W-C Cheng

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About

W-C Cheng is a researcher whose work sits at the intersection of computational intelligence, nonlinear system identification, and fault detection. Drawing inspiration from biological immune systems, Cheng has pioneered the application of artificial immune system (AIS) frameworks to complex engineering challenges that traditional methods struggle to address effectively. Cheng's most recognized contribution, a 2001 paper on nonlinear system identification using artificial immune systems (13 citations), introduced a novel methodology combining a simplified incremental approach with the maximum entropy principle and an instantaneous feedback mechanism — an elegant solution for reorganizing and adapting system models in real time. Building on this foundation, Cheng extended the immune-inspired paradigm into the domain of fault detection, presenting an innovative model-based approach for nonlinear systems. This work, published in 2004 and accumulating nearly 17 citations across related publications, demonstrated how immune models could generate reliable residuals for fault diagnosis, with the orthogonal least-squares method employed to identify the most significant receptor vectors. Collectively, Cheng's research has helped establish artificial immune systems as a credible and powerful tool in systems engineering, offering students and researchers a biologically grounded yet mathematically rigorous alternative for tackling identification and diagnostic problems in nonlinear domains.