this paper works on the concept of flatness and its practical application for the design of an optimal transient controller in a synchronous machine. the feedback linearization scheme of interest requires the generation of a flat output from which the feedback control law can easily be designed. thus the computation of the flat output for reduced order model of the synchronous machine with simp...

in this paper, a reaction system consisting of two parallel, non-isothermal autocatalytic reactions in a continuous stirred tank reactor (cstr) has been considered. reactor chaotic behavior is possible for certain values of system parameters. two types of controllers are designed and compared in order to control both the reactor temperature and the product concentration. the first controller is...

In this paper, we develop a method to design the input control to track the output of a nonminimum-phase nonlinear systems asymptotically. The design of the control inputs is based on an exact linearization. To perform the exact linearization, the other output should be selected such that its relative degree is equal to the dimension of the system. Furthermore, the desired output of the output ...

a digital look-up table adaptive predistortion technique using a six-port receiver for power amplifier linearization is presented. the system is designed in ka-band for a dvb-s2 satellite link. we use a six-port receiver at the linearizationloop in place of classic heterodyne receivers. the six-port receiver is implemented by the use of passive microwavecircuits and detector diodes. this approa...

The paper deals with a problem of linearization of multi-output logic functions. Specifically, the case is discussed, when the functions have a large number of variables and cannot be efficiently linearized by using known techniques. For solution of the problem a socalled piecewise linearization is proposed. The piecewise linearization comprises decomposition of an initial multi-output function...

u = a(x) + b(x)v, (3) where b(x) is a nonsingular matrix, and v ∈ Rp is a transformed or virtual input, so that the inputoutput response between v and y is linear. This requirement is called input-output linearization because only the input-output map h is made linear. On the other hand, full state linearization refers to the case when the whole state x must be “linearized”. Linearization of th...

u = a(x) + b(x)v, (3) where b(x) is a nonsingular matrix, and v ∈ Rp is a transformed or virtual input, so that the inputoutput response between v and y is linear. This requirement is called input-output linearization because only the input-output map h is made linear. On the other hand, full state linearization refers to the case when the whole state x must be “linearized”. Linearization of th...

Black-box modeling techniques based on artificial neural networks are opening new horizons for modeling and controlling nonlinear processes in biotechnology and chemical process industries. The link between dynamic process models and actual process control is provided by the concept of model based control (MBC), e.g. Internal Model Control (IMC) or Model Based Predictive Control (MBPC). To avoi...