Graduation Semester and Year




Document Type


Degree Name

Doctor of Philosophy in Aerospace Engineering


Mechanical and Aerospace Engineering

First Advisor

Kamesh Subbarao


The duality of estimation and control problems is a well known fact in control theory literature. Parameter convergence and closed loop stability are usually competing interests for a given control scheme. This motivates identification routines to be performed only in offline experiments. On the other hand stable controllers do not guarantee parameter convergence to true parameters. Thus there is a need for a higher level abstraction for a control scheme which acts in stages and prioritizes various aspects at different stages. The stage abstraction for controller is inspired by human intuition towards dealing with control and identification simultaneously and hence named Intuitive control framework. The first stage prioritizes stabilization of states only. The controller moves onto the next stage after the unknown system is stabilized. The subsequent stages involves optimization with different performance metrics through adaptive learning. After enough information for identification is acquired, the control schemes developed for various optimal metrics are used to estimate the unknown parameters in the final stage. This narrative for selective prioritization of objectives and a higher level abstraction for control schemes is illustrated for a continuous linear time invariant state space realization with state feedback. Numerous real-world applications can benefit from this online system identification routine inspired by the human cognitive process. This offers a seamless integration of control and identification with a higher level of priorities. Such framework is presented with explicit formulations for certain classes of dynamic systems, and evaluated with computer simulations as well as experimental results. Further computation of forward reachable sets after identification also offers the only way to perform such computation for an unknown system without the need for experimentation. Identified reachable sets are also presented with a discussion on their accuracy.


Aerospace Engineering | Engineering | Mechanical Engineering


Degree granted by The University of Texas at Arlington