**Spring 95:**

**DYNAMICS AND CONTROL OF FLEXIBLE STRUCTURES**: This course introduces the subject of dynamics and control of flexible structures in both mechanical and aerospace applications. It is a combination of mathematics, control theory, and dynamics. The following topics are covered: review of basic mathematical background (ordinary differential equations, linear algebra), models of flexible structures in second-order and first-order forms, frequency response functions, continuous and discrete-time representation of dynamic systems, work-energy rate principle, Liapunov stability, observability and controllability, observer and Kalman filter, state-feedback control, output-feedback control.

**Fall 95-Fall
98:**

**ENGINEERING DYNAMICS:**This course gives an introduction to vibration analysis of mechanical systems. The following topics are covered: equations of motion, free response of single-degree-of-freedom system, forced response under harmonic, periodic, and non-periodic excitation, transient and steady state responses, beat phenomenon, matrix approach to the analysis of multi-degree-of-freedom systems, frequencies, damping factors, mode shapes, Lagrange's equations, lumped and distributed parameter systems, discretization methods, vibration absorbers, introduction to structural control.

**Spring 96,
Spring 98:**

**SYSTEM IDENTIFICATION**: This course gives an introduction to system identification theory and its applications to mechanical and aerospace systems. The following topics are covered: review of mathematical foundations, discrete-time and continuous-time models, state-space and input-output models, Markov parameters and observer Markov parameters, discrete Fourier transform, frequency response functions, singular value decomposition, least-squares parameter estimation, minimal realization theory, Observer/Kalman filter identification (OKID), recursive identification techniques, and introduction to adaptive estimation and control theory.

**Spring 97:**

**OPTIMAL CONTROL AND ESTIMATION**: This course gives an introduction to stochastic optimal control theory and application. The following topics are covered in the course: mathematical foundations, parametric optimization, conditions for optimality, linear quadratic regulator (LQR) numerical optimization, and neighboring-optimal solutions. Least-squares estimates, propagation of state estimates and uncertainty, and optimal filters and predictors; optima control in the presence of uncertainty, certainty equivalence and the linear-quadratic-Gaussian regulator problem (LQG), frequency domain solutions and robustness of closed-loop control.

**Spring 99:**

**LEARNING CONTROL AND SOFT COMPUTING**: Learning control deals with the problem of synthesizing an appropriate control input to make the system produce a desired action by repeated trials without having to know detailed knowledge of the system under control. This concept imitates human learning by practice. This course will study the current theory of learning control and its connection to repetitive control, adaptive control, and system identification. Modern topics such as genetic algorithm, fuzzy logic, and neural networks will also be explored.

**Spring 00:**

**MODERN CONTROL**: Introduction to modern state-space methods for control system design and analysis with applications to multiple-input multiple-output dynamical systems, including robotic systems and flexible structures. The following topics are covered: state-space representation of systems, continuous-time and discrete-time representations, controllability and observability, state feedback control, stability, state estimation, observer design, input-output models, static and dynamic output feedback control, optimal control design methods, and introduction to state-space system identification.

**Fall 00:**

**SOLID MECHANICS**: After a brief review of rigid body statics, the field equations describing the static behavior of deformable elastic solids are developed. The stress and strain tensors are introduced and utilized in the development. Exact and approximate solutions of the field equations are used in the study of common loading cases, including tension/compression, bending, torsion, and pressure. In the laboratory component of the course, various methods of experimental solid mechanics are introduced. Some of these methods are used in a laboratory project in which the deformation and stress in an actual load system (wood bridge project) are determined and compared with theoretical predictions.