Autonomous systems have secured a unique and expanding role in commercial and military applications. Self driving cars, agricultural applications, communication relay nodes, space exploration, and long-duration surveillance missions are examples. Control theory plays a central role in making these systems autonomous. This course will teach advanced control system design methods used in developing autonomous systems using real-world aerospace models.
The level of control theory used industry has advanced significantly in the last 20 years. Using my experiences gained in developing aerospace control systems I have configures this course to teach what an engineering student needs to know to work in industry today, and in the future. The control design and analysis examples used throughout the course are real examples of autonomous systems.
This course will cover graduate-level control system design methods for multi-input multi-output linear dynamic systems. Specific topics include: Advanced design and analysis of control systems by state-space methods: classical control review, Laplace transforms, review of linear algebra (vector space, change of basis, diagonal and Jordan forms), linear dynamic systems (modes, stability, controllability, state feedback, observability, observers, canonical forms, output feedback, separation principle and decoupling), nonlinear dynamic systems (stability, Lyapunov methods). Frequency domain analysis of multivariable control systems using singular values. State space control system design methods: state feedback, observer feedback, pole placement, linear optimal control and the robust servomechanism. Robustness theory and analyzing the sensitivity to knowing model parameters. Control design and analysis exercises will be used to reinforce learning of the theory with Matlab-based CAD (computer-aided design) projects that use real aerospace system models.
Goals: Develop the mathematical background and sophistication required to understand the fundamentals of modern control and systems theory used in industry. Learn the concepts involved in modern control and systems theory, in order to prepare for more advanced topics and courses, permit self-learning and enable you to approach and solve real-world problems with confidence.
Figure. Shown is the fully autonomous X-45A Joint-Unmanned Combat Air System which was an open-loop unstable aircraft. Control system design models from the X-45A are used in the course to show how to achieve control system performance with robustness.
Who Should Attend?
Students enrolled in the M Eng.ME Program interested in learning control system design methods used in industry.
Prerequisite: Undergraduate Control and Dynamics Course.
Textbook: Lavretsky and Wise, Robust and Adaptive Control with Aerospace Applications
Course Outline: This 16-week semester course will consist of weekly lectures and assignments covering the theoretical material, with a midterm exam and final exam.
1. Review of dynamic system models and classical control concepts, design and analysis.
2. Mathematical background for modern control and systems: review of matrix algebra, linear vector spaces and operators, eigenvalues and eigenvectors, Cayley-Hamilton Theorem
3. Qualitative aspects of linear systems theory: State-space representation of linear systems, controllability, reachability, observability, Kalman decomposition of the state-space
4. Frequency domain analysis of multivariable systems. Return difference matrix, sensitivity and complementary sensitivity, singular value frequency response methods, guaranteed stability margins for linear quadratic regulators. Stability robustness methods for complex and real uncertainties.
5. Quantitative aspects of linear systems theory: Pole placement and state feedback controllers, output feedback, observers and the separation principle, stabilizability and detectability
6. Optimal control system design: Linear quadratic optimal control
Computer Usage: Student projects are assigned that requires the use of Matlab software. The projects includes control design, simulation, and frequency domain analysis.
Homework and Projects 50%
Midterm, Final Exam 50%
Kevin A. Wise is a Senior Technical Fellow, Advanced Flight Controls, in the Phantom Works division of The Boeing Company, is President and CEO of Innovative Control Technologies, LLC, (http://inncontech.com/) and is a Chief Advisor at Kelda Drilling Controls (http://www.kelda.no/) in Norway. He received his BS, MS, and Ph.D. in Mechanical Engineering from the University of Illinois in 1980, 82, and 87, respectively. Since joining Boeing in 1982, he has developed vehicle management systems, flight control systems, and control system design tools and processes for advanced manned and unmanned aircraft and weapon systems. Some recent programs include KC-46 Tanker boom, Dominator UAS, Phantom Eye Hydrogen Powered UAS, QF-16 Full Scale Aerial Target, X-45 J-UCAS, X-36, and JDAM. His research interests include intelligent autonomy and battle management, aircraft dynamics and control, robust adaptive control, optimal control, robustness theory, and intelligent drilling solutions. He has authored more than 100 technical articles and seven book chapters; he has published a textbook titled Robust and Adaptive Control Theory, with Aerospace Examples; and he teaches control theory at Washington University in St. Louis. Dr. Wise is a member of the National Academy of Engineering, is the recipient of the AIAA Intelligent Systems Award (2018), IEEE Technical Excellence in Aerospace Control Award (2016), IFAC/AACC Control Engineering Practice Award (2007), and the AIAA Mechanics and Control of Flight Award (2004). He is an IEEE Fellow, and Fellow of the AIAA.