Real-time reconfigurable control system design using on-line neural estimator

The growing demand in system reliability and survivability under failures has urged ever-increasing research effort on the development of fault diagnosis and accommodation. In this paper, the on-line fault tolerant control problem for dynamic systems under unanticipated failures is investigated from a realistic point of view without any specific assumption on type of system dynamical structure or failure scenarios. The sufficient condition for system on-line stability under catastrophic failures has been derived using the discrete-time Lyapunov stability theory. Based upon the existing control theory and the modern intelligent techniques, an on-line fault accommodation control strategy is proposed to deal with the desired trajectory-tracking problems for systems suffering from various unknown and unanticipated catastrophic failures. To investigate the feasibility of the developed technique for unanticipated fault accommodation in real hardware under the real-time environment, an on-line fault tolerant control test bed has been constructed to validate the proposed technology. Both on-line simulations and the real-time experiment show encouraging results and promising futures of on-line real-time fault tolerant control based solely upon insufficient information of the system dynamics and the failure modes