An Improved Model-Free Adaptive Nonlinear Control and Its Automatic Application

Improved Model Predictive Control and Its Application

* Corresponding author: [email protected] Abstract: This paper presents a modified form of model based predictive control that exploits the concept of non-trivial terminal state weighting in the cost function. While maintaining simplicity of implementation, the performance of this algorithm is not sacrificed and the computational burden compared with traditional approaches is greatly reduc...

Improved Optimization Process for Nonlinear Model Predictive Control of PMSM

Model-based predictive control (MPC) is one of the most efficient techniques that is widely used in industrial applications. In such controllers, increasing the prediction horizon results in better selection of the optimal control signal sequence. On the other hand, increasing the prediction horizon increase the computational time of the optimization process which make it impossible to be imple...

Model Free Adaptive Control

Application of a Direct Model Reference Adaptive Controller (DMRAC) in a Nonlinear Cardiovascular Model

The objective of this study is to design a robust direct model reference adaptive controller (DMRAC) for a nonlinear cardiovascular model over a range of plant parameters representing a variety of physical conditions. The direct adaptive controllers used in thisd study require the plant to be almost strictly positive real (ASPR) that is, for a plant to be controlled there must exist a feedback ...

An Improved Back Propagation Neural Network Model and Its Application

Abstrac—t-Stroke is one of the most serious disease, and the incidence rate of stroke is confirmed to be related to environmental factors including temperature, pressure and humidity .In order to obtain the relationship between the incidence rate and environmental factors , we research on local daily meteorological data and stroke disease cases from January 2008 to December 2012, which is provi...