Final exam: Computer-controlled systems (Datorbaserad styrning, 1RT450, 1TS250)
|
|
- Philip Stanley
- 5 years ago
- Views:
Transcription
1 Uppsala University Department of Information Technology Systems and Control Professor Torsten Söderström Final exam: Computer-controlled systems (Datorbaserad styrning, RT450, TS250) Date: December 9, 2008 Responsible examiner: Torsten Söderström Preliminary grades: p, p, p. Instructions The solutions to the problems can be given in Swedish or in English. Problem 6 is an alternative to the homework assignment. (In case you choose to hand in a solution to Problem 6 you will be accounted for the best performance of the homework assignments and Problem 6.) Solve each problem on a separate page. Write your name on every page. Provide motivations for your solutions. Vague or lacking motivations may lead to a reduced number of points. Aiding material: Textbooks in automatic control (such as Reglerteori flervariabla och olinjära metoder, Reglerteknik Grundläggande teori, and others), mathematical handbooks, collection of formulas (formelsamlingar), textbooks in mathematics, calculators. Note that the following are not allowed: Exempelsamling med lösningar, copies of OH transparencies. Good luck!
2 Problem Consider an oscillative system with transfer function ( ) 2 Ó Ó + 2 Ó Design a feedback regulator using Internal Model Control and tuning. Will the regulator be integrating? 5 points Problem 2 Consider a two-input, two-output system with the transfer function ¼ ½ ( ) (a) Determine RGA((0)). (b) Which input-output pairing should be preferred? 4 points Problem 3 Civ intends to use Kalman filter theory as a methodology to filter a noisy measurement signal. Consider the setup displayed in the figure below. Here Þ(Ø) is the useful signal, Ò(Ø) the measurement noise and Ý(Ø) the noisy measurements. The filter to be designed is denoted Ä, which output ˆÞ(Ø) should be a good estimate of the useful signal Þ(Ø). It is desired that Ä( ) should be a low-pass filter with the characteristics Ä(0) Ä( ) decreasing at least as for large Ú ¹ Þ ¹ Ý ¹ ( ) Ò + Ä( ) ˆÞ (a) Civ first tried to model the signal Þ(Ø) as a first order filtered signal with the transfer function ( ) + and with a white input signal Ú(Ø) having intensity Ö Ú. The measurement noise is also assumed to be white noise, and to have intensity Ö. 2
3 Show that the setup can in state space form be written as Ü Ü + Ú Ý ( )Ü + Ò What values can the parameter take? Writing the general observer in the form ˆÜ ˆÜ + [Ý ( )ˆÜ] derive the corresponding filter transfer function Ä( ). (b) What constraints on the model ( ) are needed to meet the specified properties of the filter Ä( )? (c) Using the constraints on ( ) derived in part (b), derive the Kalman filter. How is it influenced by the choice of the parameter? 3 points (d) Show that the way the noise intensities Ö Ú and Ö influence in the Kalman filter is only through the ratio Ö Ú Ö, and write out this dependence explicitly. (e) Assume instead that the signal model is taken as the second order system ( ) ( 0 0) ( + ) Will the constraint Ä(0) be satisfied? 3 points Problem 4 Consider À 2 control of the system with the weightings ( ) + Ï Ë ( ) «(«0) Ï Ì ( ) Ï Ù ( ) (a) Write the extended model in state-space form. (b) Find the solution of the associated Riccati equation. (c) Determine the optimal À 2 regulator. 4 points 5 points 3
4 Problem 5 Consider the feedback system in the figure below. Relä Ö 0 Σ ( ) Σ À( ) where À( ) ( ) ( + )( + 2) Use the circle criterion to design the feedback parameters and such that the closed loop system is guaranteed to be asymptotically stable. 6 points Problem 6 Consider a system with the transfer function ( ) 0 + where is a real-valued number. (a) When designing a controller for the system, Civerth chose not to consider the crosscouplings in the system, that is he used the simplified model 0 ( ) Determine the relative model uncertainty. (b) Civerth made a choice to design two decoupling PI-regulators, which leads to the feedback Ì Ã + Ì Ý ( ) 0 Ì 0 Ã Ì 2 Determine the regulator parameters, based on the simplified open loop model, so that the closed loop system becomes ( ) Á. + (c) Use some suitable robustness criterion to decide for which values of one can guarantee that the closed loop system is stable, when the feedback in (b) is applied. 3 points 4
5 (d) Determine for precisely what values of the closed loop system is indeed stable. 3 points 5
6 Uppsala University Department of Information Technology Systems and Control Prof Torsten Söderström Computer-controlled systems, December 9, 2008 Answers and brief solutions Problem The transfer function É( ) becomes É( ) and the regulator will be ( + ) 2 ( ) ( + ) Ó + 2 Ó 2 Ó Ý ( ) [ É( )( )] É( ) Ó + 2 Ó ( + ) ( +) Ó Ó + 2 Ó Ó As Ý (0) ½, the regulator is integrating. Problem 2 (a) In this case Hence RGA((0)) (0) (b) Avoid pairing leading to negative diagonal elements in RGA. Hence combine Ù with Ý 2, and Ù 2 with Ý. Problem 3 (a) The state-space model means that the transfer function from Ú to Þ is ( Á ) Æ ( ) + ( ) Any non-zero value of can be used. 6
7 The observer leads to so ˆÞ ( )ˆÜ ( ) Ô + + Ý Ä( ) + + (b) The condition Ä(0) leads to that Civ must make the choice (c,d) The Riccati equation becomes in this case simply 0 0 È + È Ì + ÆÊ Ú Æ Ì È Ì Ê È Ö Ú Ô 2 ( ) 2 Ö with the solution Ô 2 Ô ÖÚ Ö The corresponding filter gain is (Ô)( Ö ) Ö ÖÚ Ö In the filter the parameter does not depend at all on. Ö ÖÚ Ö (e) Represent the system as Ü 0 0 Ý 0 Ü + 0 Ü + Ú Then it holds Ä 0 Ô Ô 2 Ô Ô(Ô + + ) Ô + 2 Ô 2 + ( + )Ô + 2 which shows in particular that Ä(0), no matter of the values of and 2. 7
8 Problem 4 (a) Write the system to be controlled as Ü Ü + Ù Ý Ü Set Choose the second state as Þ Ù Þ 2 Ü Þ 3 «Ô (Ü + Û) Ü 2 Þ 3 This gives together the extended model 0 Ü Ü + «0 0 Check the matrix Æ Ý 0 Ü + Û ¼ Þ 0 0 ½ ¼ 0 Ü «0 0 «0 Ù + «½ Ù 0 Û As it does not have any eigenvalue in the right half plane, the model is in innovations form. (b) The Riccati equation 0 Ì Ë + Ë Å Ì Å Ë( Ì ) Ì Ë gives in partitioned form with «0 0 Ë « Evaluating the matrix equation componentwize, « «
9 The second equation gives 22 2 «+ 2 from which we conclude that 2 0. Hence, the third equation gives The first equation implies « « The positive sign must be chosen, as 0 must hold. Hence, ¼ Ë 2 + ( 4 + 2«3 + 2 ) «+ «2 (c) For the optimal regulator it holds and then Problem 5 Ä ( Ì ) Ì Ë Ý ( ) Ä Á + ( Ì ) Ì Ë + Æ Æ «+ ««( + + ) «2( + ) ( + + ) «2 ( + ) 2 ( «2 ) «( + ) Ô 4 + 2«3 + 2 «( + ) + Ô 2 + 2«+ The relay gives the bounds 0 2 ½. The circle in the circle criterion becomes the full left half plan. The linear part must hence lie fully in the right half plan. The linear part has transfer function 0 ( ) ( ) [ + À( )] 9 + ( + )( + 2) ½
10 The requirement Re 0 () 0 is equivalent to Problem 6 Re + ( + )( + 2) 0 µ Re ( + )( + )( + 2) 0 µ Re [ (2 2 ) (2 2 ) 3) ] 0 µ (2 2 ) µ 2 + (3 ) µ (a) Introduce ( ) [Á + ( )] ( ), which gives 0 ( ) ( ) ( ) Á 0 (b) The closed loop system will be ( ) Ã( + Ì ) Ì (0 + ) + Ã( + Ì ) Á + Á precisely when Ì Ì 2 0 Ã Ã 2 0. (c) The robustness criteria for the uncertainty in part (a) is Ì ½, that is the largest singular value of Ì () () must be less than one for all frequencies. Here Ì ( ) Á. Using + ( ) as in part (b), Ì ( ) ( ) The singular values of this matrix happens to be equal, and () 2 () Hence, robust stability is guaranteed if which finally leads to the condition Ô 2 + Ô 2 + 0
11 (d) The loop gain will be Ä( ) ( ) Ý ( ) The sensitivity function becomes Ë( ) [Á + Ä( )] + ( + ) One can then see that the system is stable precisely when ( + ) 2 2 has all zeros strictly in the left half plane, which is the case when.
Final exam: Automatic Control II (Reglerteknik II, 1TT495)
Uppsala University Department of Information Technology Systems and Control Professor Torsten Söderström Final exam: Automatic Control II (Reglerteknik II, TT495) Date: October 6, Responsible examiner:
More informationFinal exam: Automatic Control II (Reglerteknik II, 1TT495)
Uppsala University Department of Information Technology Systems and Control Professor Torsten Söderström Final exam: Automatic Control II (Reglerteknik II, TT495) Date: October 22, 2 Responsible examiner:
More informationAutomatic Control III (Reglerteknik III) fall Nonlinear systems, Part 3
Automatic Control III (Reglerteknik III) fall 20 4. Nonlinear systems, Part 3 (Chapter 4) Hans Norlander Systems and Control Department of Information Technology Uppsala University OSCILLATIONS AND DESCRIBING
More informationAutomatic Control II: Summary and comments
Automatic Control II: Summary and comments Hints for what is essential to understand the course, and to perform well at the exam. You should be able to distinguish between continuous-time (c-t) and discrete-time
More informationExam in Systems Engineering/Process Control
Department of AUTOMATIC CONTROL Exam in Systems Engineering/Process Control 7-6- Points and grading All answers must include a clear motivation. Answers may be given in English or Swedish. The total number
More informationExam in Automatic Control II Reglerteknik II 5hp (1RT495)
Exam in Automatic Control II Reglerteknik II 5hp (1RT495) Date: August 4, 018 Venue: Bergsbrunnagatan 15 sal Responsible teacher: Hans Rosth. Aiding material: Calculator, mathematical handbooks, textbooks
More informationExam in Systems Engineering/Process Control
Department of AUTOMATIC CONTROL Exam in Systems Engineering/Process Control 27-6-2 Points and grading All answers must include a clear motivation. Answers may be given in English or Swedish. The total
More informationECE 388 Automatic Control
Controllability and State Feedback Control Associate Prof. Dr. of Mechatronics Engineeering Çankaya University Compulsory Course in Electronic and Communication Engineering Credits (2/2/3) Course Webpage:
More informationT i t l e o f t h e w o r k : L a M a r e a Y o k o h a m a. A r t i s t : M a r i a n o P e n s o t t i ( P l a y w r i g h t, D i r e c t o r )
v e r. E N G O u t l i n e T i t l e o f t h e w o r k : L a M a r e a Y o k o h a m a A r t i s t : M a r i a n o P e n s o t t i ( P l a y w r i g h t, D i r e c t o r ) C o n t e n t s : T h i s w o
More informationExercises Automatic Control III 2015
Exercises Automatic Control III 205 Foreword This exercise manual is designed for the course "Automatic Control III", given by the Division of Systems and Control. The numbering of the chapters follows
More information! " # $! % & '! , ) ( + - (. ) ( ) * + / 0 1 2 3 0 / 4 5 / 6 0 ; 8 7 < = 7 > 8 7 8 9 : Œ Š ž P P h ˆ Š ˆ Œ ˆ Š ˆ Ž Ž Ý Ü Ý Ü Ý Ž Ý ê ç è ± ¹ ¼ ¹ ä ± ¹ w ç ¹ è ¼ è Œ ¹ ± ¹ è ¹ è ä ç w ¹ ã ¼ ¹ ä ¹ ¼ ¹ ±
More informationHere represents the impulse (or delta) function. is an diagonal matrix of intensities, and is an diagonal matrix of intensities.
19 KALMAN FILTER 19.1 Introduction In the previous section, we derived the linear quadratic regulator as an optimal solution for the fullstate feedback control problem. The inherent assumption was that
More informationAutomatic Control II Computer exercise 3. LQG Design
Uppsala University Information Technology Systems and Control HN,FS,KN 2000-10 Last revised by HR August 16, 2017 Automatic Control II Computer exercise 3 LQG Design Preparations: Read Chapters 5 and 9
More informationRäkneövningar Empirisk modellering
Räkneövningar Empirisk modellering Bengt Carlsson Systems and Control Dept of Information Technology, Uppsala University 5th February 009 Abstract Räkneuppgifter samt lite kompletterande teori. Contents
More informationCONVEX OPTIMIZATION OVER POSITIVE POLYNOMIALS AND FILTER DESIGN. Y. Genin, Y. Hachez, Yu. Nesterov, P. Van Dooren
CONVEX OPTIMIZATION OVER POSITIVE POLYNOMIALS AND FILTER DESIGN Y. Genin, Y. Hachez, Yu. Nesterov, P. Van Dooren CESAME, Université catholique de Louvain Bâtiment Euler, Avenue G. Lemaître 4-6 B-1348 Louvain-la-Neuve,
More informationF O R SOCI AL WORK RESE ARCH
7 TH EUROPE AN CONFERENCE F O R SOCI AL WORK RESE ARCH C h a l l e n g e s i n s o c i a l w o r k r e s e a r c h c o n f l i c t s, b a r r i e r s a n d p o s s i b i l i t i e s i n r e l a t i o n
More informationLab 2 Iterative methods and eigenvalue problems. Introduction. Iterative solution of the soap film problem. Beräkningsvetenskap II/NV2, HT (6)
Beräkningsvetenskap II/NV2, HT 2008 1 (6) Institutionen för informationsteknologi Teknisk databehandling Besöksadress: MIC hus 2, Polacksbacken Lägerhyddsvägen 2 Postadress: Box 337 751 05 Uppsala Telefon:
More informationI. D. Landau, A. Karimi: A Course on Adaptive Control Adaptive Control. Part 9: Adaptive Control with Multiple Models and Switching
I. D. Landau, A. Karimi: A Course on Adaptive Control - 5 1 Adaptive Control Part 9: Adaptive Control with Multiple Models and Switching I. D. Landau, A. Karimi: A Course on Adaptive Control - 5 2 Outline
More informationPeriodic monopoles and difference modules
Periodic monopoles and difference modules Takuro Mochizuki RIMS, Kyoto University 2018 February Introduction In complex geometry it is interesting to obtain a correspondence between objects in differential
More informationFRTN 15 Predictive Control
Department of AUTOMATIC CONTROL FRTN 5 Predictive Control Final Exam March 4, 27, 8am - 3pm General Instructions This is an open book exam. You may use any book you want, including the slides from the
More informationMultilevel Preconditioning of Graph-Laplacians: Polynomial Approximation of the Pivot Blocks Inverses
Multilevel Preconditioning of Graph-Laplacians: Polynomial Approximation of the Pivot Blocks Inverses P. Boyanova 1, I. Georgiev 34, S. Margenov, L. Zikatanov 5 1 Uppsala University, Box 337, 751 05 Uppsala,
More information: œ Ö: =? À =ß> real numbers. œ the previous plane with each point translated by : Ðfor example,! is translated to :)
â SpanÖ?ß@ œ Ö =? > @ À =ß> real numbers : SpanÖ?ß@ œ Ö: =? > @ À =ß> real numbers œ the previous plane with each point translated by : Ðfor example, is translated to :) á In general: Adding a vector :
More informationCitation Osaka Journal of Mathematics. 43(2)
TitleIrreducible representations of the Author(s) Kosuda, Masashi Citation Osaka Journal of Mathematics. 43(2) Issue 2006-06 Date Text Version publisher URL http://hdl.handle.net/094/0396 DOI Rights Osaka
More informationEL2520 Control Theory and Practice
EL2520 Control Theory and Practice Lecture 8: Linear quadratic control Mikael Johansson School of Electrical Engineering KTH, Stockholm, Sweden Linear quadratic control Allows to compute the controller
More informationBlock-tridiagonal matrices
Block-tridiagonal matrices. p.1/31 Block-tridiagonal matrices - where do these arise? - as a result of a particular mesh-point ordering - as a part of a factorization procedure, for example when we compute
More informationSeparation Principle & Full-Order Observer Design
Separation Principle & Full-Order Observer Design Suppose you want to design a feedback controller. Using full-state feedback you can place the poles of the closed-loop system at will. U Plant Kx If the
More informationLecture 16: Modern Classification (I) - Separating Hyperplanes
Lecture 16: Modern Classification (I) - Separating Hyperplanes Outline 1 2 Separating Hyperplane Binary SVM for Separable Case Bayes Rule for Binary Problems Consider the simplest case: two classes are
More informationCS 323: Numerical Analysis and Computing
CS 323: Numerical Analysis and Computing MIDTERM #2 Instructions: This is an open notes exam, i.e., you are allowed to consult any textbook, your class notes, homeworks, or any of the handouts from us.
More informationOPTIMAL CONTROL AND ESTIMATION
OPTIMAL CONTROL AND ESTIMATION Robert F. Stengel Department of Mechanical and Aerospace Engineering Princeton University, Princeton, New Jersey DOVER PUBLICATIONS, INC. New York CONTENTS 1. INTRODUCTION
More informationContents lecture 5. Automatic Control III. Summary of lecture 4 (II/II) Summary of lecture 4 (I/II) u y F r. Lecture 5 H 2 and H loop shaping
Contents lecture 5 Automatic Control III Lecture 5 H 2 and H loop shaping Thomas Schön Division of Systems and Control Department of Information Technology Uppsala University. Email: thomas.schon@it.uu.se,
More informationprobability of k samples out of J fall in R.
Nonparametric Techniques for Density Estimation (DHS Ch. 4) n Introduction n Estimation Procedure n Parzen Window Estimation n Parzen Window Example n K n -Nearest Neighbor Estimation Introduction Suppose
More informationThis document has been prepared by Sunder Kidambi with the blessings of
Ö À Ö Ñ Ø Ò Ñ ÒØ Ñ Ý Ò Ñ À Ö Ñ Ò Ú º Ò Ì ÝÊ À Å Ú Ø Å Ê ý Ú ÒØ º ÝÊ Ú Ý Ê Ñ º Å º ² ºÅ ý ý ý ý Ö Ð º Ñ ÒÜ Æ Å Ò Ñ Ú «Ä À ý ý This document has been prepared by Sunder Kidambi with the blessings of Ö º
More informationETIKA V PROFESII PSYCHOLÓGA
P r a ž s k á v y s o k á š k o l a p s y c h o s o c i á l n í c h s t u d i í ETIKA V PROFESII PSYCHOLÓGA N a t á l i a S l o b o d n í k o v á v e d ú c i p r á c e : P h D r. M a r t i n S t r o u
More informationExpressions for the covariance matrix of covariance data
Expressions for the covariance matrix of covariance data Torsten Söderström Division of Systems and Control, Department of Information Technology, Uppsala University, P O Box 337, SE-7505 Uppsala, Sweden
More informationSUCCESSIVE POLE SHIFTING USING SAMPLED-DATA LQ REGULATORS. Sigeru Omatu
SUCCESSIVE POLE SHIFING USING SAMPLED-DAA LQ REGULAORS oru Fujinaka Sigeru Omatu Graduate School of Engineering, Osaka Prefecture University, 1-1 Gakuen-cho, Sakai, 599-8531 Japan Abstract: Design of sampled-data
More informationAnalysis of Discrete-Time Systems
TU Berlin Discrete-Time Control Systems 1 Analysis of Discrete-Time Systems Overview Stability Sensitivity and Robustness Controllability, Reachability, Observability, and Detectabiliy TU Berlin Discrete-Time
More informationLecture 9 Nonlinear Control Design
Lecture 9 Nonlinear Control Design Exact-linearization Lyapunov-based design Lab 2 Adaptive control Sliding modes control Literature: [Khalil, ch.s 13, 14.1,14.2] and [Glad-Ljung,ch.17] Course Outline
More informationPole placement control: state space and polynomial approaches Lecture 2
: state space and polynomial approaches Lecture 2 : a state O. Sename 1 1 Gipsa-lab, CNRS-INPG, FRANCE Olivier.Sename@gipsa-lab.fr www.gipsa-lab.fr/ o.sename -based November 21, 2017 Outline : a state
More informationLoop parallelization using compiler analysis
Loop parallelization using compiler analysis Which of these loops is parallel? How can we determine this automatically using compiler analysis? Organization of a Modern Compiler Source Program Front-end
More informationÜbersetzungshilfe / Translation aid (English) To be returned at the end of the exam!
Prüfung Regelungstechnik I (Control Systems I) Prof. Dr. Lino Guzzella 3.. 24 Übersetzungshilfe / Translation aid (English) To be returned at the end of the exam! Do not mark up this translation aid -
More informationEL 625 Lecture 10. Pole Placement and Observer Design. ẋ = Ax (1)
EL 625 Lecture 0 EL 625 Lecture 0 Pole Placement and Observer Design Pole Placement Consider the system ẋ Ax () The solution to this system is x(t) e At x(0) (2) If the eigenvalues of A all lie in the
More informationAn LQ R weight selection approach to the discrete generalized H 2 control problem
INT. J. CONTROL, 1998, VOL. 71, NO. 1, 93± 11 An LQ R weight selection approach to the discrete generalized H 2 control problem D. A. WILSON², M. A. NEKOUI² and G. D. HALIKIAS² It is known that a generalized
More informationNon Standard Neutrino Interactions
Oscillation Phenomenology NSI and Neutrino Oscillations Our recent Work Non Standard Neutrino Interactions from Physics beyond the Standard Model J.Baumann Arnold Sommerfeld Center, Department für Physik
More informationExamination paper for TFY4240 Electromagnetic theory
Department of Physics Examination paper for TFY4240 Electromagnetic theory Academic contact during examination: Associate Professor John Ove Fjærestad Phone: 97 94 00 36 Examination date: 16 December 2015
More informationFinding small factors of integers. Speed of the number-field sieve. D. J. Bernstein University of Illinois at Chicago
The number-field sieve Finding small factors of integers Speed of the number-field sieve D. J. Bernstein University of Illinois at Chicago Prelude: finding denominators 87366 22322444 in R. Easily compute
More informationLecture 9 Nonlinear Control Design. Course Outline. Exact linearization: example [one-link robot] Exact Feedback Linearization
Lecture 9 Nonlinear Control Design Course Outline Eact-linearization Lyapunov-based design Lab Adaptive control Sliding modes control Literature: [Khalil, ch.s 13, 14.1,14.] and [Glad-Ljung,ch.17] Lecture
More informationInternational Journal of PharmTech Research CODEN (USA): IJPRIF, ISSN: Vol.8, No.7, pp , 2015
International Journal of PharmTech Research CODEN (USA): IJPRIF, ISSN: 0974-4304 Vol.8, No.7, pp 99-, 05 Lotka-Volterra Two-Species Mutualistic Biology Models and Their Ecological Monitoring Sundarapandian
More informationAnalysis of Discrete-Time Systems
TU Berlin Discrete-Time Control Systems TU Berlin Discrete-Time Control Systems 2 Stability Definitions We define stability first with respect to changes in the initial conditions Analysis of Discrete-Time
More informationAutomatic Control Systems theory overview (discrete time systems)
Automatic Control Systems theory overview (discrete time systems) Prof. Luca Bascetta (luca.bascetta@polimi.it) Politecnico di Milano Dipartimento di Elettronica, Informazione e Bioingegneria Motivations
More informationAutomatic control III. Homework assignment Deadline (for this assignment): Monday December 9, 24.00
Uppsala University Department of Information Technology Division of Systems and Control November 18, 2013 Automatic control III Homework assignment 2 2013 Deadline (for this assignment): Monday December
More informationONGOING WORK ON FAULT DETECTION AND ISOLATION FOR FLIGHT CONTROL APPLICATIONS
ONGOING WORK ON FAULT DETECTION AND ISOLATION FOR FLIGHT CONTROL APPLICATIONS Jason M. Upchurch Old Dominion University Systems Research Laboratory M.S. Thesis Advisor: Dr. Oscar González Abstract Modern
More informationIntroduction to System Identification and Adaptive Control
Introduction to System Identification and Adaptive Control A. Khaki Sedigh Control Systems Group Faculty of Electrical and Computer Engineering K. N. Toosi University of Technology May 2009 Introduction
More informationState Observers and the Kalman filter
Modelling and Control of Dynamic Systems State Observers and the Kalman filter Prof. Oreste S. Bursi University of Trento Page 1 Feedback System State variable feedback system: Control feedback law:u =
More informationFramework for functional tree simulation applied to 'golden delicious' apple trees
Purdue University Purdue e-pubs Open Access Theses Theses and Dissertations Spring 2015 Framework for functional tree simulation applied to 'golden delicious' apple trees Marek Fiser Purdue University
More informationConnection equations with stream variables are generated in a model when using the # $ % () operator or the & ' %
7 9 9 7 The two basic variable types in a connector potential (or across) variable and flow (or through) variable are not sufficient to describe in a numerically sound way the bi-directional flow of matter
More informationDEPARTMENT OF MANAGEMENT AND ECONOMICS Royal Military College of Canada. ECE Modelling in Economics Instructor: Lenin Arango-Castillo
Page 1 of 5 DEPARTMENT OF MANAGEMENT AND ECONOMICS Royal Military College of Canada ECE 256 - Modelling in Economics Instructor: Lenin Arango-Castillo Final Examination 13:00-16:00, December 11, 2017 INSTRUCTIONS
More informationLinear and Nonlinear Regression with Application to Unbalance Estimation
Linear and Nonlinear Regression with Application to Unbalance Estimation Peter Nauclér Torsten Söderström Abstract This paper considers estimation of parameters that enters nonlinearly in a regression
More informationAUTOMATIC CONTROL. Andrea M. Zanchettin, PhD Spring Semester, Introduction to Automatic Control & Linear systems (time domain)
1 AUTOMATIC CONTROL Andrea M. Zanchettin, PhD Spring Semester, 2018 Introduction to Automatic Control & Linear systems (time domain) 2 What is automatic control? From Wikipedia Control theory is an interdisciplinary
More informationAN IDENTIFICATION ALGORITHM FOR ARMAX SYSTEMS
AN IDENTIFICATION ALGORITHM FOR ARMAX SYSTEMS First the X, then the AR, finally the MA Jan C. Willems, K.U. Leuven Workshop on Observation and Estimation Ben Gurion University, July 3, 2004 p./2 Joint
More informationOptimal control and estimation
Automatic Control 2 Optimal control and estimation Prof. Alberto Bemporad University of Trento Academic year 2010-2011 Prof. Alberto Bemporad (University of Trento) Automatic Control 2 Academic year 2010-2011
More informationMutually orthogonal latin squares (MOLS) and Orthogonal arrays (OA)
and Orthogonal arrays (OA) Bimal Roy Indian Statistical Institute, Kolkata. Bimal Roy, Indian Statistical Institute, Kolkata. and Orthogonal arrays (O Outline of the talk 1 Latin squares 2 3 Bimal Roy,
More informationCDS Final Exam
CDS 22 - Final Exam Instructor: Danielle C. Tarraf December 4, 2007 INSTRUCTIONS : Please read carefully! () Description & duration of the exam: The exam consists of 6 problems. You have a total of 24
More information6545(Print), ISSN (Online) Volume 4, Issue 3, May - June (2013), IAEME & TECHNOLOGY (IJEET)
INTERNATIONAL International Journal of JOURNAL Electrical Engineering OF ELECTRICAL and Technology (IJEET), ENGINEERING ISSN 976 & TECHNOLOGY (IJEET) ISSN 976 6545(Print) ISSN 976 6553(Online) Volume 4,
More informationState Regulator. Advanced Control. design of controllers using pole placement and LQ design rules
Advanced Control State Regulator Scope design of controllers using pole placement and LQ design rules Keywords pole placement, optimal control, LQ regulator, weighting matrixes Prerequisites Contact state
More informationAutomatic Control 2. Loop shaping. Prof. Alberto Bemporad. University of Trento. Academic year
Automatic Control 2 Loop shaping Prof. Alberto Bemporad University of Trento Academic year 21-211 Prof. Alberto Bemporad (University of Trento) Automatic Control 2 Academic year 21-211 1 / 39 Feedback
More information5. Observer-based Controller Design
EE635 - Control System Theory 5. Observer-based Controller Design Jitkomut Songsiri state feedback pole-placement design regulation and tracking state observer feedback observer design LQR and LQG 5-1
More informationDESIGN AND IMPLEMENTATION OF SENSORLESS SPEED CONTROL FOR INDUCTION MOTOR DRIVE USING AN OPTIMIZED EXTENDED KALMAN FILTER
INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATION ENGINEERING & TECHNOLOGY (IJECET) International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN 0976 ISSN 0976 6464(Print)
More informationA brief introduction to robust H control
A brief introduction to robust H control Jean-Marc Biannic System Control and Flight Dynamics Department ONERA, Toulouse. http://www.onera.fr/staff/jean-marc-biannic/ http://jm.biannic.free.fr/ European
More informationu x + u y = x u . u(x, 0) = e x2 The characteristics satisfy dx dt = 1, dy dt = 1
Õ 83-25 Þ ÛÐ Þ Ð ÚÔÜØ Þ ÝÒ Þ Ô ÜÞØ ¹ 3 Ñ Ð ÜÞ u x + u y = x u u(x, 0) = e x2 ÝÒ Þ Ü ÞØ º½ dt =, dt = x = t + c, y = t + c 2 We can choose c to be zero without loss of generality Note that each characteristic
More informationLQR, Kalman Filter, and LQG. Postgraduate Course, M.Sc. Electrical Engineering Department College of Engineering University of Salahaddin
LQR, Kalman Filter, and LQG Postgraduate Course, M.Sc. Electrical Engineering Department College of Engineering University of Salahaddin May 2015 Linear Quadratic Regulator (LQR) Consider a linear system
More informationDr Ian R. Manchester Dr Ian R. Manchester AMME 3500 : Root Locus
Week Content Notes 1 Introduction 2 Frequency Domain Modelling 3 Transient Performance and the s-plane 4 Block Diagrams 5 Feedback System Characteristics Assign 1 Due 6 Root Locus 7 Root Locus 2 Assign
More informationDeformations of calibrated D-branes in flux generalized complex manifolds
Deformations of calibrated D-branes in flux generalized complex manifolds hep-th/0610044 (with Luca Martucci) Paul Koerber koerber@mppmu.mpg.de Max-Planck-Institut für Physik Föhringer Ring 6 D-80805 München
More informationPlanning for Reactive Behaviors in Hide and Seek
University of Pennsylvania ScholarlyCommons Center for Human Modeling and Simulation Department of Computer & Information Science May 1995 Planning for Reactive Behaviors in Hide and Seek Michael B. Moore
More informationCS 323: Numerical Analysis and Computing
CS 323: Numerical Analysis and Computing MIDTERM #2 Instructions: This is an open notes exam, i.e., you are allowed to consult any textbook, your class notes, homeworks, or any of the handouts from us.
More informationEXAM IN MODELING AND SIMULATION (TSRT62)
EXAM IN MODELING AND SIMULATION (TSRT62) SAL: ISY:s datorsalar TID: Wednesday 4th January 2017, kl. 8.00 12.00 KURS: TSRT62 Modeling and Simulation PROVKOD: DAT1 INSTITUTION: ISY ANTAL UPPGIFTER: 5 ANTAL
More informationBlock vs. Stream cipher
Block vs. Stream cipher Idea of a block cipher: partition the text into relatively large (e.g. 128 bits) blocks and encode each block separately. The encoding of each block generally depends on at most
More informationExam in FRT110 Systems Engineering and FRTN25 Process Control
Department of AUTOMATIC CONTROL Exam in FRT Systems Engineering and FRTN5 Process Control June 5, 5, 4: 9: Points and grades All answers must include a clear motivation. Answers may be given in English
More informationA GENERALIZED SECOND ORDER COMPENSATOR DESIGN FOR VIBRATION CONTROL OF FLEXIBLE STRUCTURES
A GENERALIZED SECOND ORDER COMPENSATOR DESIGN FOR VIBRATION CONTROL OF FLEXIBLE STRUCTURES Hyochoong ~ a n and ~ t Brij N. Agrawalt Naval Postgraduate School Monterey, California t Abstract In this paper,
More informationStructured Uncertainty and Robust Performance
Structured Uncertainty and Robust Performance ELEC 571L Robust Multivariable Control prepared by: Greg Stewart Devron Profile Control Solutions Outline Structured uncertainty: motivating example. Structured
More informationHere are proofs for some of the results about diagonalization that were presented without proof in class.
Suppose E is an 8 8 matrix. In what follows, terms like eigenvectors, eigenvalues, and eigenspaces all refer to the matrix E. Here are proofs for some of the results about diagonalization that were presented
More informationExam on Information Field Theory
Exam on Information Field Theory 25.07.2017 Name: Matrikelnummer: The exam consists of four exercises. Please do check if you received all of them. There are more questions than you will be able to solve
More informationDesign of Decentralised PI Controller using Model Reference Adaptive Control for Quadruple Tank Process
Design of Decentralised PI Controller using Model Reference Adaptive Control for Quadruple Tank Process D.Angeline Vijula #, Dr.N.Devarajan * # Electronics and Instrumentation Engineering Sri Ramakrishna
More informationAlexander Scheinker Miroslav Krstić. Model-Free Stabilization by Extremum Seeking
Alexander Scheinker Miroslav Krstić Model-Free Stabilization by Extremum Seeking 123 Preface Originating in 1922, in its 95-year history, extremum seeking has served as a tool for model-free real-time
More informationEECS C128/ ME C134 Final Wed. Dec. 15, am. Closed book. Two pages of formula sheets. No calculators.
Name: SID: EECS C28/ ME C34 Final Wed. Dec. 5, 2 8- am Closed book. Two pages of formula sheets. No calculators. There are 8 problems worth points total. Problem Points Score 2 2 6 3 4 4 5 6 6 7 8 2 Total
More informationFEL3210 Multivariable Feedback Control
FEL3210 Multivariable Feedback Control Lecture 6: Robust stability and performance in MIMO systems [Ch.8] Elling W. Jacobsen, Automatic Control Lab, KTH Lecture 6: Robust Stability and Performance () FEL3210
More informationOptimal Control of PDEs
Optimal Control of PDEs Suzanne Lenhart University of Tennessee, Knoville Department of Mathematics Lecture1 p.1/36 Outline 1. Idea of diffusion PDE 2. Motivating Eample 3. Big picture of optimal control
More informationEvery real system has uncertainties, which include system parametric uncertainties, unmodeled dynamics
Sensitivity Analysis of Disturbance Accommodating Control with Kalman Filter Estimation Jemin George and John L. Crassidis University at Buffalo, State University of New York, Amherst, NY, 14-44 The design
More informationComputer Problem 1: SIE Guidance, Navigation, and Control
Computer Problem 1: SIE 39 - Guidance, Navigation, and Control Roger Skjetne March 12, 23 1 Problem 1 (DSRV) We have the model: m Zẇ Z q ẇ Mẇ I y M q q + ẋ U cos θ + w sin θ ż U sin θ + w cos θ θ q Zw
More information1.1 OBJECTIVE AND CONTENTS OF THE BOOK
1 Introduction 1.1 OBJECTIVE AND CONTENTS OF THE BOOK Hysteresis is a nonlinear phenomenon exhibited by systems stemming from various science and engineering areas: under a low-frequency periodic excitation,
More informationMATH 1553, C. JANKOWSKI MIDTERM 3
MATH 1553, C JANKOWSKI MIDTERM 3 Name GT Email @gatechedu Write your section number (E6-E9) here: Please read all instructions carefully before beginning Please leave your GT ID card on your desk until
More informationAUTOMATIC CONTROL COMMUNICATION SYSTEMS LINKÖPING
"!# $ %'&)(+* &-,.% /03254-687:9@?A?AB54 C DFEHG)IJ237KI#L BM>A>@ION B5P Q ER0EH?@EHBM4.B3PTSU;V68BMWX2368ERY@BMI Q 7K[25>@6AWX7\4)6]B3PT^_IH7\Y\6A>AEHYK25I#^_4`MER47K7\>AER4` a EH4GbN
More informationDerivation of the Kalman Filter
Derivation of the Kalman Filter Kai Borre Danish GPS Center, Denmark Block Matrix Identities The key formulas give the inverse of a 2 by 2 block matrix, assuming T is invertible: T U 1 L M. (1) V W N P
More informationF-TRANSFORM FOR NUMERICAL SOLUTION OF TWO-POINT BOUNDARY VALUE PROBLEM
Iranian Journal of Fuzzy Systems Vol. 14, No. 6, (2017) pp. 1-13 1 F-TRANSFORM FOR NUMERICAL SOLUTION OF TWO-POINT BOUNDARY VALUE PROBLEM I. PERFILIEVA, P. ŠTEVULIÁKOVÁ AND R. VALÁŠEK Abstract. We propose
More informationStochastic Models, Estimation and Control Peter S. Maybeck Volumes 1, 2 & 3 Tables of Contents
Navtech Part #s Volume 1 #1277 Volume 2 #1278 Volume 3 #1279 3 Volume Set #1280 Stochastic Models, Estimation and Control Peter S. Maybeck Volumes 1, 2 & 3 Tables of Contents Volume 1 Preface Contents
More informationCONTROL SYSTEMS, ROBOTICS, AND AUTOMATION - Vol. V - Prediction Error Methods - Torsten Söderström
PREDICTIO ERROR METHODS Torsten Söderström Department of Systems and Control, Information Technology, Uppsala University, Uppsala, Sweden Keywords: prediction error method, optimal prediction, identifiability,
More informationK c < K u K c = K u K c > K u step 4 Calculate and implement PID parameters using the the Ziegler-Nichols tuning tables: 30
1.5 QUANTITIVE PID TUNING METHODS Tuning PID parameters is not a trivial task in general. Various tuning methods have been proposed for dierent model descriptions and performance criteria. 1.5.1 CONTINUOUS
More informationMAE 143B - Homework 9
MAE 43B - Homework 9 7.2 2 2 3.8.6.4.2.2 9 8 2 2 3 a) G(s) = (s+)(s+).4.6.8.2.2.4.6.8. Polar plot; red for negative ; no encirclements of, a.s. under unit feedback... 2 2 3. 4 9 2 2 3 h) G(s) = s+ s(s+)..2.4.6.8.2.4
More informationProblem Weight Score Total 100
EE 350 EXAM IV 15 December 2010 Last Name (Print): First Name (Print): ID number (Last 4 digits): Section: DO NOT TURN THIS PAGE UNTIL YOU ARE TOLD TO DO SO Problem Weight Score 1 25 2 25 3 25 4 25 Total
More informationLA PRISE DE CALAIS. çoys, çoys, har - dis. çoys, dis. tons, mantz, tons, Gas. c est. à ce. C est à ce. coup, c est à ce
> ƒ? @ Z [ \ _ ' µ `. l 1 2 3 z Æ Ñ 6 = Ð l sl (~131 1606) rn % & +, l r s s, r 7 nr ss r r s s s, r s, r! " # $ s s ( ) r * s, / 0 s, r 4 r r 9;: < 10 r mnz, rz, r ns, 1 s ; j;k ns, q r s { } ~ l r mnz,
More informationIdentification and estimation of state variables on reduced model using balanced truncation method
Journal of Physics: Conference Series PAPER OPEN ACCESS Identification and estimation of state variables on reduced model using balanced truncation method To cite this article: Trifena Punana Lesnussa
More information