Novel Signal Processing Algorithms to Exploit and Classify Active Sonobuoy Returns
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AbstractNot Available SSCI proposes to develop robust software-enabled intelligent control algorithms and adaptive control design toolkit for rapid controller design and prototyping for autonomous systems operating under highly unpredictable circumstances such as sensor and actuator failures, large external environmental disturbances, parametric uncertainties, and hard and safety constraints on the variables of interest. The proposed approach to solving this problem is based on the framework on Multiple Models, Switching and Tuning and Adaptive Interacting Multiple Observers for fast and accurate Failure Detection and Identification (FDI) in the presence of failures and damages; use of multiple reference models and combined robust and adaptive control for fast and efficient control reconfiguration, and Model Predictive Control (MPC) for handling different constraints. To achieve these objectives the following tasks will be carried out: (i) Failure modeling, sensitivity analysis and achievable performance determination; (ii) Design of multiple reference models and robust stabilizing controllers; (iii) Development of adaptive decentralized FDI observers (iv) Development of robust adaptive re-configurable flight control algorithms; (v) Testing, turning and performance evaluation of the control algorithms on a Boeing's Tailless Advanced Fighter Aircraft (TAFA benchmark example in collaboration with Boeing (vi) Validation of our design using the Game-theoretic approach in collaboration with UC Berkley; (prof. Sastry) (vii) Development of the Control Design software toolkit; (viii) Delivery of the Control Design Toolkit, all test results, associated documentation and final report; The FDI and MPC software modules developed by SSCI will be used as the starting point in the development of the proposed control system design software toolkit. Boeing Phantom Works will provide both technical and commercialization support on all phases of the project.
* information listed above is at the time of submission.