Abstract
In this paper we present an approach to fault-tolerant control based on multiple models, switching, and tuning and its implementation to a hardware-in-the-loop simulation of Delta Clipper Experimental dynamics. The Delta Clipper Experimental is characterized by large control input redundancy, which made it an ideal test bed for evaluation of advanced fault-tolerant and adaptive reconfigurable control strategies. The overall failure detection, identification, and accommodation architecture is an upgraded version of our Fast Online Actuator Reconfiguration Enhancement (FLARE) system. The FLARE approach is based on representing different possible fault and failure scenarios using multiple observers, such that the case of nominal (no-failure) operation is covered along with the loss-of-effectiveness, lock-in-place, and hardover failures of the flight control effectors. Based on a suitably chosen performance criterion, the FLARE system quickly detects single or multiple failures and reconfigures the controls, thus achieving either the original desired performance or graceful performance degradation. In the first stage of the project, the FLARE system was tested on a medium-fidelity simulation of Delta Clipper Experimental dynamics, resulting in excellent performance over a large range of single and multiple faults and failures. Following that, in collaboration with Boeing Phantom Works, the FLARE run-time code was installed at their site and tested on a hardware-in-the-loop test bed consisting of an electromechanical actuator actuating a gimballed engine as a part of a simulation of the Delta Clipper Experimental dynamics. A large number of hardware-in-the-loop simulations were run to cover a dense test-case matrix, including cases of up to 10 simultaneous control effector failures. In all cases FLARE was able to quickly and accurately detect the failures and reconfigure the controls, resulting in excellent overall system performance. In this paper we describe the Delta Clipper Experimental and its dynamics model, along with the multiple models, switching, and tuning based modification of our FLARE system. This is followed by a description ofthe experimental test bed and a discussion of the results obtained through hardware-in-the-loop testing.
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