This paper presents fuzzy and conventional performance of model reference adaptive control(MRAC) to control a DC drive. The aims of this work are achieving better match of motor speed with reference speed, decrease of noises under load changes and disturbances, and increase of system stability. The operation of nonadaptive control and the model reference of fuzzy and conventional adaptive contr...

Fuzzy controllers are represented by if-then rules and thus can provide a user friendly and understandable knowledge representation. Evolutionary algorithms have been widely used for optimal design of fuzzy controllers. In this paper, we first present the state-of-art adaptive fuzzy control design using evolutionary algorithms and then attempt to enhance the performance of the simple genetic se...

This paper proposes a fuzzy approximation-based adaptive sliding-mode controller for uncertain nonlinear perturbed underactuated systems. The fuzzy logic system is used for approximating the unknown nonlinear functions. For estimating the parameters of the fuzzy systems and some unknown bounds, a set of adaptation laws are appropriately designed. The boundedness of all signals of the closed-loo...

We discuss several fuzzy models to approximate friction and other disturbances in mechatronic systems, especially linear and rotarional electrical drives. Some methods of experimental identification of disturbance forces are presented. We consider several fuzzy models to compromise between model accuracy and complexity. Fuzzy model is used in an adaptive control loop. Several adaptive control a...

An adaptive fuzzy PID controller with gain scheduling is proposed in this paper. The structure of the proposed gain scheduled fuzzy PID (GS FPID) controller consists of both fuzzy PI-like controller and fuzzy PD-like controller. Both of fuzzy PIlike and PD-like controllers are weighted through adaptive gain scheduling, which are also determined by fuzzy logic inference. A modified genetic algor...

The paper presents a comparison of various soft computing techniques used for filtering and enhancing speech signals. The three major techniques that fall under soft computing are neural networks, fuzzy systems and genetic algorithms. Other hybrid techniques such as neuro-fuzzy systems are also available. In general, soft computing techniques have been experimentally observed to give far superi...

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...

This paper, deals with an indirect adaptive fuzzy control of discrete-time MIMO nonlinear systems with parametric variations. The synthesis of the state feedback control law is based on the T-S fuzzy models developed by a local description of the considered system. In the first step, gradient method is used to adjust model parameters locally estimated by the fuzzy model. The state feedback cont...

In this paper, a novel adaptive fuzzy backstepping output feedback control scheme is proposed for a class of single-input single-output (SISO) uncertain nonlinear systems without measurements of states. Fuzzy logic systems (FLS) are used to tackle unknown nonlinear functions, and the adaptive fuzzy output feedback controller is constructed by combining fuzzy filters observer design and the dyna...