Kooperativer Bibliotheksverbund

UID:

Format: 1 online resource (264 pages)

ISBN: 0-12-814006-2 , 0-12-814005-4

Note: Front Cover -- Dynamic Estimation and Control of Power Systems -- Copyright -- Contents -- About the Authors -- Preface -- List of Figures -- List of Tables -- List of Abbreviations -- List of Symbols -- 1 Introduction -- 1.1 State of the art -- 1.1.1 Energy management system -- 1.1.2 Phasor measurement units (PMUs) -- 1.1.3 Flexible AC transmission system (FACTS) -- 1.1.4 Wide-area measurements and wide-area control -- 1.1.5 Dynamic state estimation (DSE) and dynamic control -- 1.2 Static state estimation (SSE) versus dynamic state estimation (DSE) -- 1.3 Challenges to power system dynamic estimation and control -- 1.4 Book organization -- 2 Power System Modeling, Simulation, and Control Design -- 2.1 Power system model -- 2.1.1 Generating unit: a generator and its excitation system -- 2.1.2 Power system stabilizers (PSSs) -- 2.1.3 FACTS control devices -- 2.1.3.1 Thyristor-controlled series capacitor (TCSC) -- 2.1.3.2 Static VAR compensator (SVC) -- 2.1.3.3 Thyristor-controlled phase angle regulator (TCPAR) -- 2.1.4 Loads, network interface, and network equations -- 2.2 Power system simulation and analysis -- 2.2.1 Load ow analysis -- 2.2.2 Initialization and time-domain simulation -- 2.2.3 Linear analysis and basics of control design -- 2.2.3.1 System linearization -- 2.2.3.2 Eigenvalues -- 2.2.3.3 Participation factor and residue -- 2.2.3.4 Controllable devices, controllers, inputs, and outputs: examples -- 2.2.3.5 Electromechanical modes -- 2.2.3.6 Interarea modes and mode shapes -- 2.2.3.7 Residue-based linear control design -- 3 Centralized Dynamic Estimation and Control -- 3.1 NCPS modeling with output feedback -- 3.1.1 State space representation of power system -- 3.1.2 Sensors and actuators -- 3.1.3 Communication protocol, packet delay, and packet dropout -- 3.1.4 Controller -- 3.1.5 Estimator -- 3.1.5.1 State prediction step. , 3.1.5.2 Measurement prediction and Kalman update step -- 3.2 Closed-loop stability and damping response -- 3.2.1 Stability analysis framework of a jump linear system -- 3.2.1.1 LMIs for mean-square stability -- 3.2.1.2 LMIs for adequate damping response -- 3.2.2 Physical signi cance of the developed LMIs -- 3.3 Case study: 68-bus 16-machine 5-area NCPS -- 3.3.1 System description -- 3.3.2 Simulation results and discussion -- 3.3.2.1 Operating condition 1 (base case) -- 3.3.2.2 Operating condition 2 -- 3.3.2.3 Effect of sampling period -- 3.3.2.4 Robustness -- 3.4 Limitations -- 3.5 Summary -- 4 Decentralized Dynamic Estimation Using PMUs -- 4.1 Problem statement and methodology in brief -- 4.1.1 Problem statement -- 4.1.2 Methodology -- 4.2 Power system modeling and discrete DAEs -- 4.2.1 Generators -- 4.2.2 Excitation systems -- 4.2.3 Power system stabilizer (PSS) -- 4.2.4 Network model -- 4.3 Pseudoinputs and decentralization of DAEs -- 4.4 Unscented Kalman lter (UKF) -- 4.4.1 Generation of sigma points -- 4.4.2 State prediction -- 4.4.3 Measurement prediction -- 4.4.4 Kalman update -- 4.5 Case study: 68-bus test system -- 4.5.1 Noise variances -- 4.5.1.1 Measurement noise -- 4.5.1.2 Process noise -- 4.5.2 Simulation results and discussion -- 4.5.2.1 Estimation accuracy -- 4.5.2.2 Computational feasibility -- 4.5.2.3 Sensitivity to noise -- 4.6 Bad-data detection -- 4.7 Other PMU-based methods of DSE -- 4.8 Summary -- 5 Dynamic Parameter Estimation of Analogue Voltage and Current Signals -- 5.1 Interpolated DFT-based estimation -- 5.1.1 Expressions for mean values of the parameter estimates -- 5.2 Variance of parameter estimates -- 5.2.1 Cramer-Rao bounds for the parameters -- 5.2.2 Expressions for variance of the parameter estimates -- 5.3 Implementation example -- 5.4 Summary -- 6 Decentralized Dynamic Estimation Using CTs/VTs. , 6.1 Decoupled power system equations after incorporating internal angle -- 6.2 Two-stage estimation based on interpolated DFT and UKF -- 6.3 Case study -- 6.3.1 Simulation parameters -- 6.3.2 Estimation accuracy -- 6.3.3 Estimation in the presence of colored noise -- 6.3.4 Computational feasibility -- 6.4 Extension to an unbalanced system -- 6.5 Summary -- 7 Control Based on Dynamic Estimation: Linear and Nonlinear Theories -- 7.1 Linear optimal control -- 7.1.1 Problem statement -- 7.1.2 Classical LQR control -- 7.1.3 Linear quadratic control for systems with exogenous inputs -- 7.1.4 Implementation example: a third-order LTI system -- 7.1.4.1 Known and deterministic model of the exogenous input -- ELQR policy -- Classical LQR policy -- Disturbance accommodating LQR policy -- Comparison of control performance -- 7.1.4.2 Known and stochastic model of the exogenous input -- 7.1.4.3 Unknown model for the exogenous input -- 7.2 Nonlinear optimal control -- 7.2.1 Basics of control using normal forms -- 7.3 Summary -- 8 Decentralized Linear Control Using DSE and ELQR -- 8.1 Architecture of control -- 8.2 Decentralization of control -- 8.2.1 Details of state matrices used in integrated ELQR -- 8.3 Integrated ELQR control -- 8.3.1 Damping control -- 8.4 Case study -- 8.4.1 System description -- 8.4.2 Control performance -- 8.4.3 Robustness to different operating conditions -- 8.4.4 Control efforts and state costs -- 8.4.5 Comparison with centralized wide area-based control -- 8.4.6 Effect of noise/bad data on control performance -- 8.4.7 Computational feasibility -- 8.5 Summary -- 9 Decentralized Nonlinear Control Using DSE & Normal Forms -- 9.1 Normal form of power system dynamics -- 9.1.1 Relative degree -- 9.1.2 Linearized dynamics -- 9.1.3 Internal dynamics -- 9.2 Asymptotic stability of zero dynamics -- 9.3 Overall stability and control expression. , 9.4 Decentralized dynamic state estimation -- 9.5 Case study -- 9.5.1 Case A: Assessment of small signal stability -- 9.5.1.1 Modal and sensitivity analysis -- 9.5.2 Case B: Assessment of transient stability -- 9.5.3 Discussion on the magnitude of the control input and the control performance -- 9.5.4 Computational feasibility -- 9.6 Summary -- 10 Conclusion -- A Description of the 16-Machine, 68-Bus, 5-Area Test System -- A.1 System data -- A.1.1 Bus data -- A.1.2 Line data -- A.1.3 Machine parameters -- A.1.4 Excitation system parameters -- A.1.5 PSS parameters -- A.1.6 TCSC parameters -- B Dynamic State Estimation Plots for Unit 3 and Unit 9 -- C Level-2 S-Function Used in Integrated ELQR -- Bibliography -- Index -- Back Cover.

Language: English

UID:

Format: 1 online resource (398 pages)

Edition: Third edition.

ISBN: 1-78862-971-X

Content: Over 100 recipes for penetration testing using Metasploit and virtual machinesKey FeaturesSpecial focus on the latest operating systems, exploits, and penetration testing techniquesLearn new anti-virus evasion techniques and use Metasploit to evade countermeasuresAutomate post exploitation with AutoRunScriptExploit Android devices, record audio and video, send and read SMS, read call logs, and much moreBuild and analyze Metasploit modules in RubyIntegrate Metasploit with other penetration testing toolsBook DescriptionMetasploit is the world's leading penetration testing tool and helps security and IT professionals find, exploit, and validate vulnerabilities. Metasploit allows penetration testing automation, password auditing, web application scanning, social engineering, post exploitation, evidence collection, and reporting. Metasploit's integration with InsightVM (or Nexpose), Nessus, OpenVas, and other vulnerability scanners provides a validation solution that simplifies vulnerability prioritization and remediation reporting. Teams can collaborate in Metasploit and present their findings in consolidated reports. In this book, you will go through great recipes that will allow you to start using Metasploit effectively. With an ever increasing level of complexity, and covering everything from the fundamentals to more advanced features in Metasploit, this book is not just for beginners but also for professionals keen to master this awesome tool. You will begin by building your lab environment, setting up Metasploit, and learning how to perform intelligence gathering, threat modeling, vulnerability analysis, exploitation, and post exploitation—all inside Metasploit. You will learn how to create and customize payloads to evade anti-virus software and bypass an organization's defenses, exploit server vulnerabilities, attack client systems, compromise mobile phones, automate post exploitation, install backdoors, run keyloggers, highjack webcams, port public exploits to the framework, create your own modules, and much more. What you will learnSet up a complete penetration testing environment using Metasploit and virtual machinesMaster the world s leading penetration testing tool and use it in professional penetration testingMake the most of Metasploit with PostgreSQL, importing scan results, using workspaces, hosts, loot, notes, services, vulnerabilities, and exploit resultsUse Metasploit with the Penetration Testing Execution Standard methodologyUse MSFvenom efficiently to generate payloads and backdoor files, and create shellcodeLeverage Metasploit s advanced options, upgrade sessions, use proxies, use Meterpreter sleep control, and change timeouts to be stealthyWho this book is forIf you are a Security professional or pentester and want to get into vulnerability exploitation and make the most of the Metasploit framework, then this book is for you. Some prior understanding of penetration testing and Metasploit is required.

Note: Includes index.

Language: English

Keywords: Electronic books.

URL: Click to View

UID:

Format: xxvii, 234 Seiten , Diagramme

ISBN: 9780128140055

Language: English

Subjects: Engineering

Keywords: Elektrizitätsversorgungsnetz ; Regelung

Author information: Pal, Bikash 1968-

UID:

Format: 1 Online-Ressource (xii, 397 Seiten) : , Illustrationen, Diagramme (teilweise farbig).

Edition: Third edition

ISBN: 978-1-78862-971-3 , 1-78862-971-X

Note: Description based on online resource; title from title page (viewed April 2, 2018)

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-1-78862-317-9

Language: English

URL: Volltext  (URL des Erstveröffentlichers)

UID:

Format: iii, 250 p.

Edition: Electronic reproduction. Ann Arbor, MI : ProQuest, 2015. Available via World Wide Web. Access may be limited to ProQuest affiliated libraries.

Note: "Quick answers to common problems." , Includes index.

Language: English

Keywords: Electronic books.

URL: Click to View

UID:

Format: 1 online resource (699 pages)

Edition: 1st edition

ISBN: 1-83864-494-6

Content: Evade antiviruses and bypass firewalls with the most widely used penetration testing frameworks Key Features Gain insights into the latest antivirus evasion techniques Set up a complete pentesting environment using Metasploit and virtual machines Discover a variety of tools and techniques that can be used with Kali Linux Book Description Penetration testing or ethical hacking is a legal and foolproof way to identify vulnerabilities in your system. With thorough penetration testing, you can secure your system against the majority of threats. This Learning Path starts with an in-depth explanation of what hacking and penetration testing is. You’ll gain a deep understanding of classical SQL and command injection flaws, and discover ways to exploit these flaws to secure your system. You'll also learn how to create and customize payloads to evade antivirus software and bypass an organization's defenses. Whether it's exploiting server vulnerabilities and attacking client systems, or compromising mobile phones and installing backdoors, this Learning Path will guide you through all this and more to improve your defense against online attacks. By the end of this Learning Path, you'll have the knowledge and skills you need to invade a system and identify all its vulnerabilities. This Learning Path includes content from the following Packt products: Web Penetration Testing with Kali Linux - Third Edition by Juned Ahmed Ansari and Gilberto Najera-Gutierrez Metasploit Penetration Testing Cookbook - Third Edition by Abhinav Singh , Monika Agarwal, et al What you will learn Build and analyze Metasploit modules in Ruby Integrate Metasploit with other penetration testing tools Use server-side attacks to detect vulnerabilities in web servers and their applications Explore automated attacks such as fuzzing web applications Identify the difference between hacking a web application and network hacking Deploy Metasploit with the Penetration Testing Execution Standard (PTES) Use MSFvenom to generate payloads and backdoor files, and create shellcode Who this book is for This Learning Path is designed for security professionals, web programmers, and pentesters who want to learn vulnerability exploitation and make the most of the Metasploit framework. Some understanding of penetration testing and Metasploit is required, but basic system administration skills and the ability to read code are a must. Downloading the example code for this ebook: You can download the exampl...

Additional Edition: ISBN 1-83864-607-8

Language: English

UID:

Format: 1 online resource (264 pages)

ISBN: 0-12-814006-2 , 0-12-814005-4

Note: Front Cover -- Dynamic Estimation and Control of Power Systems -- Copyright -- Contents -- About the Authors -- Preface -- List of Figures -- List of Tables -- List of Abbreviations -- List of Symbols -- 1 Introduction -- 1.1 State of the art -- 1.1.1 Energy management system -- 1.1.2 Phasor measurement units (PMUs) -- 1.1.3 Flexible AC transmission system (FACTS) -- 1.1.4 Wide-area measurements and wide-area control -- 1.1.5 Dynamic state estimation (DSE) and dynamic control -- 1.2 Static state estimation (SSE) versus dynamic state estimation (DSE) -- 1.3 Challenges to power system dynamic estimation and control -- 1.4 Book organization -- 2 Power System Modeling, Simulation, and Control Design -- 2.1 Power system model -- 2.1.1 Generating unit: a generator and its excitation system -- 2.1.2 Power system stabilizers (PSSs) -- 2.1.3 FACTS control devices -- 2.1.3.1 Thyristor-controlled series capacitor (TCSC) -- 2.1.3.2 Static VAR compensator (SVC) -- 2.1.3.3 Thyristor-controlled phase angle regulator (TCPAR) -- 2.1.4 Loads, network interface, and network equations -- 2.2 Power system simulation and analysis -- 2.2.1 Load ow analysis -- 2.2.2 Initialization and time-domain simulation -- 2.2.3 Linear analysis and basics of control design -- 2.2.3.1 System linearization -- 2.2.3.2 Eigenvalues -- 2.2.3.3 Participation factor and residue -- 2.2.3.4 Controllable devices, controllers, inputs, and outputs: examples -- 2.2.3.5 Electromechanical modes -- 2.2.3.6 Interarea modes and mode shapes -- 2.2.3.7 Residue-based linear control design -- 3 Centralized Dynamic Estimation and Control -- 3.1 NCPS modeling with output feedback -- 3.1.1 State space representation of power system -- 3.1.2 Sensors and actuators -- 3.1.3 Communication protocol, packet delay, and packet dropout -- 3.1.4 Controller -- 3.1.5 Estimator -- 3.1.5.1 State prediction step. , 3.1.5.2 Measurement prediction and Kalman update step -- 3.2 Closed-loop stability and damping response -- 3.2.1 Stability analysis framework of a jump linear system -- 3.2.1.1 LMIs for mean-square stability -- 3.2.1.2 LMIs for adequate damping response -- 3.2.2 Physical signi cance of the developed LMIs -- 3.3 Case study: 68-bus 16-machine 5-area NCPS -- 3.3.1 System description -- 3.3.2 Simulation results and discussion -- 3.3.2.1 Operating condition 1 (base case) -- 3.3.2.2 Operating condition 2 -- 3.3.2.3 Effect of sampling period -- 3.3.2.4 Robustness -- 3.4 Limitations -- 3.5 Summary -- 4 Decentralized Dynamic Estimation Using PMUs -- 4.1 Problem statement and methodology in brief -- 4.1.1 Problem statement -- 4.1.2 Methodology -- 4.2 Power system modeling and discrete DAEs -- 4.2.1 Generators -- 4.2.2 Excitation systems -- 4.2.3 Power system stabilizer (PSS) -- 4.2.4 Network model -- 4.3 Pseudoinputs and decentralization of DAEs -- 4.4 Unscented Kalman lter (UKF) -- 4.4.1 Generation of sigma points -- 4.4.2 State prediction -- 4.4.3 Measurement prediction -- 4.4.4 Kalman update -- 4.5 Case study: 68-bus test system -- 4.5.1 Noise variances -- 4.5.1.1 Measurement noise -- 4.5.1.2 Process noise -- 4.5.2 Simulation results and discussion -- 4.5.2.1 Estimation accuracy -- 4.5.2.2 Computational feasibility -- 4.5.2.3 Sensitivity to noise -- 4.6 Bad-data detection -- 4.7 Other PMU-based methods of DSE -- 4.8 Summary -- 5 Dynamic Parameter Estimation of Analogue Voltage and Current Signals -- 5.1 Interpolated DFT-based estimation -- 5.1.1 Expressions for mean values of the parameter estimates -- 5.2 Variance of parameter estimates -- 5.2.1 Cramer-Rao bounds for the parameters -- 5.2.2 Expressions for variance of the parameter estimates -- 5.3 Implementation example -- 5.4 Summary -- 6 Decentralized Dynamic Estimation Using CTs/VTs. , 6.1 Decoupled power system equations after incorporating internal angle -- 6.2 Two-stage estimation based on interpolated DFT and UKF -- 6.3 Case study -- 6.3.1 Simulation parameters -- 6.3.2 Estimation accuracy -- 6.3.3 Estimation in the presence of colored noise -- 6.3.4 Computational feasibility -- 6.4 Extension to an unbalanced system -- 6.5 Summary -- 7 Control Based on Dynamic Estimation: Linear and Nonlinear Theories -- 7.1 Linear optimal control -- 7.1.1 Problem statement -- 7.1.2 Classical LQR control -- 7.1.3 Linear quadratic control for systems with exogenous inputs -- 7.1.4 Implementation example: a third-order LTI system -- 7.1.4.1 Known and deterministic model of the exogenous input -- ELQR policy -- Classical LQR policy -- Disturbance accommodating LQR policy -- Comparison of control performance -- 7.1.4.2 Known and stochastic model of the exogenous input -- 7.1.4.3 Unknown model for the exogenous input -- 7.2 Nonlinear optimal control -- 7.2.1 Basics of control using normal forms -- 7.3 Summary -- 8 Decentralized Linear Control Using DSE and ELQR -- 8.1 Architecture of control -- 8.2 Decentralization of control -- 8.2.1 Details of state matrices used in integrated ELQR -- 8.3 Integrated ELQR control -- 8.3.1 Damping control -- 8.4 Case study -- 8.4.1 System description -- 8.4.2 Control performance -- 8.4.3 Robustness to different operating conditions -- 8.4.4 Control efforts and state costs -- 8.4.5 Comparison with centralized wide area-based control -- 8.4.6 Effect of noise/bad data on control performance -- 8.4.7 Computational feasibility -- 8.5 Summary -- 9 Decentralized Nonlinear Control Using DSE & Normal Forms -- 9.1 Normal form of power system dynamics -- 9.1.1 Relative degree -- 9.1.2 Linearized dynamics -- 9.1.3 Internal dynamics -- 9.2 Asymptotic stability of zero dynamics -- 9.3 Overall stability and control expression. , 9.4 Decentralized dynamic state estimation -- 9.5 Case study -- 9.5.1 Case A: Assessment of small signal stability -- 9.5.1.1 Modal and sensitivity analysis -- 9.5.2 Case B: Assessment of transient stability -- 9.5.3 Discussion on the magnitude of the control input and the control performance -- 9.5.4 Computational feasibility -- 9.6 Summary -- 10 Conclusion -- A Description of the 16-Machine, 68-Bus, 5-Area Test System -- A.1 System data -- A.1.1 Bus data -- A.1.2 Line data -- A.1.3 Machine parameters -- A.1.4 Excitation system parameters -- A.1.5 PSS parameters -- A.1.6 TCSC parameters -- B Dynamic State Estimation Plots for Unit 3 and Unit 9 -- C Level-2 S-Function Used in Integrated ELQR -- Bibliography -- Index -- Back Cover.

Language: English

UID:

Format: 1 online resource (264 pages)

ISBN: 0-12-814006-2 , 0-12-814005-4

Note: Front Cover -- Dynamic Estimation and Control of Power Systems -- Copyright -- Contents -- About the Authors -- Preface -- List of Figures -- List of Tables -- List of Abbreviations -- List of Symbols -- 1 Introduction -- 1.1 State of the art -- 1.1.1 Energy management system -- 1.1.2 Phasor measurement units (PMUs) -- 1.1.3 Flexible AC transmission system (FACTS) -- 1.1.4 Wide-area measurements and wide-area control -- 1.1.5 Dynamic state estimation (DSE) and dynamic control -- 1.2 Static state estimation (SSE) versus dynamic state estimation (DSE) -- 1.3 Challenges to power system dynamic estimation and control -- 1.4 Book organization -- 2 Power System Modeling, Simulation, and Control Design -- 2.1 Power system model -- 2.1.1 Generating unit: a generator and its excitation system -- 2.1.2 Power system stabilizers (PSSs) -- 2.1.3 FACTS control devices -- 2.1.3.1 Thyristor-controlled series capacitor (TCSC) -- 2.1.3.2 Static VAR compensator (SVC) -- 2.1.3.3 Thyristor-controlled phase angle regulator (TCPAR) -- 2.1.4 Loads, network interface, and network equations -- 2.2 Power system simulation and analysis -- 2.2.1 Load ow analysis -- 2.2.2 Initialization and time-domain simulation -- 2.2.3 Linear analysis and basics of control design -- 2.2.3.1 System linearization -- 2.2.3.2 Eigenvalues -- 2.2.3.3 Participation factor and residue -- 2.2.3.4 Controllable devices, controllers, inputs, and outputs: examples -- 2.2.3.5 Electromechanical modes -- 2.2.3.6 Interarea modes and mode shapes -- 2.2.3.7 Residue-based linear control design -- 3 Centralized Dynamic Estimation and Control -- 3.1 NCPS modeling with output feedback -- 3.1.1 State space representation of power system -- 3.1.2 Sensors and actuators -- 3.1.3 Communication protocol, packet delay, and packet dropout -- 3.1.4 Controller -- 3.1.5 Estimator -- 3.1.5.1 State prediction step. , 3.1.5.2 Measurement prediction and Kalman update step -- 3.2 Closed-loop stability and damping response -- 3.2.1 Stability analysis framework of a jump linear system -- 3.2.1.1 LMIs for mean-square stability -- 3.2.1.2 LMIs for adequate damping response -- 3.2.2 Physical signi cance of the developed LMIs -- 3.3 Case study: 68-bus 16-machine 5-area NCPS -- 3.3.1 System description -- 3.3.2 Simulation results and discussion -- 3.3.2.1 Operating condition 1 (base case) -- 3.3.2.2 Operating condition 2 -- 3.3.2.3 Effect of sampling period -- 3.3.2.4 Robustness -- 3.4 Limitations -- 3.5 Summary -- 4 Decentralized Dynamic Estimation Using PMUs -- 4.1 Problem statement and methodology in brief -- 4.1.1 Problem statement -- 4.1.2 Methodology -- 4.2 Power system modeling and discrete DAEs -- 4.2.1 Generators -- 4.2.2 Excitation systems -- 4.2.3 Power system stabilizer (PSS) -- 4.2.4 Network model -- 4.3 Pseudoinputs and decentralization of DAEs -- 4.4 Unscented Kalman lter (UKF) -- 4.4.1 Generation of sigma points -- 4.4.2 State prediction -- 4.4.3 Measurement prediction -- 4.4.4 Kalman update -- 4.5 Case study: 68-bus test system -- 4.5.1 Noise variances -- 4.5.1.1 Measurement noise -- 4.5.1.2 Process noise -- 4.5.2 Simulation results and discussion -- 4.5.2.1 Estimation accuracy -- 4.5.2.2 Computational feasibility -- 4.5.2.3 Sensitivity to noise -- 4.6 Bad-data detection -- 4.7 Other PMU-based methods of DSE -- 4.8 Summary -- 5 Dynamic Parameter Estimation of Analogue Voltage and Current Signals -- 5.1 Interpolated DFT-based estimation -- 5.1.1 Expressions for mean values of the parameter estimates -- 5.2 Variance of parameter estimates -- 5.2.1 Cramer-Rao bounds for the parameters -- 5.2.2 Expressions for variance of the parameter estimates -- 5.3 Implementation example -- 5.4 Summary -- 6 Decentralized Dynamic Estimation Using CTs/VTs. , 6.1 Decoupled power system equations after incorporating internal angle -- 6.2 Two-stage estimation based on interpolated DFT and UKF -- 6.3 Case study -- 6.3.1 Simulation parameters -- 6.3.2 Estimation accuracy -- 6.3.3 Estimation in the presence of colored noise -- 6.3.4 Computational feasibility -- 6.4 Extension to an unbalanced system -- 6.5 Summary -- 7 Control Based on Dynamic Estimation: Linear and Nonlinear Theories -- 7.1 Linear optimal control -- 7.1.1 Problem statement -- 7.1.2 Classical LQR control -- 7.1.3 Linear quadratic control for systems with exogenous inputs -- 7.1.4 Implementation example: a third-order LTI system -- 7.1.4.1 Known and deterministic model of the exogenous input -- ELQR policy -- Classical LQR policy -- Disturbance accommodating LQR policy -- Comparison of control performance -- 7.1.4.2 Known and stochastic model of the exogenous input -- 7.1.4.3 Unknown model for the exogenous input -- 7.2 Nonlinear optimal control -- 7.2.1 Basics of control using normal forms -- 7.3 Summary -- 8 Decentralized Linear Control Using DSE and ELQR -- 8.1 Architecture of control -- 8.2 Decentralization of control -- 8.2.1 Details of state matrices used in integrated ELQR -- 8.3 Integrated ELQR control -- 8.3.1 Damping control -- 8.4 Case study -- 8.4.1 System description -- 8.4.2 Control performance -- 8.4.3 Robustness to different operating conditions -- 8.4.4 Control efforts and state costs -- 8.4.5 Comparison with centralized wide area-based control -- 8.4.6 Effect of noise/bad data on control performance -- 8.4.7 Computational feasibility -- 8.5 Summary -- 9 Decentralized Nonlinear Control Using DSE & Normal Forms -- 9.1 Normal form of power system dynamics -- 9.1.1 Relative degree -- 9.1.2 Linearized dynamics -- 9.1.3 Internal dynamics -- 9.2 Asymptotic stability of zero dynamics -- 9.3 Overall stability and control expression. , 9.4 Decentralized dynamic state estimation -- 9.5 Case study -- 9.5.1 Case A: Assessment of small signal stability -- 9.5.1.1 Modal and sensitivity analysis -- 9.5.2 Case B: Assessment of transient stability -- 9.5.3 Discussion on the magnitude of the control input and the control performance -- 9.5.4 Computational feasibility -- 9.6 Summary -- 10 Conclusion -- A Description of the 16-Machine, 68-Bus, 5-Area Test System -- A.1 System data -- A.1.1 Bus data -- A.1.2 Line data -- A.1.3 Machine parameters -- A.1.4 Excitation system parameters -- A.1.5 PSS parameters -- A.1.6 TCSC parameters -- B Dynamic State Estimation Plots for Unit 3 and Unit 9 -- C Level-2 S-Function Used in Integrated ELQR -- Bibliography -- Index -- Back Cover.

Language: English

UID:

Format: 1 online resource (269 p.)

Edition: 1st edition

ISBN: 1-62198-904-6 , 1-281-09013-1 , 9786613775498 , 1-84951-743-6

Content: Over 80 recipes to master the most widely used penetration testing framework

Note: "Quick answers to common problems." , Includes index. , Cover; Copyright; Credits; About the Author; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Metasploit Quick Tips for Security Professionals; Introduction; Configuring Metasploit on Windows; Configuring Metasploit on Ubuntu; Metasploit with BackTrack 5 - the ultimate combination; Setting up the penetration testing lab on a single machine; Setting up Metasploit on a virtual machine with SSH connectivity; Beginning with the interfaces - the ""Hello World"" of Metasploit; Setting up the database in Metasploit; Using the database to store penetration testing results , Analyzing the stored results of the databaseChapter 2: Information Gathering and Scanning; Introduction; Passive information gathering 1.0 - the traditional way; Passive information gathering 2.0 - the next level; Port scanning - the Nmap way; Exploring auxiliary modules for scanning; Target service scanning with auxiliary modules; Vulnerability scanning with Nessus; Scanning with NeXpose; Sharing information with the Dradis framework; Chapter 3: Operating System-based Vulnerability Assessment and Exploitation; Introduction; Exploit usage quick tips , Penetration testing on a Windows XP SP2 machineBinding a shell to the target for remote access; Penetration testing on the Windows 2003 Server; Windows 7/Server 2008 R2 SMB client infinite loop; Exploiting a Linux (Ubuntu) machine; Understanding the Windows DLL injection flaws; Chapter 4: Client-side Exploitation and Antivirus Bypass; Introduction; Internet Explorer unsafe scripting misconfiguration vulnerability; Internet Explorer CSS recursive call memory corruption; Microsoft Word RTF stack buffer overflow; Adobe Reader util.printf() buffer overflow , Generating binary and a shellcode from msfpayloadBypassing client-side antivirus protection using msfencode; Using the killav.rb script to disable antivirus programs; A Deeper look into the killav.rb script; Killing antivirus services from the command line; Chapter 5: Using Meterpreter to Explore the Compromised Target; Introduction; Analyzing meterpreter system commands; Privilege escalation and process migration; Setting multiple communication channels with the target; Meterpreter filesystem commands; Changing file attributes using timestomp; Using meterpreter networking commands , The getdesktop and keystroke sniffingUsing a scraper meterpreter script; Chapter 6: Advanced Meterpreter Scripting; Introduction; Passing the hash; Setting up a persistent connection with backdoors; Pivoting with meterpreter; Port forwarding with meterpreter; Meterpreter API and mixins; Railgun -- converting Ruby into a weapon; Adding a DLL and function definition to Railgun; Building a ""Windows Firewall De-activator"" meterpreter script; Analyzing an existing meterpreter script; Chapter 7: Working with Modules for Penetration Testing; Introduction; Working with scanner auxiliary modules , Working with auxiliary admin modules , English

Additional Edition: ISBN 1-84951-742-8

Language: English