| VCU | School of Engineering | Sensory Intelligent Lab |

Graduate Standing

  • ENGR 691: Pattern Recognition
    Credits: 3 (3 lecture hours and some project hours)
    Lectures: Wed 2:00 –at ENGB 235


    Description : This course will give an introduction to statistical pattern classification. The fundamental background for the course is probability theory, especially for selected topics on classification and clustering. The course is suitable for students in engineering, mathematics, or computer science who have a basic background in calculus, linear algebra, and probability theory. The students should also have some interest in exploring the field of pattern recognition.
    Prerequisites : Graduate Standing, or Instructor's permission


  • ENGR 691/591: Intelligent Systems
    Credits: 3 (3 lecture hours and some project hours)
    Lectures: Tue/Thr 4:00 –at ENGB 235


    Description : The first half of the course will give basic ideas in artificial intelligence from the perspective of building intelligent agents, which the authors in the textbook define as "anything that can be viewed as perceiving its environment through sensors and acting upon the environment through effectors. The second half of the course will give an introduction into autonomous mobile robotic systems. History, motivation, challenges, applications, and practical aspects of robot development will be discussed. The student will work as part of a team to develop one or more autonomous robots to accomplish predefined tasks. The course will cover such topics as problem definition, sensing, actuation, control, mobility, power, and data processing.
    Prerequisites : Graduate Standing, or Instructor's permission


  • ENGR 555: Dynamic & Multivariable Control
    Credits: 3 (3 lecture hours and some project hours)
    Lectures: Tue/Thr 9:30-10:45am –at ENGB 235


    Description : This course covers the use of state space methods to model analog and digital linear and nonlinear systems. Emphasis is placed on the student gaining mathematical modeling experience, performing sensitivity and stability analysis and designing compensators to meet systems specifications. Topics treated will include a review of root locus and frequency design methods, linear algebraic equations, state variable equations, state space design and digital control systems (principles and case studies). The students will use complex dynamic systems for analysis and design. The laboratory will consist of modeling and control demonstrations and experiments single-input/single-output and multivariable systems, analysis and simulation using matlab control toolbox and other control software.
    Prerequisites : Graduate Standing, or MATH 301 Differential Equations, and MATH 310 Linear Algebra or the equivalent.


Undergraduate Standing

  • ENGR 454: Automatic Controls
    Credits: 4 (3 lecture hours and 3 laboratory hours)
    Lectures: Tue/Thr 12:30 – 1:45am at ENGB 104
    Labs: M 5:30-8:30pm at ENGB 308B

    Description : This course covers the design and analysis of linear feedback systems. Emphasis is placed upon the student gaining mathematical modeling experience and performing sensitivity and stability analysis. The use of compensators to meet systems design specifications will be treated. Topics include: an overview and brief history of feedback control, dynamic models, dynamic response, basic properties of feedback, root-locus, frequency response and state space design methods. The laboratory will consist of modeling and control demonstrations and experiments single-input/single-output and multivariable systems, analysis and simulation using matlab/simulink and other control system analysis/design/implementation software. Junior or senior standing mainly for Mechanical, Electrical, and Computer Engineering.
    Prerequisites : EGRE 335, ENGR 305, or ENGR 315


  • ENGR 335: Signals and Systems I
    Credits: 4 (3 lecture hours and 3 hours teaching lab)
    Lectures: Mon/Wed 4:00 –at ENGB 235


    Description : Presents the concept of linear continuous-time and discrete-time signals and systems, their classification, and analysis and design using mathematical models. Topics to be covered: the concepts of linear systems and classification of these systems, continuous-time linear systems and differential and difference equations, convolution, frequency domain analysis of systems, Fourier series and Fourier transforms and their application, and continuous-time to discrete-time conversion, and Laplace transformation and Transfer function representation.
    Prerequisites : ENGR 206 Electric Circuits, ENGR 245 Engineering Programming Using C, and MATH 301 Differential Equations.