Engineering Applications of MATLAB® 5.3 and SIMULINK® 3
Translated from the French by Mohand Mokhtari, Michel Marie, Cécile Davy and Martine Neveu
Published on 6. December 2012
XIV, 538 pages
978-1-4471-0741-5 (ISBN)
Description
In recent years MATLAB®, together with SIMULINK® and the many associated toolboxes, has became a standard in the fields of engineering, simulation and numerical calculation. A veritable programming environment in themselves, MATLAB® and SIMULINK® bring unequalled possibilities of resolution and simulation in the fields of numerical calculation and the study of dynamic systems to students and professionals alike. These features are enhanced by excellent graphic visualisation in 2D and 3D. The originality of this book is to intelligently marry theory and practice. The theory is exposed in the first half of the work, the second part of the work being devoted to the study of real applications of control process and signal processing. This approach allows the reader, at any stage, to see the importance of the theory worked out in practical examples and follow the examples with their theoretical structure presented in a clear and concise way. The presentation of these applications begins with an initial mathematical study of the physical processes leading to the discrete modelling stage. In each of these case studies, the authors demonstrate the power of MA TLAB® and SIMULINK® tools as well as the power of the toolboxes dedicated to the control of processes, fuzzy logic, neuronal networks and signal processing. This enlightening approach gives the reader (novice or specialist) a clear and thorough understanding of these tools.
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Mohand Mokhtari | Michel Marie
Engineering Applications of MATLAB® 5.3 and SIMULINK® 3
Translated from the French by Mohand Mokhtari, Michel Marie, Cécile Davy and Martine Neveu
Book
04/2000
Springer
€85.55
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Content
1 : Analog and digital control.- 1. The principle.- 2. Presentation of main types of corrector.- 3. Analog correctors discretisation.- 4. Corrected systems stability.- 5. Examples.- 6. LQ, LQI, quadratic linear control.- 7. RST control.- 2: State representation of continuous and discrete systems.- 1. State representation of continuous systems.- 2. State representation of discrete systems.- 3. Controllability and observability.- 4. State reconstruction of a discrete dynamic system.- 5. State return control.- 6. Examples.- 7. Kalman filter.- 8. Discrete stochastic Kalman predictor.- 3: Fuzzy logic control.- 1. The fundamental principle.- 2. Stages of implementation of a fuzzy regulator.- 3. Graphical interface of the "Fuzzy Logic TOOLBOX".- 4. Creation of a fuzzy system using the toolbox commands.- 5. Fuzzy regulator use in SIMULINK®.- 6. Sugeno's method.- 4: Neural networks.- 1. Introduction.- 2. Linear adaptive neural networks.- 3. Neural networks with hidden layers, back-propagation error.- 4. Inverse neural model control.- 5. Signal prediction.- 5: Adaptive filtering.- 1. The adaptive filtering principle.- 2. Gradient algorithm, LMS criterion.- 3. The recursive least squares algorithm, exact least squares criterion.- 4. Examples of LMS adaptive filters.- 5. RLS adaptive filter example.- Application 1: Power amplifier.- 1. Description of amplifier.- 2. Characterization of amplifier.- 3. Amplifier with transistors stage feedback.- 4. Amplifier with phase lag corrector.- 5. Amplifier with feedback of phase lead type corrector.- Application 2: Electromagnetic levitation.- 1. Process modelling.- 2. Electric current amplifier control system.- 3. Analogical and discrete models of the x(t) position control system.- 4. x(t) digital follower control.- 5. Using a fuzzy corrector.- Application 3: Cart with inverted pendulum.- 1. System modelling with 2 degrees of freedom.- 2. Linear process state modelling.- 3. Edition and test of the discrete model.- 4. Fuzzy regulation of the ?(t) angular position.- 5. Fuzzy control of the x(t) position and the ?(t) angle.- 6. Graphical animation of the system.- Application 4: Oven control.- 1. Oven modelling.- 2. Integral control with compensation of poles and zeros.- 3. Discrete state representation of the oven.- 4. Control by state return with integration.- 5. Using a Kaiman reconstructor.- 6. LQ quadratic linear control.- 7. Control by neuronal inverse model.- Application 5: Travelling gantry crane with suspended mass.- 1. Modelling the travelling gantry crane with 2 degrees of freedom.- 2. Transfer functions of the system.- 3. Regulation of the ?(t) angular position.- 4. Regulation of the x(t) position truck and the ?(t) angle.- 5. State space modelling.- 6. Graphical animation of the travelling gantry crane.- 7. Fuzzy control of the gantry.- 8. RST and LQI controllers.- Application 6: Hands-free telephone.- 1. Programming Adaline using MATLAB® commands.- 2. Using S-function in a SIMULINK® model.- Application 7: Echo cancellation on a transmission line.- 1. Transmission line modelling.- 2. LMS filtering, lms1 S-function.- 3. RLS filtering, rlsl S-function.- Application 8 : Noise elimination in a conduit.- 1. Conduit modelling.- 2. LMS filtering, lms2 S-function.- 3. RLS filtering, rls2 S-function.- 4. Composite noise filtering.- Application 9 : Equalisation of a symmetrical binary channel.- 1. Generation of a random binary sequence.- 2. The dispersion Channel.- 3. Symmetrical channel equaliser.- 4. Use with SIMULINK®.- Appendix 1 : S-functions under SIMULINK® 3.- 1. S-functions functioning principle under SIMULINK® 3.- 2. Various stages of the simulation.- 3. S-function creation through a M-file call.- 3. S-function creation through a C MEX file call.- Appendix 2 : Masking a set of blocks in SIMULINK® 3.- 1. Damped sinusoidal generator.- 2. Pseudo-random binary sequence generator (PRBS).
