A decentralized adaptive approximation design for the fault tolerant control of a class interconnected feedback linearizable nonlinear systems is considered in this technical note. Multiple faults may occur in the subsystems local dynamics as well as in the interconnections between the subsystems. Linearly parameterized neural networks are used to adaptively approximate the unknown interconnection effects and changes in model dynamics due to failures. A dead-zone modification in the adaptive laws is combined with an adaptive bounding method for addressing stability and robustness issues in the presence of residual approximation errors. Outside the coverage region of the approximators, a decentralized safety control scheme is designed to steer back the trajectory by using a sliding mode approach with adaptive bounds. A simulation example is presented for illustrating the effectiveness of the proposed fault tolerant control methodology.
['Panagiotis Panagi', 'Marios M. Polycarpou']
Decentralized Fault Tolerant Control of a Class of Interconnected Nonlinear Systems