MATLAB is a powerful, versatile, and interactive software for scientific and technical computations, including simulations. Specialized toolboxes provided with built-in functions are a special feature of MATLAB. This book aims at getting the reader started with computations and simulations in system engineering quickly and easily and then proceeds to build concepts for advanced computations and simulations that include the control and compensation of systems. Simulation through SIMULINK has also been described to allow the reader to get the feel of the real world situation.

Inhalt

1. System Representation and Modeling.- 1.1 Properties of the Models.- 1.1.1 Generic Properties.- 1.1.2 Model-specific Properties.- 1.2 Creating a Model.- 1.2.1 Zero/Pole/Gain (zpk) Model.- 1.2.2 Transfer Function (tf) Model.- 1.2.3 State Space (ss) Model.- 1.2.3.1 Standard State Space Model.- 1.2.3.2 Descriptor State Space Model.- 1.2.4 Frequency Response Data (frd) Model.- 1.2.5 Generation of Random Stahle Models.- Exercise for Chapter 1.- 2. Model Manipulation.- 2.1 The Precedence Rule and the Law of Property Inheritance.- 2.1.1 The Precedence Rule.- 2.1.2 The Law of Property Inheritance.- 2.2 Arithmetic Operations on Models.- 2.2.1 Addition and Subtraction.- 2.2.2 Multiplication.- 2.2.3 Inversion.- 2.2.4 Right Divide.- 2.2.5 Left Divide.- 2.2.6 Transposition.- 2.2.7 Pertransposition.- 2.2.8 Power of Model.- 2.2.9 Stacking.- 2.3 Interconnection of Models.- 2.3.1 Concatenation.- 2.3.2 Append.- 2.3.3 Augstate.- 2.3.4 Connect.- 2.3.5 Feedback.- 2.3.6 Linear Fractional Transformation (lft) Connection.- 2.3.7 Parallel and Series Connection.- 2.4 The Linear Time Invariant (LTI) Subsystem.- 2.4.1 Obtaining a Subsystem.- 2.4.2 Modifying a System/Subsystem.- 2.4.3 Subsystem Manipulations.- Exercise for Chapter 2.- 3. Getting Information from the Models.- 3.1 Model-specific Information.- 3.1.1 Zero/Pole/Gain Model.- 3.1.2 Transfer Function Model.- 3.1.3 State Space Model.- 3.1.4 Frequency Response Data Model.- 3.2 Direct Property Referencing Method of Getting Information.- 3.3 The 'get' Function.- 3.4 Information about Model Dimensions and Characteristics.- 3.5 Conversion of Models.- 3.5.1 Automatic Conversion.- 3.5.2 Conversion by Specifying.- 3.5.3 Continuous/Discrete Conversions.- 3.6 A Few Words on Model Properties Again.- 3.6.1 Overruling the Precedence Rule and the Law of Property Inheritance.- 3.6.2 Setting/Modifying the LTI Properties.- 3.6.3 More on Time Delays.- 3.6.3.1 Mapping Discrete-time Delays to Poles at the Origin.- 3.6.3.2 Pade Approximation of Time Delays.- 3.6.3.3 Computing Time Delays of LTI Models.- Exercise for Chapter 3.- 4. Model Analysis.- 4.1 Model Dynamics of Control System.- 4.1.1 System Poles.- 4.1.2 System Zeros.- 4.1.3 Low-frequency or DC Gain.- 4.1.4 Pole-zero Map.- 4.1.5 H2 and L? Norms.- 4.1.6 Covariance of Response to White Noise.- 4.1.7 Natural Frequency and Damping of LTI Model Poles.- 4.1.8 Sorting Eigenvalues.- 4.2 Time Response Analysis of Control Systems.- 4.2.1 Response of a Model to Standard Signals.- 4.2.2 Response of a Model to Arbitrary Periodic Signals.- 4.2.3 The Unit Step Function.- 4.3 Frequency Response Analysis of Control Systems.- 4.3.1 Obtaining Frequency Response Plots.- 4.3.2 Getting Information from the Plots.- 4.3.2.1 Evaluating Frequency Response over a Frequency Range.- 4.3.2.2 Evaluating Frequency Response at a Particular Frequency.- 4.3.2.3 Evaluating Gain Margin, Phase Margin, Crossover Frequencies and Judging Stability.- 4.4 State Space Analysis of Control Systems.- 4.4.1 Eigenvalues and Eigenvectors.- 4.4.2 Initial Condition Response of ss Model.- 4.4.3 Canonical State Space Realization.- 4.4.4 Controlability and Observability.- 4.4.5 Controlability and Observability Gramians.- 4.4.6 Balancing of ss Model.- 4.4.6.1 Using Diagonal Similarity.- 4.4.6.2 Using Gramian-based Balancing of State Space Realizations.- 4.4.7 State Reduction of ss Model.- 4.4.7.1 The modred Function.- 4.4.7.2 The minreal Function.- 4.4.7.3 The sminreal Function.- Exercise for Chapter 4.- 5. The Control System Toolbox's GUIs.- 5.1 The LTI Viewer.- 5.1.1 Initializing the LTI Viewer.- 5.1.2 More about the ltiview Function.- 5.1.3 The LTI Viewer Environment.- 5.1.4 The Bottom Command Bar.- 5.1.5 The Right Click Menus.- 5.1.6 More about Clicking on the Plots.- 5.1.7 A Few Words on the LTI Arrays Response Plots.- 5.1.7.1 The Model Selector for LTI Arrays Window.- 5.2 The Root Locus Design GUI.- 5.2.1 Initializing the Root Locus Design GUI.- 5.2.2 The Root Locus Design GUI Environment.- 5.2.3 Using Root Locus Design GUI.- Exercise for Chapter 5.- 6. Control System Design through Simulink®.- 6.1 System Representation/Modeling.- 6.1.1 Modeling Using Simulink® Library.- 6.1.2 Modeling Using Control System Toolbox Library.- 6.2 Model Manipulation.- 6.2.1 Arithmetic Operations on Models.- 6.2.2 Interconnection of Models.- 6.3 Model Analysis.- 6.4 The Simulink® LTI Viewer.- 6.4.1 Invoking and Using the Simulink® LTI Viewer.- 6.5 A Few Words of Caution.- Exercise for Chapter 6.- 7. Design of Compensators for Systems.- 7.1 Classical Methods for Design.- 7.1.1 Obtaining Root Locus Plot for a Model.- 7.1.2 Selecting Feedback Gain from Root Locus Plot.- 7.1.3 Designing Compensator Using Root Locus Technique.- 7.2 Solution of Lyapunov's Equation and Stability.- 7.3 Modern Methods for Design.- 7.3.1 Design of State Feedback Controller.- 7.3.1.1 For SISO Models.- 7.3.1.2 For MIMO Models.- 7.3.2 Design of State Estimator/Observer.- 7.3.3 Design of State Regulator.- 7.4 Design of Optimal Compensators.- 7.4.1 Riccati Equations.- 7.4.1.1 Solution of Continuous-time Algebraic Riccati Equations.- 7.4.1.2 Solution of Discrete-time Algebraic Riccati Equations.- 7.4.2 Design of Kalman State Estimator.- 7.4.2.1 Kalman Estimator for Continuous-/Discrete-time Models.- 7.4.2.2 Discrete Kalman State Estimator for Continuous-time Models.- 7.4.3 Design of Linear Quadratic State Feedback Regulator.- 7.4.3.1 Linear Quadratic State Feedback Regulator for Continuous Models.- 7.4.3.2 Linear Quadratic State Feedback Regulator for Discrete Models.- 7.4.3.3 Linear Quadratic State Feedback Regulator with Output Weighting.- 7.4.3.4 Discrete Linear Quadratic State Feedback Regulator for Continuous Model.- 7.4.4 Design of Linear Quadratic Gaussian Regulator.- Exercise for Chapter 7.- 8. Some Simple Applications.- 8.1 Which Method to Choose.- 8.2 Electrical Systems.- 8.2.1 Purely Resistive Circuit.- 8.2.2 Purely Inductive Circuit.- 8.2.3 Purely Capacitive Circuit.- 8.2.4 Series RL Circuit.- 8.2.4.1 Simulation from the Matlab® Window.- 8.2.4.1 Simulation from the Simulink® Window.- 8.2.5 Output Characteristics of a PNP Transistor (Linear Portion in Common Emitter Configuration).- 8.2.6 Series RLC Circuit.- 8.2.7 Bandpass Filter.- 8.3 Mechanical System.- 8.3.1 Translational Mechanical Systems.- 8.3.1.1 Force-displacement System.- 8.3.1.2 Spring-mass-damper-lever System.- 8.3.1.3 Double Spring-mass-damper System.- 8.3.2 Rotational Mechanical Systems.- 8.3.2.1 Spring-inertia-damper System.- 8.3.2.2 Inertia-spring-inertia-damper System.- 8.4 Fluid Systems.- 8.4.1 Hydraulic Systems.- 8.4.1.1 Isolated-tank System.- 8.4.1.2 Interacting-fluid System.- 8.4.2 Pneumatic Systems.- 8.4.1.1 Pneumatic-valve System.- 8.5 Thermal Systems.- 8.5.1 A Mercury-thermometer System.- 8.5.2 Oil-heating System.- Exercise for Chapter 8.- 9. Some Complex Applications.- 9.1 DC Motors.- 9.1.1 Separately-excited DC Motor.- 9.1.2 DC Series Motor.- 9.2 Plunger System.- 9.3 Power-generating Systems.- 9.4 Power-plant System.- 9.5 Pacemaker System.- 9.6 Inverted-pendulum-on-cart System.- 9.7 Essential-oil-extraction Plant.- 9.8 Musical-octave System.- Exercise for Chapter 9.- Appendix A.- Appendix B.- Appendix C.- C.l Plotting some Typical Signals.- Appendix D.- D.l Plotting some Typical Signals.- Appendix E.- References.