T-S fuzzy systems optimization identification based on FCM and PSO

designing unmanned aerial vehicle based on neuro-fuzzy systems

در این پایان نامه، کنترل نرو-فازی در پرنده هدایت پذیر از دور (پهپاد) استفاده شده است ابتدا در روش پیشنهادی اول، کنترل کننده نرو-فازی توسط مجموعه اطلاعات یک کنترل کننده pid به صورت off-line آموزش دیده است و در روش دوم یک کنترل کننده نرو-فازی on-line مبتنی بر شناسایی سیستم توسط شبکه عصبی rbf پیشنهاد شده است. سپس کاربرد این کنترل کننده در پهپاد بررسی شده است و مقایسه ای ما بین کنترل کننده های معمو...

Combining PSO and FCM for Dynamic Fuzzy Clustering Problems

T-S Neural Network Model Identification of Ultra-Supercritical Units for Superheater Based on Improved FCM

The study constructs the T-S neural network model for the superheater with multiple inputs and single output and presents an improved FCM algorithm aiming to solve the inputs’ space division problem. The function parameters of the Gaussian membership are obtained to identify the model structure and the recursive least squares method is adopted to identify model parameters. Simulations results s...

Switching fuzzy modelling and control scheme using T-S fuzzy systems with nonlinear consequent parts

This paper extends the idea of switching T-S fuzzy systems with linear consequent parts to nonlinear ones. Each nonlinear subsystem is exactly represented by a T-S fuzzy system with Lure’ type consequent parts, which allows to model and control wider classes of switching systems and also reduce the computation burden of control synthesis. With the use of a switching fuzzy Lyapunov function, the...

A Novel Identification Method for Generalized T-S Fuzzy Systems

In order to approximate any nonlinear system, not just affine nonlinear systems, generalized T-S fuzzy systems, where the control variables and the state variables, are all premise variables are introduced in the paper. Firstly, fuzzy spaces and rules were determined by using ant colony algorithm. Secondly, the state-space model parameters are identified by using genetic algorithm. The simulati...