Fully Tuned Radial Basis Function Neural Networks for Flight Control
presents the use of the Radial Basis Function (RBF) neural networks for
adaptive control of nonlinear systems with emphasis on flight control
applications. A Lyapunov synthesis approach is used to derive the tuning
rules for the RBF controller parameters in order to guarantee the
stability of the closed loop system. Unlike previous methods that tune
only the weights of the RBF network, this book presents the derivation
of the tuning law for tuning the centers, widths, and weights of the RBF
network, and compares the results with existing algorithms. It also
includes a detailed review of system identification, including indirect
and direct adaptive control of nonlinear systems using neural
networks.
Fully Tuned Radial Basis Function Neural Networks for Flight Control
is an excellent resource for professionals using neural adaptive
controllers for flight control applications.