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 paper, the problem of distributed adaptive consensus tracking control for second-order nonlinear heterogeneous multi-agent systems (MASs) with input quantization is considered. A output feedback scheme based on a K-filter developed to suppress influences unknown disturbances and quantization. contrast existing approaches, an additional design parameter introduced into controller ensure ...

This work considers the problem of control actuator fault detection and isolation and fault-tolerant control for a multi-input multi-output nonlinear system subject to constraints on the manipulated inputs and proposes a fault detection and isolation filter and controller reconfiguration design. The implementation of the fault detection and isolation filters and reconfiguration strategy are dem...

Abstract: In this paper, the controller introduced represent, at the best knowledge of the authors, the first application of feedback linearization technique to control a Twin Rotor Multi-input Multi-output System (TRMS). With the coupling effects considered as the uncertainties, the highly coupled nonlinear TRMS is decomposed into a horizontal and a vertical subsystem. Then, two control laws a...

Hardware realization of a Neural Network (NN), to a large extent depends on the efficient implementation of a single neuron. FPGA-based reconfigurable computing architectures are suitable for hardware implementation of neural networks. FPGA realization of ANNs with a large number of neurons is still a challenging task. This paper discusses the issues involved in implementation of a multi-input ...

In this contribution, the identification and control of nonlinear SMBchromatographic processes are discussed. Instead of using the physical manipulated process variables, the flow rates of extract, desorbent, and recycle, and the switching time directly, a new set of input variables ( -factors) is employed as control inputs to reduce input/output couplings. A new measure of the front positions ...