This document describes using SimScape to model electrical systems mathematically. It provides instructions on building a simple model of an electrical circuit with a resistor, capacitor, inductor and voltage source. Key steps include selecting the appropriate blocks from SimScape libraries, connecting the blocks to represent the circuit, adding sources and scopes using Simulink blocks, and ensuring a solver configuration block is included. The model can then be simulated to observe the circuit behavior under varying conditions.
This document discusses the characteristics and operation of DC motors. It describes the construction and components of DC motors, including that the armature is usually located on the rotor and the field is on the stator. It also discusses separately excited DC motors and series DC motors, how their speed and torque can be controlled, and their applications.
Thevenin's Theorem,Mesh analysis and sine wave BasicIkhlas Rahman
This document provides an overview of Thevenin's theorem, mesh analysis, and sine waves. It discusses Thevenin's theorem and how any circuit can be simplified to a single voltage source and resistor. It then gives the steps to use Thevenin's theorem including finding the Thevenin resistance Rth and voltage Vth. An example problem demonstrates finding the Thevenin equivalent circuit. Mesh analysis is introduced as a method for solving planar circuits using Kirchhoff's voltage law. Key aspects of mesh analysis like identifying meshes and applying KVL are outlined. Finally, basic characteristics of sine waves like instantaneous value, peak amplitude, period, and frequency are defined.
This document discusses solving RLC series parallel circuits using Simulink. It introduces Kirchhoff's voltage law and differentiating the voltage equations to express the RLC response in general form. It provides a Simulink model for a series RLC circuit and instructs the reader to change component values and make a parallel RLC model. It also introduces the SimPowerSystems library for modeling electrical systems in Simulink and lists some commonly used blocks with an example circuit.
Two port network parameters, Z, Y, ABCD, h and g parameters, Characteristic impedance,
Image transfer constant, image and iterative impedance, network function, driving point and
transfer functions – using transformed (S) variables, Poles and Zeros.
Dc bridge types ,derivation and its applicationkaroline Enoch
The DC Bridge is used for measuring the unknown electrical resistance. This can be done by balancing the two legs of the bridge circuit. The value of one of the arm is known while the other of them is unknown
1. The document discusses the Routh-Hurwitz stability criterion, which is a test used to determine the stability of linear time-invariant systems by constructing a Routh array from the coefficients of the characteristic equation and analyzing it.
2. Special cases that can occur with the Routh array, such as a zero in the first column or an entire zero row, are explained along with their implications.
3. An important application of the Routh-Hurwitz criterion is determining the range of values for a system gain K that ensures stability.
THIS PPT IS MAINLY BASED ON ELECTRICAL CIRCUIT ANALYSIS PROBLEM AND THIS PPT ALSO SOLVED THEORETICALLY AND SOLVED BY USING THE MATLAB SOFTWARE AND THIS ALSO CONTAINS THE CODE AND RESULTS ARE ALSO THERE.SO THIS IS USEFUL
1) O documento discute as transformadas de Clarke e Park, que são usadas para representar sistemas trifásicos em coordenadas bifásicas;
2) A transformada de Clarke projeta as grandezas do sistema trifásico nos eixos alfa-beta, formando um sistema equivalente bifásico estacionário;
3) Já a transformada de Park gera um vetor girante que permite representar grandezas do sistema trifásico em coordenadas dq em rotação.
This document discusses the characteristics and operation of DC motors. It describes the construction and components of DC motors, including that the armature is usually located on the rotor and the field is on the stator. It also discusses separately excited DC motors and series DC motors, how their speed and torque can be controlled, and their applications.
Thevenin's Theorem,Mesh analysis and sine wave BasicIkhlas Rahman
This document provides an overview of Thevenin's theorem, mesh analysis, and sine waves. It discusses Thevenin's theorem and how any circuit can be simplified to a single voltage source and resistor. It then gives the steps to use Thevenin's theorem including finding the Thevenin resistance Rth and voltage Vth. An example problem demonstrates finding the Thevenin equivalent circuit. Mesh analysis is introduced as a method for solving planar circuits using Kirchhoff's voltage law. Key aspects of mesh analysis like identifying meshes and applying KVL are outlined. Finally, basic characteristics of sine waves like instantaneous value, peak amplitude, period, and frequency are defined.
This document discusses solving RLC series parallel circuits using Simulink. It introduces Kirchhoff's voltage law and differentiating the voltage equations to express the RLC response in general form. It provides a Simulink model for a series RLC circuit and instructs the reader to change component values and make a parallel RLC model. It also introduces the SimPowerSystems library for modeling electrical systems in Simulink and lists some commonly used blocks with an example circuit.
Two port network parameters, Z, Y, ABCD, h and g parameters, Characteristic impedance,
Image transfer constant, image and iterative impedance, network function, driving point and
transfer functions – using transformed (S) variables, Poles and Zeros.
Dc bridge types ,derivation and its applicationkaroline Enoch
The DC Bridge is used for measuring the unknown electrical resistance. This can be done by balancing the two legs of the bridge circuit. The value of one of the arm is known while the other of them is unknown
1. The document discusses the Routh-Hurwitz stability criterion, which is a test used to determine the stability of linear time-invariant systems by constructing a Routh array from the coefficients of the characteristic equation and analyzing it.
2. Special cases that can occur with the Routh array, such as a zero in the first column or an entire zero row, are explained along with their implications.
3. An important application of the Routh-Hurwitz criterion is determining the range of values for a system gain K that ensures stability.
THIS PPT IS MAINLY BASED ON ELECTRICAL CIRCUIT ANALYSIS PROBLEM AND THIS PPT ALSO SOLVED THEORETICALLY AND SOLVED BY USING THE MATLAB SOFTWARE AND THIS ALSO CONTAINS THE CODE AND RESULTS ARE ALSO THERE.SO THIS IS USEFUL
1) O documento discute as transformadas de Clarke e Park, que são usadas para representar sistemas trifásicos em coordenadas bifásicas;
2) A transformada de Clarke projeta as grandezas do sistema trifásico nos eixos alfa-beta, formando um sistema equivalente bifásico estacionário;
3) Já a transformada de Park gera um vetor girante que permite representar grandezas do sistema trifásico em coordenadas dq em rotação.
Power System Analysis was a core subject for Electrical & Electronics Engineering, Based On Anna University Syllabus. The Whole Subject was there in this document.
Share with it ur friends & Follow me for more updates.!
The document describes different minimal configuration options for PCS 7 systems with 1-3 PCs, including an ES/OS single-user system, an ES/OS client and OS server configuration, an ES, Master OS and Standby OS configuration, and an ES/Master OS and Standby OS configuration. It provides details on the functionality, required hardware and licensing, and step-by-step configuration instructions for setting up each of these minimal PCS 7 configurations with a reduced number of computers.
Chapter 02: Introduction to compute virtualizationSsendiSamuel
Cloud computing 1.0 focused on virtualization which today has become the foundation of cloud computing. This chapter focuses on the architecture and technologies involved in compute virtualization.
This document provides an overview of a PCS 7 system training course, including:
1) The course will introduce participants to the general workflow of a PCS 7 project from requirements to maintenance using a simulated automation of a 4 reactor plant.
2) The training will utilize one ES/OS, one AS with distributed I/O, and Industrial Ethernet as the system bus to simulate the automation based on available equipment.
3) Participants will work through tasks at different levels using the main PCS 7 engineering tools to create their own training project, with the process behavior simulated on the AS CPU.
Microservice-based Architecture on the Salesforce App Cloudpbattisson
This document discusses microservice architecture patterns that can be implemented on the Salesforce1 platform. It introduces three patterns: 1) the gateway pattern, where a gateway microservice handles calls to the Salesforce REST API; 2) the synchronous broker pattern, where a broker microservice uses a custom Apex REST endpoint to route messages synchronously; and 3) the asynchronous broker pattern, similar to the synchronous but using asynchronous communication. Code examples are provided and microservices on Salesforce1 are discussed. The presentation provides an overview of these patterns to implement microservice architecture using Salesforce.
S-parameters are used to analyze microwave circuits operating between 300MHz to 1000GHz. S-parameters relate the input and output traveling wave variables of network components using a scattering matrix. For a two-port network, the S-parameters relate the incident and reflected waves at each port. S11 and S22 represent reflection coefficients, while S12 and S21 represent transmission coefficients. Networks can be reciprocal if S12 = S21, and symmetrical if S11 = S22. LTSpice can be used to simulate S-parameters for two-port networks.
This document contains information about configuring and setting up the SIMATIC PCS 7 operator station (OS). It discusses single station and multi-station system configurations, and covers topics like the OS project editor, tag management, compiling the OS, and connecting the OS to automation systems. The document provides guidance on steps for configuring the OS, including setting computer properties, configuring layouts and message displays, defining process images, and checking the connection between the OS and automation systems.
A circuit consists of electrical elements connected in a closed loop to allow current flow. Key concepts include:
- Current is the flow of electric charge. Voltage is electrical potential difference and power is the rate of work done.
- Circuits have active elements like voltage and current sources that supply energy and passive elements like resistors, inductors and capacitors that receive energy.
- Kirchhoff's laws state that the algebraic sum of voltages around any loop is zero and the algebraic sum of currents at any node is zero.
- Resistors in series add, resistors in parallel calculate using reciprocal formula. Source transformations allow representing one source type as another while maintaining terminal characteristics.
Voltage Mode Control of Buck ConverterManish Kumar
Voltage Mode Control of Buck Converter (Dec 2012 - April 2013): The Buck-converter converts an input voltage into a lower output voltage, it is also called step-down converter. The buck converter is designed in continuous current conduction mode. To get the regulated output voltage, compensation mechanism using voltage mode control is used. This project involved simulation, design and hardware construction of voltage mode control of buck converter using PID compensator. The error signal is compared with a saw-tooth ramp voltage and desired PWM signal.
• Designed and developed a buck converter circuit using the PID Compensator to get a stable output of 5V-5A from an input of 12V.
• Circuit Simulation using ORCAD (PSpice); Stability analysis of the closed loop system for desired phase and
gain margin using MATLAB; Designed PID compensator by modifying the open loop buck converter circuit obtained by Simulation using ORCAD (PSpice). Implemented Compensator and PWM scheme using NXP LPC1768 Micro-controller.
Electrical analogous of mechanical translational systemKALPANA K
This document discusses electrical analogies of mechanical translational systems. There are two types of analogies: force-voltage and force-current. Force-voltage analogy models mechanical equations as electrical mesh equations. Force-current analogy models mechanical equations as electrical node equations. Two example problems are presented to illustrate drawing the analogous electrical circuits and verifying with mesh/node equations. Homework is assigned to practice drawing and verifying additional analogous circuits.
1. The document discusses symmetrical components, which allow representation of unbalanced three-phase quantities as the sum of three balanced components.
2. It introduces the positive, negative, and zero sequence components and the transformation matrix used to relate the symmetrical components to the original unbalanced quantities.
3. Symmetrical components are useful for simplifying analysis of unbalanced conditions like single line-to-ground faults in power systems. Sequence impedances can be used to model devices and transmission lines.
Factors considered for High Voltage Cable Joint design Shahab Khan
This document discusses key factors to consider for high voltage cable joint design. It outlines several important design factors, including the types of cables being joined, voltage levels, expected transient overvoltages, number of phases, dielectric strength of interfaces, choice of materials, and location of installation. The document emphasizes that cable joints are vulnerable points that require reliable designs to ensure good thermal performance, electrical stress control, and environmental and mechanical protection. Proper consideration of cable joint design factors is important for safety and long-term reliability of cable systems.
A janela principal do EPLAN é a janela principal onde são exibidos os principais elementos da interface do utilizador. Ela contém:
1. O menu principal no topo, que permite acessar as principais funções do programa.
2. A barra de ferramentas abaixo do menu, que oferece atalhos para funções comuns.
3. O Navegador de Páginas à esquerda, que lista todas as páginas do projeto.
4. A Pré-visualização Gráfica à esquerda, que mostra uma prévia da página selecionada no
This document provides an overview of Cisco's Unified Computing System (UCS). It discusses how server deployment has evolved from rackmount servers to blade servers to UCS. UCS aims to unify computing, networking, and storage infrastructure and simplify management. It consists of fabric interconnects, chassis, blades, and fabric extenders. Service profiles allow logical assignment of resources for stateless server provisioning and mobility. Use cases include deployment, upgrades, provisioning, high availability, and disaster recovery.
1. A three-phase fault occurred at Bus 5 in the power system. The fault current (IF) was calculated to be 5 pu based on the total fault impedance of 16.0j ohms as seen from Bus 5.
2. The fault current supplied by Generator 1 (IG1F) was calculated to be 2.1 pu, and by Generator 2 (IG2F) was calculated to be 8.0 pu.
3. The voltages during fault condition were calculated to be 0.68 pu at Bus 5 and 0.24 pu at Bus 3, indicating a voltage drop from the pre-fault voltage of 1.0 pu at all buses.
This document discusses key concepts related to alternating current (AC) fundamentals. It defines sinusoidal AC voltages and currents using mathematical expressions involving amplitude, angular frequency, time, and phase. It describes different waveform properties like instantaneous value, peak amplitude, peak-to-peak value, period, frequency, and phase difference. It also defines important AC metrics like root mean square (RMS) value, average value, form factor, and peak factor - and provides the analytical methods to calculate these values from a sinusoidal waveform's maximum and minimum values.
This document provides a summary of a seminar presentation on analyzing single phase AC circuits. The presentation covered various circuit elements in AC circuits including resistors, inductors, and capacitors in both series and parallel configurations. It discussed the concepts of impedance, phase relationships between voltage and current, and resonance. Resonance occurs when the inductive and capacitive reactances are equal, resulting in maximum current flow. The key topics were analyzing purely resistive, inductive, and capacitive circuits, and combinations using circuit laws and phasor diagrams.
This document discusses simulating a photovoltaic (PV) energy conversion system using MATLAB/Simulink and PLECS. It first describes the graphical environments of MATLAB/Simulink and PLECS. It then presents the simulation of a PV inverter system, developing models of the control system in MATLAB/Simulink and models of the power electronics plant using both MATLAB/Simulink transfer functions and PLECS circuit components. Simulation results are provided to compare the two approaches.
Simulink software allows users to model, simulate, and analyze dynamic systems. It provides a graphical interface for building models as block diagrams using premade blocks or custom blocks. Models can represent systems from various industries and can be linear or nonlinear, continuous or discrete. Simulink is integrated with MATLAB, allowing users to define inputs, store outputs, and perform analyses.
Power System Analysis was a core subject for Electrical & Electronics Engineering, Based On Anna University Syllabus. The Whole Subject was there in this document.
Share with it ur friends & Follow me for more updates.!
The document describes different minimal configuration options for PCS 7 systems with 1-3 PCs, including an ES/OS single-user system, an ES/OS client and OS server configuration, an ES, Master OS and Standby OS configuration, and an ES/Master OS and Standby OS configuration. It provides details on the functionality, required hardware and licensing, and step-by-step configuration instructions for setting up each of these minimal PCS 7 configurations with a reduced number of computers.
Chapter 02: Introduction to compute virtualizationSsendiSamuel
Cloud computing 1.0 focused on virtualization which today has become the foundation of cloud computing. This chapter focuses on the architecture and technologies involved in compute virtualization.
This document provides an overview of a PCS 7 system training course, including:
1) The course will introduce participants to the general workflow of a PCS 7 project from requirements to maintenance using a simulated automation of a 4 reactor plant.
2) The training will utilize one ES/OS, one AS with distributed I/O, and Industrial Ethernet as the system bus to simulate the automation based on available equipment.
3) Participants will work through tasks at different levels using the main PCS 7 engineering tools to create their own training project, with the process behavior simulated on the AS CPU.
Microservice-based Architecture on the Salesforce App Cloudpbattisson
This document discusses microservice architecture patterns that can be implemented on the Salesforce1 platform. It introduces three patterns: 1) the gateway pattern, where a gateway microservice handles calls to the Salesforce REST API; 2) the synchronous broker pattern, where a broker microservice uses a custom Apex REST endpoint to route messages synchronously; and 3) the asynchronous broker pattern, similar to the synchronous but using asynchronous communication. Code examples are provided and microservices on Salesforce1 are discussed. The presentation provides an overview of these patterns to implement microservice architecture using Salesforce.
S-parameters are used to analyze microwave circuits operating between 300MHz to 1000GHz. S-parameters relate the input and output traveling wave variables of network components using a scattering matrix. For a two-port network, the S-parameters relate the incident and reflected waves at each port. S11 and S22 represent reflection coefficients, while S12 and S21 represent transmission coefficients. Networks can be reciprocal if S12 = S21, and symmetrical if S11 = S22. LTSpice can be used to simulate S-parameters for two-port networks.
This document contains information about configuring and setting up the SIMATIC PCS 7 operator station (OS). It discusses single station and multi-station system configurations, and covers topics like the OS project editor, tag management, compiling the OS, and connecting the OS to automation systems. The document provides guidance on steps for configuring the OS, including setting computer properties, configuring layouts and message displays, defining process images, and checking the connection between the OS and automation systems.
A circuit consists of electrical elements connected in a closed loop to allow current flow. Key concepts include:
- Current is the flow of electric charge. Voltage is electrical potential difference and power is the rate of work done.
- Circuits have active elements like voltage and current sources that supply energy and passive elements like resistors, inductors and capacitors that receive energy.
- Kirchhoff's laws state that the algebraic sum of voltages around any loop is zero and the algebraic sum of currents at any node is zero.
- Resistors in series add, resistors in parallel calculate using reciprocal formula. Source transformations allow representing one source type as another while maintaining terminal characteristics.
Voltage Mode Control of Buck ConverterManish Kumar
Voltage Mode Control of Buck Converter (Dec 2012 - April 2013): The Buck-converter converts an input voltage into a lower output voltage, it is also called step-down converter. The buck converter is designed in continuous current conduction mode. To get the regulated output voltage, compensation mechanism using voltage mode control is used. This project involved simulation, design and hardware construction of voltage mode control of buck converter using PID compensator. The error signal is compared with a saw-tooth ramp voltage and desired PWM signal.
• Designed and developed a buck converter circuit using the PID Compensator to get a stable output of 5V-5A from an input of 12V.
• Circuit Simulation using ORCAD (PSpice); Stability analysis of the closed loop system for desired phase and
gain margin using MATLAB; Designed PID compensator by modifying the open loop buck converter circuit obtained by Simulation using ORCAD (PSpice). Implemented Compensator and PWM scheme using NXP LPC1768 Micro-controller.
Electrical analogous of mechanical translational systemKALPANA K
This document discusses electrical analogies of mechanical translational systems. There are two types of analogies: force-voltage and force-current. Force-voltage analogy models mechanical equations as electrical mesh equations. Force-current analogy models mechanical equations as electrical node equations. Two example problems are presented to illustrate drawing the analogous electrical circuits and verifying with mesh/node equations. Homework is assigned to practice drawing and verifying additional analogous circuits.
1. The document discusses symmetrical components, which allow representation of unbalanced three-phase quantities as the sum of three balanced components.
2. It introduces the positive, negative, and zero sequence components and the transformation matrix used to relate the symmetrical components to the original unbalanced quantities.
3. Symmetrical components are useful for simplifying analysis of unbalanced conditions like single line-to-ground faults in power systems. Sequence impedances can be used to model devices and transmission lines.
Factors considered for High Voltage Cable Joint design Shahab Khan
This document discusses key factors to consider for high voltage cable joint design. It outlines several important design factors, including the types of cables being joined, voltage levels, expected transient overvoltages, number of phases, dielectric strength of interfaces, choice of materials, and location of installation. The document emphasizes that cable joints are vulnerable points that require reliable designs to ensure good thermal performance, electrical stress control, and environmental and mechanical protection. Proper consideration of cable joint design factors is important for safety and long-term reliability of cable systems.
A janela principal do EPLAN é a janela principal onde são exibidos os principais elementos da interface do utilizador. Ela contém:
1. O menu principal no topo, que permite acessar as principais funções do programa.
2. A barra de ferramentas abaixo do menu, que oferece atalhos para funções comuns.
3. O Navegador de Páginas à esquerda, que lista todas as páginas do projeto.
4. A Pré-visualização Gráfica à esquerda, que mostra uma prévia da página selecionada no
This document provides an overview of Cisco's Unified Computing System (UCS). It discusses how server deployment has evolved from rackmount servers to blade servers to UCS. UCS aims to unify computing, networking, and storage infrastructure and simplify management. It consists of fabric interconnects, chassis, blades, and fabric extenders. Service profiles allow logical assignment of resources for stateless server provisioning and mobility. Use cases include deployment, upgrades, provisioning, high availability, and disaster recovery.
1. A three-phase fault occurred at Bus 5 in the power system. The fault current (IF) was calculated to be 5 pu based on the total fault impedance of 16.0j ohms as seen from Bus 5.
2. The fault current supplied by Generator 1 (IG1F) was calculated to be 2.1 pu, and by Generator 2 (IG2F) was calculated to be 8.0 pu.
3. The voltages during fault condition were calculated to be 0.68 pu at Bus 5 and 0.24 pu at Bus 3, indicating a voltage drop from the pre-fault voltage of 1.0 pu at all buses.
This document discusses key concepts related to alternating current (AC) fundamentals. It defines sinusoidal AC voltages and currents using mathematical expressions involving amplitude, angular frequency, time, and phase. It describes different waveform properties like instantaneous value, peak amplitude, peak-to-peak value, period, frequency, and phase difference. It also defines important AC metrics like root mean square (RMS) value, average value, form factor, and peak factor - and provides the analytical methods to calculate these values from a sinusoidal waveform's maximum and minimum values.
This document provides a summary of a seminar presentation on analyzing single phase AC circuits. The presentation covered various circuit elements in AC circuits including resistors, inductors, and capacitors in both series and parallel configurations. It discussed the concepts of impedance, phase relationships between voltage and current, and resonance. Resonance occurs when the inductive and capacitive reactances are equal, resulting in maximum current flow. The key topics were analyzing purely resistive, inductive, and capacitive circuits, and combinations using circuit laws and phasor diagrams.
This document discusses simulating a photovoltaic (PV) energy conversion system using MATLAB/Simulink and PLECS. It first describes the graphical environments of MATLAB/Simulink and PLECS. It then presents the simulation of a PV inverter system, developing models of the control system in MATLAB/Simulink and models of the power electronics plant using both MATLAB/Simulink transfer functions and PLECS circuit components. Simulation results are provided to compare the two approaches.
Simulink software allows users to model, simulate, and analyze dynamic systems. It provides a graphical interface for building models as block diagrams using premade blocks or custom blocks. Models can represent systems from various industries and can be linear or nonlinear, continuous or discrete. Simulink is integrated with MATLAB, allowing users to define inputs, store outputs, and perform analyses.
This document discusses modeling and simulating physical systems using Simulink. It provides two case studies:
1) A mechanical spring-mass-damper system is modeled using differential equations and simulated in Simulink. Damping is adjusted to produce underdamped, critically damped and overdamped responses.
2) A simple pendulum is modeled using nonlinear differential equations which are linearized and simulated in Simulink. The mass is displaced from equilibrium and the response is observed.
A SYSTEMC/SIMULINK CO-SIMULATION ENVIRONMENT OF THE JPEG ALGORITHMVLSICS Design
In the past decades, many factors have been continuously increasing like the functionality of embedded systems as well as the time-to-market pressure has been continuously increasing. Simulation of an entire system including both hardware and software from early design stages is one of the effective approaches to improve the design productivity. A large number of research efforts on hardware/software (HW/SW) co-simulation have been made so far. Real-time operating systems have become one of the important components in the embedded systems. However, in order to validate function of the entire system, this system has to be simulated together with application software and hardware. Indeed, traditional methods of verification have proven to be insufficient for complex digital systems. Register transfer level test-benches have become too complex to manage and too slow to execute. New methods and verification techniques began to emerge over the past few years. Highlevel test-benches, assertion-based verification, formal methods, hardware verification languages are just a few examples of the intense research activities driving the verification domain.
The document discusses the NI LabVIEW Multisim API Toolkit, which provides over 120 functions for automating circuit simulation and analysis from within the LabVIEW environment. It allows users to access simulated measurements for further analysis, correlate simulated and real measurements, and use simulated measurements for testing. Two examples are provided that demonstrate using the toolkit to automatically calculate efficiency by sweeping frequency values for a buck converter, and automating simulations of a signal conditioning circuit with different op-amps and input signals.
This paper presents a new simulator used to distribute and execute real-time simulations: the RT-LAB, developed by opal-RT technologies (Montreal, Canada). One of its essential characteristics is the perfect integration with MATLAB/Simulink. The RT-LAB allows the conversion of Simulink models in real time via real-time workshop (RTW) and their execution on one or more processors. In this context, the paper focuses on the RT-LAB real-time simulation as a complement to the MATLAB/Simulink environment, which has been used to perform the simulation of the Flywheel energy storage system (FESS -variable speed wind generation (VSWG) assembly. The purpose of employing a fairly new real-time platform (RT-LAB OP -5600) is to reduce the test and prototype time. This application will be executed on each element of our model that was previously developed under MATLAB/Simulink. The real-time simulation results are observed in the workstation.
Introduction to Modeling and Simulations.pptQasimAli493018
This document provides an introduction and overview of a course on dynamic systems and control (DSC). The course aims to teach students how to model, analyze, and design physical systems like mechanical, electrical, and fluid systems. It will cover modeling dynamic systems using differential equations, analyzing system response using analytical and numerical methods, and introducing feedback control systems. Students will learn through both theoretical discussions and real-world examples from industry. The course outline indicates it will cover topics like modeling different physical systems, dynamic response analysis in time and frequency domains, and feedback control design.
Simulink is a MATLAB toolbox that is used for modeling, simulating, and analyzing multi-domain dynamic systems. It provides a graphical interface for building models as block diagrams using customizable block libraries. Models can be simulated, and simulation results can be analyzed in MATLAB. Simulink supports system-level design, simulation, automatic code generation, and testing and verification of embedded systems. It integrates with other MATLAB tools and third-party products for various applications like state machine design, embedded code generation, and hardware-in-the-loop testing.
This document discusses using System Functions (S-functions) in Simulink as an effective tool for implementing customized algorithms. S-functions allow incorporating custom MATLAB, C, or Fortran code into Simulink models. The document presents results of implementing a voltage disturbance detection algorithm both with an S-function and a MATLAB code function. The S-function implementation was found to provide more accurate results and faster evaluation compared to the MATLAB code function approach. Graphs of the root mean square voltage values showed less variation and faster updating using the S-function versus the MATLAB code function implementation.
This document provides instructions for a lab exercise on DC circuit simulations and modeling. The objectives are to:
1. Model a generic BJT device including parasitics and save it as a sub-circuit.
2. Perform DC simulations to determine the circuit's performance characteristics and calculate bias resistor values.
3. Build a biased circuit based on the DC simulation results and test the biased network.
The lab exercise will establish a foundational BJT circuit that can be used as a sub-circuit for amplifier designs in subsequent lab exercises.
SimScale is a web-based simulation platform that allows engineers to perform simulations like finite element analysis, computational fluid dynamics, and thermodynamics directly in their web browser. It has over 65,000 users worldwide and offers fully automated meshing and solving workflows. The document provides overviews of SimScale's modeling, analysis, and post-processing capabilities as well as its pricing plans starting at €170 per month.
SimScale is a web-based simulation platform that allows engineers to perform simulations like finite element analysis, computational fluid dynamics, and thermodynamics directly in their web browser. It has over 65,000 users worldwide and offers fully automated meshing and solving workflows. The document provides overviews of SimScale's features for structural analysis, fluid analysis, and thermal analysis and discusses its pricing plans and security measures to protect user data.
This document describes a methodology for simulating heterogeneous embedded systems that include hardware, software, and electromechanical parts. Interfaces were developed to allow a VHDL simulator to communicate with a physical systems simulator and application programs. The interfaces use the C language links of the simulators to establish communication channels and exchange commands/parameter values between the simulated parts in a chained master/slave synchronization scheme. This unified simulation environment allows designers to validate the behavior of the entire system early in the design process before implementing any of its parts.
MODELLING, ANALYSIS AND SIMULATION OF DYNAMIC SYSTEMS USING CONTROL TECHNIQUE...shivamverma394
This document discusses using MATLAB and Simulink to model, analyze, and simulate dynamic systems and control techniques. It begins by explaining how to use MATLAB to obtain transfer functions from mathematical models and analyze stability. Next, it describes using Simulink to build models with blocks and implement PID controllers. Finally, it provides examples of simulating an open-loop and closed-loop spring-mass-damper system in MATLAB and Simulink to analyze the system response.
Struggling with MATLAB assignments? Our website offers top-quality MATLAB assignment help. Our expert team provides accurate solutions and detailed explanations. We ensure timely delivery and offer 24/7 support. Affordable pricing makes our services accessible to students and professionals. Don't stress over coding challenges—visit our website today!
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The document presents the modeling and real-time simulation of an induction motor using RT-LAB software. RT-LAB allows converting Simulink models to real-time simulations that can run across multiple processors. The paper discusses the mathematical model of an induction motor and its implementation in RT-LAB. Two models are presented - one where data is transferred during simulation using OpComm blocks, and another where data is recorded using OpWriteFile blocks and transferred after simulation. Simulation results are presented for an induction motor with described parameters running on an RT-LAB configuration.
Rhapsody and MATLAB/Simulink have several integration points that allow design and simulation of cyber-physical systems. This includes generating Simulink models from Rhapsody, creating S-functions for use in Simulink, and evaluating parametric constraints using MATLAB. Bringing Simulink models into the Rhapsody Design Manager enables traceability and collaboration across the system design lifecycle.
Spark Summit EU talk by Mikhail Semeniuk Hollin WilkinsSpark Summit
MLeap and Combust.ML allow machine learning pipelines developed in Spark to be deployed directly to production by serializing them to a common format and executing them outside of Spark. This addresses the common problem of data scientists developing models in Spark that then need to be rewritten by engineers for production. It also allows pipelines to be deployed via REST APIs with low latency. Benchmark tests showed average response times of 14ms for a linear regression pipeline and 24ms for a random forest pipeline on a MacBook Pro. Future work includes supporting more Spark and scikit-learn transformers and unifying model libraries with Spark.
A common need in system architecture design is to verify that if the architect is correct and can satisfy its requirements.
Execution of system architect model means to interact with state machines to test system’s control logic. It can verify if the logical sequences of functions and interfaces in different scenarios are desired.
However, only sequence itself is not enough to verify its consequence or output. So we need each function to do what it is supposed to do during model execution to verify its output, and that is what we called “simulation”.
This presentation introduced how to embed Python or MATLAB® codes inside functions to do “simulation” within Capella.
Similar to 03 1 mathematical modeling using sim-scape_electrical (20)
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2. Experiment 3: Mathematical Modelling Using SimScape
Automatic Control Systems 1
Dr. Zaer Abo-Hammour
1. Model and simulate MultiDomain Physical Systems
Simscape provides an environment for modeling and simulating physical systems spanning
mechanical, electrical, hydraulic, and other physical domains. It provides fundamental building blocks
from these domains that you can assemble into models of physical components, such as electric motors,
inverting op-amps, hydraulic valves, and ratchet mechanisms. Because Simscape components use
physical connections, your models match the structure of the system you are developing.
Simscape models can be used to develop control systems and test system-level performance. You
can extend the libraries using the MATLAB®
based Simscape language, which enables text-based
authoring of physical modeling components, domains, and libraries. You can parameterize your
models using MATLAB variables and expressions, and design control systems for your physical
system in Simulink®
. To deploy your models to other simulation environments, including hardware-
in-the-loop (HIL) systems, Simscape supports C-code generation.
2. Key Features
Single environment for modeling and simulating mechanical, electrical, hydraulic, thermal, and
other multidomain physical systems
Libraries of physical modeling blocks and mathematical elements for developing custom
components
MATLAB based Simscape language, enabling text-based authoring of physical modeling
components, domains, and libraries
Physical units for parameters and variables, with all unit conversions handled automatically
Ability to simulate models that include blocks from related physical modeling products without
purchasing those products
Support for C-code generation
3. Simscape Block Libraries
Simscape block library contains two libraries that belong to the Simscape™ product:
Foundation library — Contains basic hydraulic, pneumatic, mechanical, electrical, magnetic,
thermal, thermal liquid, and physical signal blocks, organized into sublibraries according to
technical discipline and function performed
Utilities library — Contains essential environment blocks for creating Physical Networks
models
In addition, if you have installed any of the add-on products of the Physical Modeling family, you will
see the corresponding libraries under the main Simscape library.
Simscape Foundation libraries contain a comprehensive set of basic elements and building blocks,
such as:
Mechanical building blocks for representing one-dimensional translational and rotational
motion
Electrical building blocks for representing electrical components and circuits
Magnetic building blocks that represent electromagnetic components
3. Experiment 3: Mathematical Modelling Using SimScape
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Dr. Zaer Abo-Hammour
Hydraulic building blocks that model fundamental hydraulic effects and can be combined to
create more complex hydraulic components
Pneumatic building blocks that model fundamental pneumatic effects based on the ideal gas law
Thermal building blocks that model fundamental thermal effects
Thermal liquid building blocks that model fundamental thermodynamic effects in liquids
Physical Signals block library that lets you perform math operations on physical signals, and
graphically enter equations inside the physical network
Using the elements contained in these Foundation libraries, you can create more complex components
that span different physical domains. You can then group this assembly of blocks into a subsystem and
parameterize it to reuse and share these components.
In addition to Foundation libraries, there is also a Simscape Utilities library, which contains utility
blocks, such as:
Solver Configuration block, which contains parameters relevant to numerical algorithms for
Simscape simulations. Each Simscape diagram (or each topologically distinct physical network
in a diagram) must contain a Solver Configuration block.
Simulink-PS Converter block and PS-Simulink Converter block, to connect Simscape and
Simulink® blocks. Use the Simulink-PS Converter block to connect Simulink outports to
Physical Signal inports. Use the PS-Simulink Converter block to connect Physical Signal
outports to Simulink inports.
For examples of using these blocks in a Simscape model, see the tutorial Creating and Simulating a
Simple Model.
You can combine all these blocks in your Simscape diagrams to model physical systems. You can also
use the basic Simulink blocks in your diagrams, such as sources or scopes. See Connecting Simscape
Diagrams to Simulink Sources and Scopes for more information on how to do this.
Simscape block libraries contain a comprehensive selection of blocks that represent engineering
components such as valves, resistors, springs, and so on. These prebuilt blocks, however, may not be
sufficient to address your particular engineering needs. When you need to extend the existing block
libraries, use the Simscape language to define customized components, or even new physical domains,
as textual files. Then convert your textual components into libraries of additional Simscape blocks that
you can use in your model diagrams.
Figure 3.1: SimScape Library
4. Experiment 3: Mathematical Modelling Using SimScape
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Dr. Zaer Abo-Hammour
Figure 3.2: SimScape Library
4. How Simscape Simulation Works
Simscape software gives you multiple ways to simulate and analyze physical systems in the Simulink
environment. Running a physical model simulation is similar to simulating any Simulink model. It
entails setting various simulation options, starting the simulation, and viewing the simulation results.
This topic describes various aspects of simulation specific to Simscape models. For specifics of
simulating and analyzing with individual Simscape add-on products, refer to the documentation for
those individual add-on products.
The flow chart in figure 3.3 presents the Simscape simulation sequence.
The flow chart consists of the following major phases:
1. Model Validation
2. Network Construction
3. Equation Construction
4. Initial Conditions Computation
5. Transient Initialization
6. Transient Solve
5. Experiment 3: Mathematical Modelling Using SimScape
Automatic Control Systems 4
Dr. Zaer Abo-Hammour
Figure 3.3: flow chart presents the Simscape
4.1Model Validation
The Simscape solver first validates the model configuration and checks your data entries from the
block dialog boxes.
All Simscape blocks in a diagram must be connected into one or more physical networks. Unconnected
Conserving ports are not allowed.
Each topologically distinct physical network in a diagram requires exactly one Solver
Configuration block.
If your model contains hydraulic elements, each topologically distinct hydraulic circuit in a
diagram must connect to a Custom Hydraulic Fluid block (or Hydraulic Fluid block, available
with SimHydraulics® block libraries). These blocks define the fluid properties that act as
global parameters for all the blocks that connect to the hydraulic circuit. If no hydraulic fluid
block is attached to a loop, the hydraulic blocks in this loop use the default fluid. However,
more than one hydraulic fluid block in a loop generates an error.
Similarly, if your model contains pneumatic elements, default gas properties for a pneumatic
network are for dry air and ambient conditions of 101325 Pa and 20 degrees Celsius. If you
attach a Gas Properties block to a pneumatic circuit, you can change gas properties and ambient
6. Experiment 3: Mathematical Modelling Using SimScape
Automatic Control Systems 5
Dr. Zaer Abo-Hammour
conditions for all the blocks connected to the circuit. However, more than one Gas Properties
block in a pneumatic circuit generates an error.
Signal units specified in a Simulink-PS Converter block must match the input type expected
by the Simscape block connected to it. For example, when you provide the input signal for an
Ideal Angular Velocity Source block, specify angular velocity units, such as rad/s orrpm, in the
Simulink-PS Converter block, or leave it unitless. Similarly, units specified in a PS-Simulink
Converter block must match the type of physical signal provided by the Simscape block
outport.
4.2Network Construction
After validating the model, the Simscape solver constructs the physical network based on the following
principles:
Two directly connected Conserving ports have the same values for all their Across variables (such
as voltage or angular velocity).
Any Through variable (such as current or torque) transferred along the Physical connection line is
divided among the multiple components connected by the branches. For each Through variable,
the sum of all its values flowing into a branch point equals the sum of all its values flowing out.
4.3Equation Construction
Based on the network configuration, the parameter values in the block dialog boxes, and the global
parameters defined by the fluid properties, if applicable, the Simscape solver constructs the system of
equations for the model.
These equations contain system variables of the following types:
Dynamic : Time derivatives of these variables appear in equations. Dynamic, or differential,
variables add dynamics to the system and require the solver to use numerical integration to
compute their values. Dynamic variables can produce either independent or dependent states
for simulation.
Algebraic : Time derivatives of these variables do not appear in equations. These variables
appear in algebraic equations but add no dynamics, and this typically occurs in physical
systems due to conservation laws, such as conservation of mass and energy. The states of
algebraic variables are always dependent on dynamic variables, other algebraic variables, or
inputs.
The solver then performs the analysis and eliminates variables that are not needed to solve the system
of equations. After variable elimination, the remaining variables (algebraic, dynamic dependent, and
dynamic independent) get mapped to Simulink state vector of the model.
7. Experiment 3: Mathematical Modelling Using SimScape
Automatic Control Systems 6
Dr. Zaer Abo-Hammour
4.4 Initial Conditions Computation
The Simscape solver computes the initial conditions only once, at the beginning of simulation
(t = 0). In the Solver Configuration block dialog box, the default is that the Start simulation from steady
state check box is not selected. If it is selected in your model, see Finding an Initial Steady State.
The solver computes the initial conditions by finding initial values for all the system variables that
exactly satisfy all the model equations. You can affect the initial conditions computation by block-
level variable initialization, that is, by specifying the priority and target initial values on
the Variables tab of the block dialog boxes.
The values you specify during block-level variable initialization are not the actual values of the
respective variables, but rather their target values at the beginning of simulation (t = 0). Depending on
the results of the solve, some of these targets may or may not be satisfied. The solver tries to satisfy
the high-priority targets first, then the low-priority ones:
At first, the solver tries to find a solution where all the high-priority variable targets are met
exactly, and the low-priority targets are approximated as closely as possible. If the solution is
found during this stage, it satisfies all the high-priority targets. Some of the low-priority targets
might also be met exactly, the others are approximated.
If the solver cannot find a solution that exactly satisfies all the high-priority targets, it issues a
warning and enters the second stage, where High priority is relaxed to Low. That is, the solver tries to
find a solution by approximating both the high-priority and the low-priority targets as closely as
possible.
After you initialize the block variables and prior to simulating the model, you can open the Variable
Viewer to see which of the variable targets have been satisfied. For more information on block-level
variable initialization, see Variable Initialization.
Finding an Initial Steady State
When you select the Start simulation from steady state check box, the solver attempts to find the steady
state that would result if the inputs to the system were held constant for a long enough time, starting
from the initial state obtained from the initial conditions computation just described. If the steady-state
solve succeeds, the state found is some steady state (within tolerance), but not necessarily the state
expected from the given initial conditions. Steady state means that the system variables are no longer
changing with time. Simulation then starts from this steady state.
A model can have more than one steady state. In this case, the solver selects the steady-state solution
that is consistent with the variable targets specified during block-level variable initialization.
4.5Transient Initialization
After computing the initial conditions, or after a subsequent event (such as a discontinuity resulting,
for example, from a valve opening, or from a hard stop), the Simscape solver performs transient
initialization. Transient initialization fixes all dynamic variables and solves for algebraic variables and
derivatives of dynamic variables. The goal of transient initialization is to provide a consistent set of
initial conditions for the next phase, transient solve.
8. Experiment 3: Mathematical Modelling Using SimScape
Automatic Control Systems 7
Dr. Zaer Abo-Hammour
4.6Transient Solve
Finally, the Simscape solver performs transient solve of the system of equations. In transient solve,
continuous differential equations are integrated in time to compute all the variables as a function of
time.
The solver continues to perform the simulation according to the results of the transient solve until the
solver encounters an event, such as a zero crossing or discontinuity. The event may be within the
physical network or elsewhere in the Simulink model. If the solver encounters an event, the solver
returns to the phase of transient initialization, and then back to transient solve. This cycle continues
until the end of simulation.
5. Electrical System Using SimScape
In this example, you are going to model an electrical system and observe its behavior under various
conditions. This tutorial illustrates the essential steps to building a physical model and makes you
familiar with using the basic SimScape blocks.
The figure 3.4 shows a simple model of an electrical circuit. It consists of a Resistance, Capacitor and
Inductor, which is supplied by a Voltage source.
Figure 3.4: Electrical Circuit
Modeling of System
To create an equivalent Simscape diagram, follow these steps:
1. Open the Simulink® Library Browser, as described in Simscape Block Libraries.
2. Create a new model. To do this, from the top menu bar of the Library Browser,
select File > New > Model. The software creates an empty model in memory and displays it in
a new model editor window.
3. Open the Simscape > Foundation Library > Electrical Element Elements library as shown in
figure 3.5.
4. Drag the Mass, Translational Spring, Translational Damper, and two Mechanical Translational
Reference blocks into the model window.
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5. Orient the blocks as shown in the figure 3.6. To rotate a block, select it and press Ctrl+R.
6. Connect the Resistor, Capacitor, and Inductor blocks to one of the Electrical Reference Ground
blocks as shown in figure 3.7.
Figure 3.5: Electrical Element, step 3
Figure 3.6: Selected Element, step 5
10. Experiment 3: Mathematical Modelling Using SimScape
Automatic Control Systems 9
Dr. Zaer Abo-Hammour
Figure 3.7: Connect the element, step6
7. To add the representation of the force acting on the mass, open the Simscape > Foundation
Library > Electrical > Electrical Sources library figure 3.8, and add the Controlled Voltage
Source block to your diagram as figure 3.9.
Figure 3.8: Electrical Source, step7
11. Experiment 3: Mathematical Modelling Using SimScape
Automatic Control Systems 10
Dr. Zaer Abo-Hammour
Figure 3.9: The block of circuit after add the voltage source, step7
8. Add the sensor to measure speed and position of the mass. Place the Voltage and current
Sensors block from the Electrical Sensors library figure 3.10 into your diagram and connect it
as shown in figure 3.11.
Figure 3.10: Electrical Sensor
12. Experiment 3: Mathematical Modelling Using SimScape
Automatic Control Systems 11
Dr. Zaer Abo-Hammour
Figure 3.11: Electrical circuit using SimScape
9. Now you need to add the sources and scopes. They are found in the regular Simulink libraries.
Open the Simulink > Sources library and copy the Signal Builder block into the model. Then
open the Simulink > Sinks library and copy two Scope blocks..
10. Every time you connect a Simulink source or scope to a Simscape diagram, you have to use an
appropriate converter block, to convert Simulink signals into physical signals and vice versa.
Open the Simscape > Utilities library figure 3.12 and copy a Simulink-PS Converter block and
two PS-Simulink Converter blocks into the model. Connect the blocks as shown in figure 3.13.
11. Each topologically distinct physical network in a diagram requires exactly one Solver
Configuration block, found in the Simscape > Utilities library figure 3.12. Copy this block into
your model and connect it to the circuit by creating a branching point and connecting it to the
only port of the Solver Configuration block. Your diagram now should look like figure 3.13.
Figure 3.12: Simscape Utilities Library
13. Experiment 3: Mathematical Modelling Using SimScape
Automatic Control Systems 12
Dr. Zaer Abo-Hammour
Figure 3.13: Full Simscape Representation for Electrical Circuit
The Simulation Result
Figure 3.14: The Simulation Result
14. Experiment 3: Mathematical Modelling Using SimScape
Automatic Control Systems 13
Dr. Zaer Abo-Hammour
References . . . .
1) http://www.mathworks.com/help/index.html
2) Farid Golnaraghi, Benjamin C.Kuo; Automatic Control Systems; Ninth Edition
3) Norman S.Nise; Control Systems Engineering; Sixth Edition
4) Richard C.Dorf, Robert H.Bishop; Modern Control Systems; Twelfth Edition.