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    Control Engineering

    A tantárgy neve magyarul / Name of the subject in Hungarian: Szabályozástechnika

    Last updated: 2013. szeptember 7.

    Budapest University of Technology and Economics
    Faculty of Electrical Engineering and Informatics

    Electrical Engineering BSc program

    BSc degree program

    Mandatory subject
    Course ID Semester Assessment Credit Tantárgyfélév
    VIIIA303 5 3/2/0/v 5  
    3. Course coordinator and department Dr. Kiss Bálint,
    4. Instructors

    Name Position Department 
    Dr. István Harmati (lectures)associate professor Control Engineering and Information Technology 
    Dr. Bálint Kiss (practices)associate professorControl Engineering and Information Technology 

    5. Required knowledge

    Mathematics: linear algebra, matrix calculus, complex numbers and complex calculus, linear differential equations

    Signals and systems: Furrier, Laplace and Z transforms and their properties, impulse and step responses, convolution integrals

    6. Pre-requisites
    Kötelező:
    (TárgyEredmény( "BMEVIHVA200" , "aláírás" , _ ) = -1
    VAGY
    TárgyEredmény( "BMEVIEV2021" , "aláírás" , _ ) = -1
    VAGY
    TárgyEredmény( "BMEVIEV2015" , "aláírás" , _ ) = -1
    VAGY
    TárgyEredmény( ahol a TárgyKód = "BMEVIEV2501", ahol a Típus = "JEGY", ahol a Ciklus = tetszőleges, ahol a KépzésKód = tetszőleges) >=2
    VAGY
    TárgyEredmény( ahol a TárgyKód = "BMEVIEVF005", ahol a Típus = "JEGY", ahol a Ciklus = tetszőleges, ahol a KépzésKód = tetszőleges) >=2
    VAGY
    TárgyEredmény( "BMEVIEV3058" , "aláírás" , _ ) = -1

    VAGY Training.Code=("5NAA78RESZ")

    VAGY
    EgyenCsoportTagja("Brazil 2015-16-1_erk") )

    ÉS NEM ( TárgyEredmény( "BMEVIIIAB05" , "jegy" , _ ) >= 2
    VAGY
    TárgyEredmény("BMEVIIIAB05", "FELVETEL", AktualisFelev()) > 0)

    ÉS Training.Code=("5N-A7")

    A fenti forma a Neptun sajátja, ezen technikai okokból nem változtattunk.

    A kötelező előtanulmányi rend az adott szak honlapján és képzési programjában található.

    Ajánlott:
    Mandatory: Signals and systems 2 (VIHVA200)
    7. Objectives, learning outcomes and obtained knowledge
    The control of technological, economical, and environmental processes belongs to the electrical engineers’ most important professional activities that require both abstract and applied knowledge and competences. Besides its contribution to form an engineering approach of problem solving, the course teaches the fundamentals of control engineering, the main principles of analysis and synthesis of control loops, and the use of the related computational tools.
    Obtained skills and expertise:
    Students successfully satisfying the course requirements are prepared to analyze discrete and continuous time control loops, to design different types of compensators and to later engage courses in more advanced fields in control theory such as optimal control and identification of dynamical systems.
    8. Synopsis
    1. Basic notions of control theory (3 hours of lectures): The principle of control. Presentation of control structures. Principles and differences of open and closed loop control. Functional diagrams, dataflow diagrams, conventions and standard signals and their nomenclature in a control loop. Static and dynamic characteristics of control loops, integrals of the error function. Classification of control systems. The steps of control system synthesis. Main trends in control theory including a historical review. Some important services of Matlab, Simulink, and the Control System toolbox. 

    2. Modeling of dynamical systems (3 hours of lectures): Dynamical systems. State, and state space. Solution of the state equation of a continuous time, linear, time varying (LTV) system, the properties of the fundamental matrix. Solution of the state equation of a continuous time, linear, time invariant (LTI) system, the exponential matrix, the transfer function, poles, and zeros. The consequences of a (invertible linear) coordinate transformation in the state space, LTV system invariants. Possibilities to solve the state 
    equations of a continuous time nonlinear system using numerical methods, linearization around a setpoint. Models of some classes of physical systems including mechanical and thermal processes using energy preservation laws of physics. Model establishment based on measures available on the real process. 

    3. Analysis of continuous time linear control systems (6 hours of lectures): Descriptions of single variable (SISO) linear transfers: ordinary differential equation, transfer function, Bode-plot, impulse response, step response, state equation. Transformations between descriptions. Fundamental interconnections of elements, open and closed loops. Elementary transfers. First and second order systems: characteristics in time and 
    frequency domains. Relation between the dominant pole(s) and the dynamical characteristics of a transfer. Properties of the amplitude and phase plots of a general open loop transfer function, the calculation of the crossover frequency. Steady state responses in linear control loops and consequences on reference tracking and disturbance rejection. Stability criteria: Hurwitz criterion, Nyquist criterion, Bode criterion, phase margin and crossover frequency. The description of the stability margin by the phase margin. 

    4. Synthesis of continuous time linear control systems (9 hours of lectures): The class of PID compensators, the PID compensator with filtered D term, Bode plots and pole zero distribution of the compensators. Properties of the compensators to be used. Setting the compensator parameters for a desired phase margin and steady state behavior. Examples for compensation with P, PD, PI, and PID controllers. Feedback compensation. Controller design for minimal error square integral. Root locus methods. Compensation of systems with time lag: compensation of an ideal time lag with an integrator, compensation of time lags using Smith predictor. Setting the controller parameters for bounded controller signals. Experimental setting of controller parameters using the Ziegler-Nichols method. 

    5. Analysis of discrete time linear control systems (3 hours of lectures): The Shannon law. Properties of hold elements. Signal propagation in a discrete time system in frequency domain and using state space description. Discrete time equivalent of a continuous time plant using a zero order hold element. Discrete time implementation of continuous time compensators: discrete time realization of integral and derivative operators (approximations), step response equivalence. Hardware and software realization of a PID controller using integrator anti-windup techniques. Nyquist and Bode stability criteria for discrete time control systems.

    6. Synthesis of discrete time linear control systems (3 hours of lectures): Realization of a simple direct digital control scheme. Design of a discrete time controller using the bilinear (Tustin) transform: the effect of the transformation to transmission poles and zeros, the main steps of the compensator design, setting the parameters for a given phase margin and crossover frequency using the technique already presented for the continuous time case. Design of two-degree-of-freedom controllers: the choice of the observer polynomial and the transfer function of the reference model, the steps of the design procedure to arrive to a Diophantine equation. Illustration with an example. Robustness of the two-degree-of-freedom controller scheme against parameter uncertainties. Compensation of a plant with time lag, the realization of the Smith predictor. 

    7. Control loop synthesis in state space (6 hours of lectures): Controllability and observability in continuous time linear systems. Conditions of full state controllability and observability. Staircase forms, stabilizability and detectability. Kalman decomposition of LTV systems. Pole placement using state feedback, the Ackermann formula. Design of full state observers, algebraic equivalence to the pole placement problem. Controllability 
    and observability of discrete time systems. Pole placement and actual observer design for discrete time systems. Integral control and load estimator design. 

    8. Discrete time system models and parameter identification methods (3 hours of lectures): Autoregressive (AR) and moving average (MA) processes, ARX and ARMAX models. Parameter identification of ARX models using LS methods. Parameter identification of the ARMAX model using numerical optimization and the quasi-Newton method. The services of the Identification toolbox of Matlab. The recursive LS problem and its solution with application possibilities in control engineering and signal processing. 

    9. Elementary stability theory of nonlinear systems, further topics (3 hours of lectures): Equilibria and limit cycles of nonlinear systems, their stability in Lyapunov’s sense. Uniform and asymptotic stability. Positive and negative definite functions. Lyapunov’s direct and indirect methods. Relation between the classical and Lyapunov stability for LTV systems. Invariant set, LaSalle’s invariance theorem. Examples for stability analysis of nonlinear control systems. Short introduction into further topics: new trends in contemporary control theory, new tools, rapid control prototyping, case studies to present up-to-date development tools.
    9. Method of instruction
    14 weeks of classes: 42 hours of lectures, 14 hours of classroom practices and 14 hours of computer room practices
    10. Assessment
    a. During the teaching period: mandatory presence at classroom and computer room practices (14 occasions, 2+2 absences are tolerated). Five tests are written during the semester at the beginning of the five computer laboratory practices (starting with the second occasion). The grade of at least three tests must be at least 2.00 (on the scale of 1 to 5). One midterm is written during the semester, its result must be at least 2.00 (on the scale of 1 to 5).
    b. During the exam period: no students can take exam (and hence receive credits) without satisfying the requirements during the teaching period (see point a). Exams are organized in computer rooms. The exam has two parts (90 minutes each). The first part is a closed-book test such that the students must earn at least 20 points out of 40 in order to pass. The second part consists of open-book controller synthesis problems such that the students must earn at least 20 points out of 50 in order to pass. The average of all small tests (see point a) contributes to the exam result with at most 10 points. The grade of the midterm (see point a) contributes to the exam result with at most 10 points. The final grade of the exam is given based on the points on a 100 points scale.
    c. Pre-exam: not available for this course
    11. Recaps
    The mid-term can be repeated once if the mandatory presence requirement during classroom and computer room practices was satisfied and the student also completed the requirements for the small tests.
    13. References, textbooks and resources

     

    A. D. Lewis, A Mathematical Introduction to Feedback Control, 2002

    Karl Johan Aström, Richard M. Murray. Feedback systems: an introduction for scientists and engineers. Princeton University Press, 2008

    B. C. Kuo, Farid Golnaraghi. Automatic Control Systems, 8th edition. Wiley, 2001

    Classroom and computer room practices (downloadable from Educational Portal – http://edu.iit.bme.hu)

     

    14. Required learning hours and assignment
    Contact hours70
    Preparation for contact hours36
    Preparation for the midterm14
    Homework assignmentsnone
    Home readingsnone
    Preparation for the exam30
    Total workload150
    15. Syllabus prepared by
    NamePosition Department 
    Dr. Béla Lantosprofessor emeritus Control Engineering and Information Technology 
    Dr. István Harmatiassociate professor Control Engineering and Information Technology 
    Dr. Tibor Csubák associate professorControl Engineering and Information Technology
    Dr. Zoltán Helybéliassistant professorControl Engineering and Information Technology
    Dr. Bálint Kissassociate professorControl Engineering and Information Technology