The development of a novel soft computing approach to model the supervisor of manufacturing systems is described, it is named Fuzzy Cognitive Maps (FCMs) and it is used to model the behaviour of complex systems. Fuzzy cognitive maps combine characteristics of both fuzzy logic and neural networks. The description and the construction of fuzzy cognitive maps are examined, a new methodology for de...

This paper investigates a hybrid methodology that combines fuzzy logic and neural networks, Fuzzy Cognitive Map (FCM), for modeling and controlling Supervisory Control Systems. A mathematical description of Fuzzy Cognitive Maps (FCM) will be presented and new construction methods will be extensively examined. A Fuzzy Cognitive Map will be developed to model and control a process example and the...

This paper investigates a hybrid methodology that combines fuzzy logic and neural networks, Fuzzy Cognitive Map (FCM), for modeling and controlling Supervisory Control Systems. A mathematical description of Fuzzy Cognitive Maps (FCM) will be presented and new construction methods will be extensively examined. A Fuzzy Cognitive Map will be developed to model and control a process example and the...

PID controllers are the well known and most widely used controllers in the industries. The reason behind this is because of its simple structure and reliability. Nonetheless when the plant to be controlled is highly non linear or is subjected to disturbances or we have less knowledge about it, under these conditions poor performance is obtained when we are using fixed parameter PID as controlle...

The power system dynamic instability is occurred by loosing balance relation between electrical generation and a varying load demand that justifies the necessity of using Power System Stabilizer (PSS). Moreover, the PSS must have the capability of producing appropriate stabilizing signals with limited practical amplitude and it should be robust against a wide range of operating conditions and d...

AbstractThis paper presents an intelligent navigation method for navigation of a mobile vehicle in unknown environments. The proposed navigator consists of three modules: Obstacle Avoidor, Environment Evaluator and Navigation Supervisor. The Obstacle Avoidor is a fuzzy controller whose rule base is learnt through reinforcement learning. A new and powerful training method is proposed to constru...

In this paper a neurofuzzy control strategy, composed by a neural observer and a fuzzy supervisor, for an anaerobic wastewater treatment process is proposed. The neural observer is based on a recurrent high order neural network (RHONN) which is trained by an extended Kalman filter. The main objective of the observer is to estimate methanogenic biomass, which is employed by a fuzzy supervisor. T...

this paper undertakes the synthesis of a logic-based switching h2/h∞ state-feedback controller for continuous-time lti singular perturbation systems. our solution achieves a minimum bound on the h2 performance level, while also satisfying the h∞ performance requirements. the proposed hybrid control scheme is based on a fuzzy supervisor managing the combination of two controllers. a convex lmi-b...

A hybrid control system is proposed for regulating an unknown nonlinear plant. The interface between the continuous-state plant and the discrete-event supervisor is designed using a fuzzy logic approach. The fuzzy logic interface partitions the continuous-state space into a finite number of regions. In each region, the original unknown nonlinear plant is approximated by a fuzzy logic-based line...

Changes in operating conditions can alter performances of nonlinear processes controlled with a fixed PID algorithm. One way of preventing degradation is to develop a supervised control system. In this paper we present some results about fuzzy gain scheduling of a double PID controller for stabilization of an inverted pendulum on a cart. First, on the basis of the responses obtained with an uns...