– When using the Lyapunov synthesis approach to construct a stable fuzzy control system, one important way is to regard the fuzzy systems as approximators to approximate the unknown functions in the system to be controlled. Concerning the unknownness of the unknown functions, generally there are two cases: a completely unknown case, and a partly unknown case. However, most of the schemes presen...

I. Fuzzy adaptive principle Fuzzy control based on fuzzy set theory, fuzzy linguistic variables and fuzzy logic inference for a computer based control method widely used in the control field, as an important branch of intelligent control, fuzzy control compared with the traditional control method has the following outstanding advantages: · No precise mathematical model of controlled object; · U...

In this paper, the stability analysis of a GA-Based adaptive fuzzy sliding model controller for a nonlinear system is discussed. First, a nonlinear plant is well-approximated and described with a reference model and a fuzzy model, both involving FLC rules. Then, FLC rules and the consequent parameter are decided on via an Evolved Bat Algorithm (EBA). After this, we guarantee a new tracking perf...

A new kind of multivariable adaptive fuzzy decoupling controller is present for Aero-engine, which consists of multivariable fuzzy decoupling control and fuzzy model reference learning control. A fuzzy inverse model is used to produce and adjust fuzzy rules online. The simulation results show that this controller is effective.

Active filters are widely employed in distribution system to reduce the harmonics produced by non-linear loads result in voltage distortion and leads to various power quality problems. In this work the simulation study of a Adaptive hysteresis based fuzzy logic controlled shunt active power filter capable of reducing the total harmonic distortion i s presented. The advantage of fuzzy control is...

This paper presents a robust Adaptive Fuzzy Neural Controller (AFNC) suitable for identification and control of a class of uncertain MIMO nonlinear systems. The proposed controller has the following salient features: (1) Selforganizing fuzzy neural structure, i.e. fuzzy control rules can be generated or deleted automatically; (2) Online learning ability of uncertain MIMO nonlinear systems; (3) ...

Abst rac t The slip power recovery configuration is an attractive scheme of variable speed drive, with high efficiency and low converter rating; however, high performance control has being difficult. In this paper, novel applications of fuzzy logic for the intelligent control of a slip power recovery system are presented. A direct fuzzy logic controller and an adaptive fuzzy controller, based o...

This study proposes a combination of a fuzzy sliding mode controller (FSMC) with integral-proportion-Derivative switching surface based superconducting magnetic energy storage (SMES) and PID tuned by a multi-objective optimization algorithm to solve the load frequency control in power systems. The goal of design is to improve the dynamic response of power systems after load demand changes. In t...

Recently, through the use of parameterized fuzzy approximators, various adaptive fuzzy control schemes have been developed to deal with nonlinear systems whose dynamics are poorly understood. An important class of parameterized fuzzy approximators is constructed using radial basis function (RBF) as a membership function. However, some tuneable parameters in RBF appear nonlinearly and the determ...

The purpose of designing the active suspension systems is providing comfort riding and good handling in different road disturbances. In this paper a novel control method based on adaptive neuro fuzzy system in active suspension system is proposed. Choosing the proper data base to train the ANFIS has an important role in increasing the suspension system’s performance. The data base which is used...