This paper describes a self-learning navigation method which utilizes fuzzy logic and reinforcement learning for navigation of a mobile vehicle in uncertain environments. The proposed navigator consists of three modules: Obstacle Avoidance, Move to Goal and Fuzzy Behavior Supervisor. The fuzzy rules of the on-line obstacle avoidance are learnt through reinforcement learning. A new and powerful ...

This work presents a new method for controlling fuel and air fed boiler of thermal power plant using Fuzzy logic. The control strategy is based on supervisor level using Fuzzy logic that is required to determine automatically the optimal process set points of regulations level. Besides, this paper describes thermal power plant simulator developed by Matlab-Simulink. Key-Words: Thermal power pla...

This paper investigates an Adaptive Fuzzy GainsScheduling Integral Sliding Mode Controller (AFGS-ISMC) design approach to deal with the attitude and altitude stabilization problem of an Unmanned Aerial Vehicles (UAV) precisely of a quadrotor. The Integral Sliding Mode Control (ISMC) seems to be an adequate control tool to remedy this problem. The selection of the controller parameters is done m...

The optimization of a Fuzzy Cognitive Map model for the supervision and monitoring of the radiotherapy process is proposed. This is performed through the minimization of the corresponding objective function by using the Particle Swarm Optimization and the Differential Evolution algorithms. The proposed approach determines the cause–effect relationships among the concepts of the supervisor–Fuzzy...

The goal of this paper is to propose an alternative to classical control methods of a fed-batch fermentation. Fuzzy modeling and control theory is used for that purpose. The fuzzy supervisor based on human experience and experimental data, is designed to compute the set values for a PI controller which controls the feeding dilute flow to the fermentator. The results are compared with those obta...

A novel intelligent multiple-controller framework incorporating a fuzzy-logic based switching supervisor is presented for adaptive control of non-linear systems . The proposed methodology provides the designer with an automated choice of using either: a conventional Proportional-Integral-Derivative (PID) controller, a PID structure based pole (only) placement controller, or a PID structure base...

In this article, a novel Negotiation-to-Coordinate (N2C) mechanism is proposed to explore the interactive nature of the buyer-supplier relationships for dynamic environments. The proposed N2C mechanism uses prioritized fuzzy constraints to represent trade-offs among the different probable values associated with the negotiation issues and to signify how agents should make concessions. Supervisor...

<p>This paper focuses on a photovoltaic system for pumping water. The control strategy this water is based Takagi-Sugeno type fuzzy supervisors and sliding mode controller. first generates the maximum power point current under varying climatic condition whereas second allows tracking reference signal produced by supervisor. includes generator (PVG) followed DC-DC Converter, DC bus, an AC/...

This paper gives a description of an adaptative on-line diagnosis system for the detection of slow varying changes in dynamical systems. This fault detection system is based on both a learning and a supervisor module. The learning module acts as an adaptatif fuzzy classiier i.e. its parameters are updated on-line. The supervisor module controls the learning periods of the classiier, it makes th...