this paper extends the sequential learning algorithm strategy of two different types of adaptive radial basis function-based (rbf) neural networks, i.e. growing and pruning radial basis function (gap-rbf) and minimal resource allocation network (mran) to cater for on-line identification of non-linear systems. the original sequential learning algorithm is based on the repetitive utilization of s...

This paper gives idea about design method for adaptive neural controller is proposed and it applied to the non-linear system Continuous stirred tank reactor CSTR. The investigating used in this designed tuned with process. To analyze performance of effect foot print uncertainty on controllers’ two various types algorithms namely state feedback control observer based are Radial basis function Ne...

The study proposes a new simple output feedback adaptive tracking control scheme using neural network for a class of complicated modern agricultural mechanical systems that only the system output variables can be measured. The scheme avoids design state observer and Lipschiz assumption, SPR conditions are not required and few parameters in control laws and weights update laws need to be tuned. ...

This paper details the application of an adaptive neural network based limit detection and avoidance algorithm for envelope protection on the autonomous Yamaha R-Max unmanned helicopter test bed. Software-in-the-loop and flight test results are presented. The envelope protection system is implemented as a mid-level controller component into the unmanned helicopter software infrastructure, calle...

 An adaptive input-output linearization method for general nonlinear systems is developed without using states of the system. Another key feature of this structure is the fact that, it does not need model of the system. In this scheme, neurolinearizer has few weights, so it is practical in adaptive situations.  Online training of neuroline...

Novel direct adaptive robust state and output feedback controllers are presented for the output tracking control of a class of nonlinear systems with unknown system dynamics and disturbances. Both controllers employ a variable-structure radial basis function (RBF) network that can determine its structure dynamically to approximate unknown system dynamics. Radial basis functions are added or rem...

in the present work, the influences of temperature, solvent concentration and ultrasonic irradiation time were numerically analyzed on viscosity reduction of residue fuel oil (rfo). ultrasonic irradiation was applied at power of 280 w and low frequency of 24 khz. the main feature of this research is prediction and optimization of the kinematic viscosity data. the measured results of eighty-four...