Recently the applications of unmanned systems are steadily increasing. Unmanned Surface Vessels (USV) can be used for military and rescue purposes. This paper designs a Fuzzy-LQR controller for Heading control of the USV system. A new analysis of the fuzzy system behavior presented helps to make possible precise integration of LQR features into fuzzy control. This Fuzzy-LQR controller is used t...

The main drawback of "classical" fuzzy systems is the inability to design and maintain their database. To overcome this disadvantage many types of extensions adding the adaptivity property to those systems were designed. This paper deals with one of them a new hybrid adaptation structure, called gradient-incremental adaptive fuzzy controller connecting gradient-descent methods with the so-calle...

A fuzzy controller for multivariable systems based on fuzzy controllers for the decoupled monovariable subsystems and a fuzzy compensator of the interactions is introduced. The fuzzy compensator acts as a feedforward controller. It has as inputs the outputs of the monovariable controllers considered as known perturbations and produces compensation signals which are added to the single loop cont...

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.

This paper presents an application of adaptive neuro-fuzzy (ANFIS) control for switched reluctance motor (SRM) speed. The ANFIS has the advantages of expert knowledge of the fuzzy inference system and the learning capability of neural networks. An adaptive neuro-fuzzy controller of the motor speed is then designed and simulated. Digital simulation results show that the designed ANFIS speed cont...

Abstract This paper presents the stability and rnbustncss analysis for fiizzy control system subject to paramctcr uncertainties, and the design of gains for thc fuzzy controller. Based on Lyapunov stability theory, stnbility nnd robustness conditions will be derived. The stability conditions involves only p+l linear matrix inequalities, where p i s the numbcr of rulcs of thc fuzzy controller. A...

In any of the control application, controller design is the most important part. There are different types of controller architectures available in control literature. The controller can be conventional in nature or can be intelligent in nature. The conventional controller doesn’t possess the human intelligence; where in the intelligent controller human intelligence is embed with the help of ce...

The use of a fuzzy logic controller for an active suspension system on a wheeled vehicle is investigated. Addressing the opposing goals of ride quality and bump stop avoidance are integrated into one control algorithm. Construction of the fuzzy rules base will be discussed comprehensively along with the membership function setup for both the input and output variables. Numerous quarter-car simu...

This paper presents the design and development of Neuro-Fuzzy controllers for the dc link current control in a two-terminal HVDC system. The dc link current error and its time derivative have been taken as the two inputs to the controller for deriving the control action, i.e., the firing angle of the converter. The basic structure of a Fuzzy controller has been modified to develop a Neuro-Fuzzy...

In this paper is presented a fuzzy PI controller. Fuzzy PI controller and principles their performing is considered in large applications. Based on a qualitative descripion of the system to be controlled, fuzzy controller is capable of good performances when a mathematical description is not available. The PI like controller presented is general and can be applied to any dc to dc power converte...