Systems Modeling and Control (ENS 206)

2019 Spring
Faculty of Engineering and Natural Sciences
Engineering Sciences(ENS)
3
6.00 / 6.00 ECTS (for students admitted in the 2013-14 Academic Year or following years)
İbrahim Kürşat Şendur sendur@sabanciuniv.edu,
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English
Undergraduate
MATH102 MATH201
Formal lecture,Recitation
Discussion based learning,Project based learning,Simulation
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CONTENT

Examples of physical and abstract systems and their mathematical models. Classification of dynamic system models linearity and time invariance ; finite state discrete event systems. Tools of analysis for linear systems : transform techniques, input-output analysis, block diagrams, frequency response representation. Introduction to stability and closed loop system design. Introduction to supervisory control for discrete event systems.

OBJECTIVE

Develop mathematical models of dynamical systems and control them through various controllers to obtain desired performance.

LEARNING OUTCOME

After taking this course, students should be able to:

- Develop mathematical models of simple dynamical systems such as mechanical, electrical and electromechanical systems using differential equations based on first principles.
- Obtain and manipulate transfer functions of linear time invariant (LTI) systems using Laplace transform. Identify poles and zeros of a transfer function. Construct and manipulate block diagrams of LTI systems.
- Determine and characterize the time response of 1st and 2nd order systems using various inputs such as step, ramp and sinusoids.
- Construct Matlab/Simulink models of dynamical systems and simulate them with different inputs and initial conditions.
- Develop state space representations for linear and nonlinear dynamical systems. Linearize nonlinear systems around an operating point.
- Define stability and determine stability of LTI systems.
- Sketch the root locus of LTI systems and determine conditions for critical stability from such plots. Investigate the effects of adding zeros and poles to the system.
- Determine the frequency response of LTI systems through Bode and polar plots.
- Analyze basic control systems. Distinguish open loop from closed loop (feedback) control systems.
- Design simple PID controllers and evaluate them on the transient and steady state performance of dynamical systems.

PROGRAMME OUTCOMES


1. Understand the world, their country, their society, as well as themselves and have awareness of ethical problems, social rights, values and responsibility to the self and to others. 2

2. Understand different disciplines from natural and social sciences to mathematics and art, and develop interdisciplinary approaches in thinking and practice. 5

3. Think critically, follow innovations and developments in science and technology, demonstrate personal and organizational entrepreneurship and engage in life-long learning in various subjects. 4

4. Communicate effectively in Turkish and English by oral, written, graphical and technological means. 2

5. Take individual and team responsibility, function effectively and respectively as an individual and a member or a leader of a team; and have the skills to work effectively in multi-disciplinary teams. 3


1. Possess sufficient knowledge of mathematics, science and program-specific engineering topics; use theoretical and applied knowledge of these areas in complex engineering problems. 5

2. Identify, define, formulate and solve complex engineering problems; choose and apply suitable analysis and modeling methods for this purpose. 5

3. Develop, choose and use modern techniques and tools that are needed for analysis and solution of complex problems faced in engineering applications; possess knowledge of standards used in engineering applications; use information technologies effectively. 5

4. Ability to design a complex system, process, instrument or a product under realistic constraints and conditions, with the goal of fulfilling specified needs; apply modern design techniques for this purpose. 4

5. Design and conduct experiments, collect data, analyze and interpret the results to investigate complex engineering problems or program-specific research areas. 3

6. Knowledge of business practices such as project management, risk management and change management; awareness on innovation; knowledge of sustainable development. 2

7. Knowledge of impact of engineering solutions in a global, economic, environmental, health and societal context; knowledge of contemporary issues; awareness on legal outcomes of engineering solutions; understanding of professional and ethical responsibility. 2


1. Familiarity with concepts in statistics and optimization, knowledge in basic differential and integral calculus, linear algebra, differential equations, complex variables, multi-variable calculus, as well as physics and computer science, and ability to use this knowledge in modeling, design and analysis of complex dynamical systems containing hardware and software components. 5

2. Ability to work in design, implementation and integration of engineering applications, such as electronic, mechanical, electromechanical, control and computer systems that contain software and hardware components, including sensors, actuators and controllers. 5


1. Use mathematics (including derivative and integral calculations, probability and statistics), basic sciences, computer and programming, and electronics engineering knowledge to design and analyze complex electronic circuits, instruments, software and electronics systems with hardware/software. 4

2. Analyze and design communication networks and systems, signal processing algorithms or software using advanced knowledge on differential equations, linear algebra, complex variables and discrete mathematics. 4


1. Applying fundamental and advanced knowledge of natural sciences as well as engineering principles to develop and design new materials and establish the relation between internal structure and physical properties using experimental, computational and theoretical tools. 2

2. Merging the existing knowledge on physical properties, design limits and fabrication methods in materials selection for a particular application or to resolve material performance related problems. 2

3. Predicting and understanding the behavior of a material under use in a specific environment knowing the internal structure or vice versa. 2


1. Formulate and analyze problems in complex manufacturing and service systems by comprehending and applying the basic tools of industrial engineering such as modeling and optimization, stochastics, statistics. 3

2. Design and develop appropriate analytical solution strategies for problems in integrated production and service systems involving human capital, materials, information, equipment, and energy. 3

3. Implement solution strategies on a computer platform for decision-support purposes by employing effective computational and experimental tools. 3


1. Design, implement, test, and evaluate a computer system, component, or algorithm to meet desired needs and to solve a computational problem. 3

2. Demonstrate knowledge of discrete mathematics and data structures. 3

3. Demonstrate knowledge of probability and statistics, including applications appropriate to computer science and engineering. 2


1. Comprehend key concepts in biology and physiology, with emphasis on molecular genetics, biochemistry and molecular and cell biology as well as advanced mathematics and statistics. 2

2. Develop conceptual background for interfacing of biology with engineering for a professional awareness of contemporary biological research questions and the experimental and theoretical methods used to address them. 2

ASSESSMENT METHODS and CRITERIA

  Percentage (%)
Final 40
Midterm 35
Exam 2
Assignment 18
Individual Project 5

RECOMENDED or REQUIRED READINGS

Textbook

K. Ogata, System Dynamics, 4th Edition, Prentice-Hall

Readings

W. J. Palm III, System Dynamics, 3rd Edition, McGraw-Hill Education