgc is the frequency at which the magnitude
of open loop transfer function is unity (or is the frequency at which the dB
magnitude is zero)
Phase Margin γ is obtained by adding 180° to the phase angle φ of the
open loop transfer function at the gain crossover frequency
Indicates the additional phase lag that can be provided to system without
affecting the stability of the system
Frequency Domain Specifications
14. • Indicates the additional phase lag that can be provided to system
without affecting the stability of the system
• Note: The gain margin of second order system is infinite
Frequency Domain Specifications