this paper presents a theoretical approach to implementation of the “multi-realization of nonlinear mimo systems”. this method aims to find state-variable realization for a set of systems, sharing as many parameters as possible. in this paper a special nonlinear multi-realization problem, namely the multi-realization of feedback linearizable nonlinear systems is considered and an algorithm for ...

this paper is concerned with the consensus tracking problem of high order mimo nonlinear multi-agent systems. the agents must follow a leader node in presence of unknown dynamics and uncertain external disturbances. the communication network topology of agents is assumed to be a fixed undirected graph. a distributed adaptive control method is proposed to solve the consensus problem utilizing re...

this article deals with the issues associated with developing a new design methodology for the nonlinear model-predictive control (mpc) of a chemical plant. a combination of multiple neural networks is selected and used to model a nonlinear multi-input multi-output (mimo) process with time delays.  an optimization procedure for a neural mpc algorithm based on this model is then developed. the p...

in this paper, the portfolio selection problem is considered, where fuzziness and randomness appear simultaneously in optimization process. since return and dividend play an important role in such problems, a new model is developed in a mixed environment by incorporating fuzzy random variable as multi-objective nonlinear model. then a novel interactive approach is proposed to determine the pref...

This paper presents a theoretical approach to implementation of the “Multi-realization of nonlinear MIMO systems”. This method aims to find state-variable realization for a set of systems, sharing as many parameters as possible. In this paper a special nonlinear multi-realization problem, namely the multi-realization of feedback linearizable nonlinear systems is considered and an algorithm for ...

in this paper we propose a relatively new semi-analytical technique to approximate the solution ofnonlinear multi-order fractional differential equations (fdes). we present some results concerning to the uniqueness of solution of nonlinear multi-order fdes and discuss the existence of solution for nonlinear multi-order fdes in reproducing kernel hilbert space (rkhs). we further give an error an...

in this study, we modify an iterative non-optimal without memory method, in such a way that is becomes optimal. therefore, we obtain convergence order eight with the some functional evaluations. to justify our proposed method, some numerical examples are given.

In this paper we propose a relatively new semi-analytical technique to approximate the solution of nonlinear multi-order fractional differential equations (FDEs). We present some results concerning to the uniqueness of solution of nonlinear multi-order FDEs and discuss the existence of solution for nonlinear multi-order FDEs in reproducing kernel Hilbert space (RKHS). We further give an error a...

drought is random and nonlinear phenomenon and using linear stochastic models, nonlinear artificial neural network and hybrid models is advantaged for drought forecasting. this paper presents the performances of autoregressive integrated moving average (arima), direct multi-step neural network (dmsnn), recursive multi-step neural network (rmsnn), hybrid stochastic neural network of directive ap...

in this study, a new efficient semi-analytical method is introduced to give approximate solutions of strongly nonlinear oscillators. the proposed method is based on combination of two different methods, the multi-step homotopy analysis method and spectral method, called the multi-step spectral homotopy analysis method (msham). in this method, firstly, we propose a new spectral homotopy analysis...