 Teaching Philosophy
 Although the beauty of control theories attracts many engineers, the inherent limitations of control theories are unavoidable in practice. Most of the control theories assume that a plant is given and seek a solution to obtain the desired performance by suggesting an appropriate control algorithm. RSC Lab’s research issues are all based on a fundamental question that the application of control theories should start from the beginning of mechanical design. Namely, the mechanical system should be designed considering the controllability and observability of the plant, such that the system has the minimal limitations in the controller design. Also, the controller design process should suggest both control parameters and mechanical design parameters for obtaining the most effective and energyefficient control performance. Therefore, students of RSC Lab learn both the mechanical design and control theories in an integrated way. This education philosophy may be different from typical educations in the field of Mechatronics or Robotics in a viewpoint that it deals with the interdisciplinary crossapplication of the mechanical design and control theories.
 Prof. Kyoungchul Kong, the director of RSC Lab, gives the following lectures.
 Graduate Courses
 Linear System Control (ME561)
 This lecture introduces general concepts for control of a class of linear systems. The “linear” system does not only mean an ideal system described by equations of motions, but also includes an actual mechanical system, the dominant dynamic behavior of which can be assumed to be linear. In order to deal with linear systems, this lecture first introduces linear system theory for understanding and modeling of linear systems. Linear control theory including state space descriptions, controllability/observability, transfer functions, timedomain analysis and stability are then introduced. The realworld systems, however, always show uncertainties in the dynamic characteristics, and thus this lecture also introduces robust control theory, such as small gain theorem and Hinfinity optimal control, for dealing with systems with uncertain dynamics. In this course, various numerical and mathematical methods will be introduced to design control algorithms.
 Digital System Control (ME562)
 This course is a comprehensive introduction to control system synthesis in which the digital computer plays a major role. The course covers elements of realtime computer architecture; inputoutput interfaces and data converters; analysis and synthesis of sampleddata control systems using classical and modern (statespace) methods; analysis of tradeoffs in control algorithms for computation speed and quantization effects. In addition to the fundamental theory in digital system control, this course introduces advanced control techniques such as discretetime linear quadratic control, adaptive control, parameter adaptation, repetitive control, learning control, and so on. Homework includes computer simulations where students can experience practical digital servo interfacing and implementation problems with timing, noise, and other practical issues.
 Undergraduate Courses
 Modeling and Control of Engineering System (ME361)
 The content of this lecture is to learn the principles, methods and techniques of modeling and controlling of engineering systems such as mechanical, electrical/electromechanical systems in theory and experimental aspects. This course focuses on proportional, integral, and derivative (PID) controllers and rootlocus techniques to design such controllers.
 Mechatronics
 In this lecture, mandatory knowledge for designing mechatronic systems are introduced, and an Arduino board is provided to every student for individual handson experience. The examples given to the students include the use of a motor driver and other fundamental electric components, the construction of a motor control system, the implementation of signal processing algorithms, and so on. The final term project is to develop a wheeled inverted pendulum from scratch, and students are evaluated mainly by the experimental results of their own system.
 Mechanical Systems Analysis
 This lecture introduces mathematical methods used in Mechanical Engineering, in particular linear algebra. This course reviews linear algebra covered in Engineering Mathematics, e.g., matrix arithmetic and determinants, vector spaces, eigenvalues and eigenvectors, linear transformations, homogeneous ordinary differential equations, and Fourier series.
 Linear Vibrations
 This is a typical linear vibrations course, which covers fundamentals in mechanics (e.g., linear system theory, Newtonian mechanics, Lagrangian mechanics, and state space realization), frequency and Laplace domain analyses of mechanical vibration systems, free and forced vibrations of lumped mass systems, and vibrations of distributed parameter systems.
 Materials helpful for students will be posted soon.
