MAGnetic LEVitation (Maglev) is a multi-variable, non-linear and unstable system that is
used to levitate a ferromagnetic object in free space. This paper presents the stability control …

This paper presents a new control method for nonlinear discrete-time systems, described by
an input-output model which is based on a combination of quasi-sliding mode and neural …

A new intelligent hybrid structure used for online tuning of a PID controller is proposed in this
paper. The structure is based on two adaptive neural networks, both with built-in Chebyshev …

This paper presents a new method for modelling of dynamic systems by using specially
designed orthogonal polynomial neural networks. These networks utilize the feature that the …

This paper presents one possible application of generalized quasi-orthogonal functional
networks in the sensitivity analysis of complex dynamical systems. First, a new type of first …

This paper presents a new approach for improving performances of magnetic levitation
system. Controlled parameter is the amplitude which levitated object achieves during …

This paper presents some of the results and contributions to the theory of orthogonal
polynomials, orthogonal functions and corresponding filters, achieved in the last fifteen …

Dynamic pricing is a pricing technique in which companies set extremely flexible costs for
products or services based on customer demands. Dynamic pricing is famous because of its …

This paper presents a new type of endocrine neural network (ENN). ENN utilizes artificial
glands which enable the network to be adaptive to external disturbances. Sensitivity is …

This paper deals with the design of a digital sliding mode based minimum variance control
on the basis of a discrete-time representation of the ABS model derived from a new type of …