A textbook authored by a University of Missouri-Rolla professor will soon help students at universities across the country discover the importance of nonlinear control using neural networks.
Dr. Jagannathan Sarangapani, professor of electrical and computer engineering at UMR, is the author of “Neural Network Control of Nonlinear Discrete-Time Systems,” recently published by Taylor and Francis (or CRC Press). This is his second textbook with 10 chapters. His first book appeared in 1999 and is widely used at universities around the world.
Loosely based on the inner workings of the human brain, a neural network is used in computational science to study and analyze complex phenomena. Sarangapani’s book presents modern control techniques, which he bases on the parallelism and adaptive capabilities of biological nervous systems.
Sarangapani, who has invented several neural network-based techniques to diagnose engine problems, introduces neural networks, dynamical systems, control of nonlinear systems, and feedback linearization in the textbook. He also explains system identification, model reference adaptive control, and novel optimal control using the Hamilton-Jacobi-Bellman formulation.
Sarangapani has been a UMR faculty member since 2001. He received a bachelor of science degree in 1986 from Anna University in Tamil Nadu, India. Sarangapani earned a master of science degree in 1989 from the University of Saskatchewan at Saskatoon, Canada, and a Ph.D. in 1994 from the University of Texas at Arlington.
Prior to coming to UMR, Sarangapani served as assistant professor and director of the intelligent systems laboratory in the electrical and computer engineering department at the University of Texas at San Antonio. He also worked four years with Caterpillar Inc. in Peoria, Ill., as a program manager in the systems and controls research division. He holds 17 patents.