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College of Engineering

Cyber-Physical Systems (CPS) Minor

A graphic with three photos. The first photo shows an autonomous car designed by ISU researchers. The second photo is of a robotic arm. The third photo shows GPU hardware.

With the fourth industrial revolution upon us, physical systems are being designed to have a cyber component, that enables remote access, monitoring and control. In these systems, ubiquitous sensing, and advanced data management capability are taking us from automation to autonomy via a deep interconnection between the cyber and physical entities. Cyber-physical systems (CPS) are becoming abundant in many application sectors including manufacturing, energy, health care, transportation and agriculture. Safety-, time- and life-critical systems are relying on CPS concepts to become more efficient, robust, resilient, flexible and scalable. As CPS applications become more pervasive, students with a background in CPS will be in demand to design, produce and maintain these systems.

With this motivation and encouraged by the demand from the industry stakeholders of ISU College of Engineering, this CPS minor will focus on sensing, advanced information processing (data analytics and machine learning), and controls aspects of Cyber-Physical Systems. Specific CPS application sectors such as energy/power systems, manufacturing, biomedical devices, autonomous systems, transportation, and agriculture will be in focus.

Students with a minor in CPS will complete 15 credits, 9 of which will come from three required 3-credit courses. The remaining 6 electives come from a range of options as indicated below, including courses that count towards majors. A minimum of 6 credits must be from courses 300 level or above.

*Currently this minor is only available to students in the College of Engineering*

Required Courses

CPS/ME 280X: Design and Analysis of Cyber-Physical Systems 

Initially will be offered by ME, cross-listed with ECPE, AeroE and potentially other Engineering departments 

(2-2), Cr. 3.

Prereq: ENGR 160 (or equivalent), PHYS 221 or PHYS 231+L

Course description: This course will introduce the basic concepts of cyber-physical systems (CPS); physical and cyber considerations and constraints for design, analysis, performance monitoring and control of human-engineered physical systems; basic concepts of sensing, information processing and feedback actuation. There will be substantial hands-on computer programming activity relevant to CPS applications.

CPS/CPR E 287X: Cyber-Physical System Fundamentals

Initially will be offered by ECPE, cross-listed with ME, AeroE and potentially other Engineering departments

(3-0), Cr. 3

Prereq: ENGR 160 (or equivalent), PHYS 221 or PHYS 231+L

Course description: Fundamentals of cyber-physical systems, including introduction to digital systems design, embedded platforms and programming, sensing and actuation, and performance analysis; Introduction to data communication concepts, including systems-level view of signal processing and electronic circuits, networking standards and protocols. Laboratory exercises with embedded circuits, signals, and measurement applications.

CPS/AER E 364X: Cyber-Physical Systems Application.

(2-2) Cr. 3. S.

Prereq: ENGR 160 or equivalent course; credit or enrollment in MATH 267; knowledge of Python.

Fundamental principles of cyber-physical systems and their system-level applications at an introductory level; introduction to radio control systems and control of actuators; computer programming of physical systems; data processing and communication; control loops; X-by-wire control systems; simulation; testing of control loops.

Note: Knowledge of Python may be demonstrated by having taken course using Python at ISU or elsewhere, including other CPS courses ME 280X, CPR E 287X, or independent learning.

Spring 2023 Course Plan

Curriculum Coordination Committee

Soumik Sarkar
Mechanical Engineering
soumiks@iastate.edu

Joseph Zambreno
Electrical and Computer Engineering
zambreno@iastate.edu

Matthew Nelson
Aerospace Engineering
mnelson@iastate.edu

How to Apply

To apply for the Undergraduate Minor in Cyber-Physical Systems, follow these steps:

  1. Complete the Request for Minor form available from the Iowa State University Registrar’s office.
  2. Obtain a signature from your academic advisor.
  3. Submit form to Breanna Helfrick at helfrick@iastate.edu.

We encourage you to consult either your undergraduate academic advisor or a member of the advisory committee for assistance during the application process. Email cpsminor@iastate.edu, or visit 2019 Black Engineering if you have any questions.

Elective Courses (Updated April 2021)

M E 370: Engineering Measurements
(2-3) Cr. 3. F.S.SS. Prereq: E E 442; STAT 305
Fundamentals of design, selection, and operation of components of measuring systems. Measurement processes, data acquisition systems, analysis of data, and propagation of measurement uncertainty.

M E 421: System Dynamics and Control
(3-2) Cr. 4. F.S.SS. Prereq: EE442, EE448, ME345, MATH267
Modeling and simulation of mechanical, electrical, fluid, and/or thermal systems. Development of equations of motion and dynamic response characteristics in time and frequency domains. Fundamentals of classical control applications, including mathematical analysis and design for closed loop control systems. Introduction to computer interfacing for simulation, data acquisition, and control. Laboratory exercises for hands-on system investigation and control implementation.

M E 411: Automatic Controls
(2-2) Cr. 3. F. Prereq: M E 421
Methods and principles of automatic control. Pneumatic, hydraulic, and electrical systems. Representative applications of automatic control systems. Mathematical analysis of control systems.

M E 418/M E 518: Mechanical Considerations in Robotics
(3-0) Cr. 3. S. Prereq: Credit or enrollment in M E 421
Three dimensional kinematics, dynamics, and control of robot manipulators, hardware elements and sensors. Laboratory experiments using industrial robots.

M E 456/M E 556: Machine Vision
Cr. 3. Repeatable. Alt. F., offered odd-numbered years. Prereq: MATH 317, M E 421 or permission of instructor
Practical imaging processing techniques, geometric optics, and mathematics behind machine vision, as well as the most advanced 3D vision techniques. Experience with practical vision system development and analysis. Assignments include individual bi-weekly homework; weekly readings and lectures; and a semester-long research project on design and experiment vision systems.

M E 475: Modeling and Simulation
(3-0) Cr. 3. S. Prereq: M E 421, credit or enrollment in M E 436
Introduction to computer solution techniques required to simulate flow, thermal, and mechanical systems. Methods of solving ordinary and partial differential equations and systems of algebraic equations; interpolation, numerical integration; finite difference and finite element methods.

E E 324: Signals and Systems II

(3-3)Cr.4. F. S. Prereq: E E 224
Laplace and z-Transforms, properties and inverses. Applications to LTI systems and analog/digital filters. Feedback systems and stability. State- space representation and analysis.

E E 333: Electronic Systems Design
(3-3) Cr. 4. F. Prereq: E E 230, credit or enrollment in CPR E 288
Further topics in electronic systems design: Use of sensors and actuators. High-power amplifying and switching components. Linear and switched-mode power supplies. Linear and switched-mode amplifiers. Interfacing electronic components with programmable microcontrollers. Printed circuit board technology and design tools. Laboratory exercises and design projects incorporating printed circuit technology.

E E 425: Machine learning: A Signal Processing Perspective
Cr. 3. S. Prereq: E E 322/STAT 322 (preferred) or STAT 330; and MATH 207 or MATH 407/507 (preferred).
Basic machine learning tools and techniques. Predictive modeling, regression (least squares estimation), classification (multiple hypothesis testing), Bayesian supervised learning and time series analysis (MMSE estimation, MAP estimation, Kalman filtering and more), unsupervised learning (clustering, PCA, robust PCA). Introduce neural network and deep learning methods and the publicly available software packages for these.

E E 476: Control System Simulation
(2-3) Cr. 3. S. Prereq: E E 475
Computer aided techniques for feedback control system design, simulation, and implementation.

CPR E 230: Cyber Security Fundamentals
(2-2) Cr. 3. F. Prereq: COM S 227, E E 285, or MIS 207.
Introduction to computer and network infrastructures used to support cyber security. Basic concepts of computer and network configuration used to secure environments. Computer virtualization, network routing and address translation, computer installation and configuration, network monitoring, in a virtual environment. Laboratory experiments and exercises including secure computer and network configuration and management.

CPR E 388: Embedded Systems II: Mobile Platforms
(3-2) Cr. 4. Prereq: CPR E 288
Contemporary programming techniques for event driven systems. Mobile platforms and operating systems. Location and motion sensors based user interfaces. Threading and scheduling. Resource management – measurement and control techniques – for memory and energy. Client- server application design. Distributed applications. Laboratory includes exercises based on a mobile platform.

CPR E 488: Embedded Systems Design
(3-3) Cr. 4. Prereq: CPR E 381 or COM S 321
Embedded microprocessors, embedded memory and I/O devices, component interfaces, embedded software, program development, basic compiler techniques, platform-based FPGA technology, hardware synthesis, design methodology, real-time operating system concepts, performance analysis and optimizations.

CPR E 414: Introduction to Software Systems for Big Data Analytics
Cr. 4. F. Prereq: COMS 363; or CPRE 315 or CPRE 308; or COMS 311 or COMS 352
Introduction to different perspectives of the “data universe” and trade- offs when choosing an appropriate perspective. Impact of the concept(s) of analytics – from raw data, through its storage/representation, to interacting and querying (linguistic/interface issues). Focused studies on 3-4 different domains, followed by generalization of the concepts/ abstractions and preparing the students for the next course in this realm, targeting different domains/problems. Understanding the dependencies between problem-domain needs and the data properties, and their impact on choosing appropriate analytics tools (and how/why those tools
were developed and exist in the manners that they do). In addition, the students will be exposed to (limited selection of) internals of such tools.

CPR E 419: Software Tools for Large Scale Data Analysis
(Cross-listed with S E). (3-3) Cr. 4. Prereq: COM S 228
Software tools for managing and manipulating large volumes of data, external memory processing, large scale parallelism, and stream processing, data interchange formats. Weekly programming labs that involve the use of a parallel computing cluster.

CPR E 421: Software Analysis and Verification for Safety and Security
(Cross-listed with S E). Cr. 3. F.S. Prereq: COM S 309; CPR E 310 or Com S 230 Significance of software safety and security; various facets of security incyber-physical and computer systems; threat modeling for software safety and security; and categorization of software vulnerabilities. Software analysis and verification: mathematical foundations, data structures and algorithms, program comprehension, analysis, and verification tools; automated vs. human-on-the-loop approach to analysis and verification; and practical considerations of efficiency, accuracy, robustness, and scalability of analysis and verification. Cases studies with application and systems software; evolving landscape of software security threats and mitigation techniques. Understanding large software, implementing software analysis and verification algorithms.

CPR E 458: Real Time Systems
(Dual-listed with CPR E 558). (3-0) Cr. 3. Prereq: CPR E 308 or COM S 352
Fundamental concepts in real-time systems. Real time task scheduling paradigms. Resource management in uniprocessor, multiprocessor, and distributed real-time systems. Fault-tolerance, resource reclaiming, and overload handling. Real-time channel, packet scheduling, and real-time LAN protocols. Case study of real-time operating systems. Laboratory experiments.

A B E 403: Modeling, Simulation, and Controls for Agricultural and Biological Systems

(Dual-listed with A B E 503). (2-2) Cr. 3. Alt. S., offered odd-numbered years. Prereq: ABE 316, and ABE 363, and MATH 266 or MATH 267
Modeling dynamic systems with ordinary differential equations. Introduction to state variable methods of system analysis. Analysis of mechanical, electrical, and fluid power systems. Analytical and numerical solutions of differential equations. Introduction to classical control theory. Feedback and stability examined in the s domain. Frequency response as an analytical and experimental tool. MATLAB will be used throughout the course for modeling. Individual and/or group projects required for graduate credit.

A B E 404: Instrumentation for Agricultural and Biosystems Engineering
(Dual-listed with A B E 504). (2-2) Cr. 3. F. Prereq: ABE 316 and ABE 363
Interfacing techniques for computer-based data acquisition and control systems. Basic interfacing components including A/D and D/A conversion, signal filtering, multiplexing, and process control. Sensors and theory of operation applied to practical monitoring and control problems. Individual and group projects required for graduate credit.

A B E 410: Electronic Systems Integration for Agricultural Machinery
(Dual-listed with A B E 510). Cr. 3. S.
System architecture and design of electronics used in agricultural machinery and production systems. Emphasis on information technology and systems integration for automated agriculture processes. Design of Controller Area Network (CAN BUS) communication systems and discussion of relevant standards (ISO 11783 and SAE J1939). Application of technologies for sensing, distribution control, and automation of agricultural machinery will be emphasized.

I E 413: Stochastic Modeling, Analysis and Simulation

(4-0) Cr. 4. F. Prereq: MATH 265, STAT 231
Development of probabilistic and simulation models using a simulation language. Introduction to Markov processes and other queuing models. Application to various areas of manufacturing and service systems such as assembly, material handling, and customer queues. Fitting of statistical distributions to data. Utilization of model output towards improved decision-making.

I E 432: Industrial Automation
(2-3) Cr. 3. S. Prereq: Phys 222
Overview of electrical circuit theory and its relationship to industrial control systems. Theory and application of transducers in the form of sensors and actuators, with applications in manufacturing, distribution and mechanical systems. Programmable Logic Controllers (PLC), their programming and use for automation solutions. Introduction of automated identification systems such as Radio Frequency Identification (RFID) and Bar Coding technologies.

I E 487: Big Data Analytics and Optimization
(Dual-listed with I E 587). Cr. 3. S. Prereq: IE 312, Stat 231
Optimization and statistical learning related to big data problems. Modern modeling for data-driven optimization problems and their applications in big data analytics. Algorithms for optimization and statistical learning and their implementation. Applications in manufacturing sector and service sciences.

AER E 365X: Avionics and Controls Laboratory

(1-2) Cr. 2. F. Pre-reqs: AER E 160, AER E 161, enrollment or credit in MATH 267. Fundamental principles of digital avionics; radio control systems and pulse-width-modulation control of servos and motors; programming embedded systems; data communication; PID control loops; fly-by-wire control systems; simulation; bench/flight testing of control loops.

AER E 407: Formal Methods
(Dual-listed with AER E 507). (Cross-listed with COM S). Cr. 3. S. Prereq: AER E 361 for AER E majors. COM S 311 for COM S majors. AER E 361 or COM S 311, or an equivalent course, plus instructor permission for other majors.
Introduction to the fundamentals of formal methods, a set of mathematically rigorous techniques for the formal specification, validation, and verification of safety- and security-critical systems. Tools, techniques, and applications of formal methods with an emphasis on real-world use-cases such as enabling autonomous operation. Build experience in writing mathematically analyzable specifications from English operational concepts for real cyberphysical systems, such as aircraft and spacecraft. Review capabilities and limitations of formal methods in the design, verification, and system health management of today’s complex systems.

AER E 433: Spacecraft Dynamics and Control
(3-0) Cr. 3. F. Prereq: EM 345
Three-dimensional rotational kinematics and attitude dynamics of a rigid body in space. Stability analysis of a spinning spacecraft with or without energy dissipation. Attitude dynamics and stability of a satellite in circular orbit. Introduction to spacecraft attitude determination and control systems (ADCS). Simulation of spacecraft attitude-dynamics and control problems of practical interest using MATLAB.

AER E 463: Introduction to Multidisciplinary Design Optimization
(Dual-listed with AER E 563). (3-0) Cr. 3. F. Prereq: senior standing in College of Engineering or permission of instructor
Introduction to the theory and methods of Multidisciplinary Design Optimization (MDO), including system coupling, system sensitivity methods, decomposition methods, MDO formulations (such as multi- discipline feasible (MDF), individual discipline feasible (IDF) and all-at- once (AAO) approaches, and MDO search methods.

AER E 464: Spacecraft Systems
(3-0) Cr. 3. S. Prereq: AER E 351
An examination of spacecraft systems including attitude determination and control, power, thermal control, communications, propulsion, guidance, navigation, command and data handling, and mechanisms. Explanation of space and operational environments as they impact spacecraft design. Includes discussion of safety, reliability, quality, maintainability, testing, cost, legal, and logistics issues.

C E 449: Structural Health Monitoring

(Dual-listed with C E 549). (3-0) Cr. 3. Prereq: Senior classification in Engineering or permission of instructor
Introductory and advanced topics in structural health monitoring (SHM) of aeronautical, civil, and mechanical systems. Topics include sensors, signal processing in time and frequency domains, data acquisition
and transmission systems, design of integrated SHM solutions, nondestructive evaluation techniques, feature extraction methods, and cutting-edge research in the field of SHM. Graduate students will have a supervisory role to assist students in 449 and an additional design project or more in-depth analysis and design.

C E 453: Highway Design
(2-2) Cr. 3. F. Prereq: C E 306, C E 355
Introduction to highway planning and design. Design, construction, and maintenance of highway facilities. Level-of-service, stopping sight distance, highway alignment, earthwork and pavement design. Design project, oral reports and written reports. Computer applications.

C E 556: Transportation Data Analysis
(3-0) Cr. 3. Prereq: C E 355, a Statistics course at the 300 level or higher
Analysis of transportation data, identification of data sources and limitations. Static and dynamic data elements such as infrastructure characteristics, flow and operations-related data elements. Spatial and temporal extents data for planning, design, operations, and management of transportation systems. Summarizing, analyzing, modeling, and interpreting data. Use of information technologies for highways, transit, and aviation systems.

All of the courses listed here are either currently offered or under modification/development in the College of Engineering. In order to be included in the approved course list, course content must be at least 50% CPS related. CPS related means content significantly covers any of the following in an engineering context:

  1. Systems theory – sensing, modeling and control
  2. Data analytics, machine learning, computational engineering
  3. Cyber systems, embedded systems

The final POS for each student in the minor will be approved by the minor steering committee or their designate to ensure uniform program oversight.

One advantage of a minor in Cyber-Physical Systems at ISU is that, as shown above, there are currently many courses related to a variety of CPS-related topics that are being taught in various departments by our COE faculty. As new courses are developed in CPS, they can be added to this list after being approved by the minor’s curriculum coordination committee.