Guaranteed Performance Adaptive Control (GPAC) for Aerospace Applications

The major objectives of this project are: (i) To develop relevant performance metrics for adaptive systems, and (ii) To design guaranteed performance adaptive controllers using an adaptive Multiple Models, Switching and Tuning (MMST) approach. This is a highly complex problem that has not been solved so far even for linear systems. The key capability that the proposed work will provide is to assure consistent performance in adaptive control of time-varying and nonlinear systems under large uncertainties. Our objective is to build upon SSCI's extensive work in this field and derive theoretical conditions under which performance of the overall adaptive system can be guaranteed in the case of linear time-invariant and time-varying systems, and some classes of nonlinear systems. Successful theoretical developments will facilitate Verification and Validation (V&V) procedures and flight certification of adaptive flight control software. In order to achieve the project objectives, in Phase I we propose to carry out the following tasks: (i) Problem Formulation; (ii) Development of a Simulation Testbed based on Autonomous Aerial Refueling (AAR); (iii) Development of Guaranteed Performance Adaptive Control (GPAC) Algorithms; (iv) Initial Study of the Finite-time Stability of the Switching Strategies; and (v) Implementation & Performance Evaluation of the GPAC Algorithms on the Simulation Testbed. Professor K. S. Narendra of Yale University, who is world-renown for his fundamental contributions to adaptive control, will provide theoretical support under the project. Phase II will involve high-fidelity and piloted simulations in collaboration with Boeing, who will also provide commercialization support in Phase III.