Introduction to Control Systems at Al Mustakbal University

. . . : : : : : 2024 - 2025 L0 - Introduction to Control Systems Email: Osama.Ali.Awad@uomus.edu.iq

AL MUSTAKBAL UNIVERSITY College of engineering and technical Engineering Medical Device Technology Engineering Department Control Systems Course/4thClass Associate Prof. Osama A. Awad

Control Engineering 3 credit course 2 hours/week theoretical lectures . 2 hours/week practical lectures . Matlab knowledge is required. Quizes and attendance 10 /50. LAB (Reports and attendance) 20/50. Midterm Exam I & II 20/50. Final Lab Exam 10/50. Final Exam 40/50.

Control Theory Modern Control Engineering Fifth Edition 2010. Katsuhiko Ogata Modern Control Engineering Richard C. Dorf and Robert H. Bishop Addison Wesley 2009.

Week No. 1,2 3,4,5 6 7,8,9 Topics Introduction to control systems Open loop control system Closed loop control system Design of control systems Mathematical Background and Modeling of Dynamic Systems Differential Equation of Physical Systems Linear Approximation of Physical Systems Laplace Transform / Inverse Laplace Transformation The Transfer Function of Linear Systems Electrical System / Mechanical System / Analogous between Electrical and mechanical DC Motor (Derivation of Mathematical model and Transfer Function) Block Diagram Models Block Diagram Reduction Mason's Signal Flow Graph Models Characteristics and Performance of Feedback Control System Test Input Signals Performance of a First-Order System Performance of a Second-Order System The S-plane Root Location and the Transient Response Sensitivity of Control systems to parameter Variations Disturbance Signals in Feedback Control System Steady State Error

10,11 12,13 14,15 The Stability of Linear feedback Systems The concept of Stability The Routh-Hurwitz Stability Criterion The relative Stability of Feedback Control Systems The Root Locus Method The Root locus Concept The Root Locus Procedure (Rules for Constructing Root Loci) Special Cases Root Locus Analysis Of Control Systems Frequency Response Methods Bode Diagrams Polar Plots Nichols chart Nyquist Criterion TEXT BOOK: Katsuhiko Ogata ,Modern Control Engineering, Prentise-Hall International, 5th , 2010

Control Theory is often regarded as the branch of the general. Control theory is concerned with physical applications. In order to put Control Theory into practice, a bridge must be built between the real world and mathematical theory. Transfer Functions and frequency domain techniques are the classical approaches to represent control systems. State Space representation is another type to describe the mathematical models of control systems (MIMO)

In general control theory is concerned with physical applications A control system is considered to be any system which exists for the purpose of: - Regulating (Stabilization Problems). or - Tracking (controlling the output as desired) Hence, Control system is an interconnection of many components or functional units in such away to produce a desired results. Engineers and Scientists are frequently confronted with the following major tasks: 1- Analyzing real world Problems.

2- Synthesizing Solutions to these Problems. 3- or developing theories to explain them. One of the first steps which is being needed in any of the above major tasks is Modeling . It is the process of the development of the mathematical model that describe the problem being studied. This model must not be oversimplified or conclusions drawn form it will not be valid in the real world. And the model should not be so complex as to complicate unnecessarily the analysis (cost , time,.. )

Two distinct approaches are used for modeling: Analytical Modeling using systematic application of basic physical laws to system components and there interconnections. Experimental Modeling Time series models Auto Regressive(AR), Moving Average (MA), and ARMA models . I/O data Identifications

Classification of Systems The types of equations required to describe a system depends on the types of elemental equation and the type of inputs from the environment. System models are classified according to the types of equations used to describe them:

Types of System Models: 1-Distributed vs Lumped 2-Stochastic vs Deterministic 3-Discrete vs continuous 4-Nonlinear vs Linear 5-Time varying vs constant coefficient 6-nonhomogeneous vs homogenous

When you have a long metal cylinder, each little bit of cylinder has some resistance and some capacitance. If you don't need a good model, you can lump all the little bits of resistance into one resistor, and all the little bits of capacitance into one capacitor. That's lumping. If you need a really good model, then you should treat all the little bits of resistance and capacitance as little bits connected to each other. That's distributed.

Introduction: Control Theory: It is that part of science which concern with control problems. Control Problem: If we want something to act or vary according to a certain performance specification, then we say that we have a control problem. Ex. We want to keep the temperature in a room at certain level and as we order, then we say that we have temperature control problem.

Plant: A piece of equipments the purpose of which is to perform a particular operation (we will call any object to be controlled a plant). Ex. Heating furnace, chemical reactor or space craft. Process: A progressively continuing operation (natural or artificial) that consist of a series of actions or changes in a certain way leading towards a particular result or end. We will call any operation to be controlled a process. Processes could be chemical, economic, or biological. System: A combination of components that act together and perform a certain objective (could be physical, biological, or economic).

Design and Implementation of Controllers One of the primary tasks what control engineering involves is designing and implementing controllers to improve system performance while satisfying the design requirements and limitations. Controllers are algorithms or devices that adjust system inputs based on feedback to achieve a desired output. By designing effective controllers, we ensure systems operate efficiently, safely and reliably.