000 06244nam a22005175i 4500
001 978-3-540-78486-9
003 DE-He213
005 20161121230547.0
007 cr nn 008mamaa
008 100301s2008 gw | s |||| 0|eng d
020 _a9783540784869
_9978-3-540-78486-9
024 7 _a10.1007/978-3-540-78486-9
_2doi
050 4 _aTJ210.2-211.495
050 4 _aTJ163.12
072 7 _aTJFM
_2bicssc
072 7 _aTJFD
_2bicssc
072 7 _aTEC004000
_2bisacsh
072 7 _aTEC037000
_2bisacsh
082 0 4 _a629.8
_223
100 1 _aHendricks, Elbert.
_eauthor.
245 1 0 _aLinear Systems Control
_h[electronic resource] :
_bDeterministic and Stochastic Methods /
_cby Elbert Hendricks, Ole Jannerup, Paul Haase Sørensen.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2008.
300 _aXX, 555 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aState Space Modelling of Physical Systems -- Analysis of State Space Models -- Linear Control System Design -- Optimal Control -- Noise in Dynamic Systems -- Optimal Observers: Kalman Filters.
520 _aModern control theory and in particular state space or state variable methods can be adapted to the description of many different systems because it depends strongly on physical modeling and physical intuition. The laws of physics are in the form of differential equations and for this reason, this book concentrates on system descriptions in this form. This means coupled systems of linear or nonlinear differential equations. The physical approach is emphasized in this book because it is most natural for complex systems. It also makes what would ordinarily be a difficult mathematical subject into one which can straightforwardly be understood intuitively and which deals with concepts which engineering and science students are already familiar. In this way it is easy to immediately apply the theory to the understanding and control of ordinary systems. Application engineers, working in industry, will also find this book interesting and useful for this reason. In line with the approach set forth above, the book first deals with the modeling of systems in state space form. Both transfer function and differential equation modeling methods are treated with many examples. Linearization is treated and explained first for very simple nonlinear systems and then more complex systems. Because computer control is so fundamental to modern applications, discrete time modeling of systems as difference equations is introduced immediately after the more intuitive differential equation models. The conversion of differential equation models to difference equations is also discussed at length, including transfer function formulations. A vital problem in modern control is how to treat noise in control systems. Nevertheless this question is rarely treated in many control system textbooks because it is considered to be too mathematical and too difficult in a second course on controls. In this textbook a simple physical approach is made to the description of noise and stochastic disturbances which is easy to understand and apply to common systems. This requires only a few fundamental statistical concepts which are given in a simple introduction which lead naturally to the fundamental noise propagation equation for dynamic systems, the Lyapunov equation. This equation is given and exemplified both in its continuous and discrete time versions. With the Lyapunov equation available to describe state noise propagation, it is a very small step to add the effect of measurements and measurement noise. This gives immediately the Riccati equation for optimal state estimators or Kalman filters. These important observers are derived and illustrated using simulations in terms which make them easy to understand and easy to apply to real systems. The use of LQR regulators with Kalman filters give LQG (Linear Quadratic Gaussian) regulators which are introduced at the end of the book. Another important subject which is introduced is the use of Kalman filters as parameter estimations for unknown parameters. The textbook is divided into 7 chapters, 5 appendices, a table of contents, a table of examples, extensive index and extensive list of references. Each chapter is provided with a summary of the main points covered and a set of problems relevant to the material in that chapter. Moreover each of the more advanced chapters (3 - 7) are provided with notes describing the history of the mathematical and technical problems which lead to the control theory presented in that chapter. Continuous time methods are the main focus in the book because these provide the most direct connection to physics. This physical foundation allows a logical presentation and gives a good intuitive feel for control system construction. Nevertheless strong attention is also given to discrete time systems. Very few proofs are included in the book but most of the important results are derived. This method of presentation makes the text very readable and gives a good foundation for reading more rigorous texts. A complete set of solutions is available for all of the problems in the text. In addition a set of longer exercises is available for use as Matlab/Simulink ‘laboratory exercises’ in connection with lectures. There is material of this kind for 12 such exercises and each exercise requires about 3 hours for its solution. Full written solutions of all these exercises are available.
650 0 _aEngineering.
650 0 _aSystem theory.
650 0 _aControl engineering.
650 0 _aRobotics.
650 0 _aMechatronics.
650 1 4 _aEngineering.
650 2 4 _aControl, Robotics, Mechatronics.
650 2 4 _aSystems Theory, Control.
700 1 _aJannerup, Ole.
_eauthor.
700 1 _aSørensen, Paul Haase.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783540784852
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-540-78486-9
912 _aZDB-2-ENG
950 _aEngineering (Springer-11647)
999 _c500592
_d500592