Master of Science, The Ohio State University, 2013, Aero/Astro Engineering

This thesis addresses the importance and issues of the robust control design of linear time-invariant (LTI) systems with real-time parameter uncertainties. It is known that most of the existing robust control techniques are fairly conservative when dealing with real time parameter uncertainty. Also, majority of these existing techniques use control gains that are essentially functions of the perturbation information. The robust control design algorithm proposed in this thesis differs from these traditional techniques by focusing on the control design in achieving a specific structure of the closed loop system matrix that guarantees a maximum stability robustness index as possible without the using any of the perturbation information. The determination of this specific desired structure of closed loop system matrix forms the focal point of this algoithm and is inspired by already existing principles in the field of ecology. Using this ecological backdrop, the desired closed loop matrix is determined to contain self regulated species with predator-prey interactions among these species. In matrix nomenclature, such a set of matrices are labelled as Target Pseudo-Symmetric (TPS) matrices and hence form the class of desirable closed-loop system matrices. Based on these TPS matrices, which capture the maximum robustness index for any LTI system, a robust control design is carried out such that the final closed loop system possesses a robustness index as close to this maximum as possible. The robust control design algorithm presented is based on minimizing the norm of an implicit error and is supported with several illustrative examples. This eco-inspired robust control algorithm exemplifies the strong correlation that exists between natural systems and engineering systems. Hence, the main goal of this thesis is to aid in the revival of research in the field of robust control using insights from ecological principles.

Committee: Rama Yedavalli Dr. (Advisor); Chia-Hsiang Menq Dr. (Committee Member) Subjects: Aerospace Engineering; Applied Mathematics; Automotive Engineering; Ecology; Engineering; Mathematics Education; Mechanical Engineering