Sharif Digital Repository

The robust fuzzy multimodel control as a potential tool to control the complex systems is presented in this paper. The main idea in multimodel controllers is to identify the best model of system at any instant and apply the appropriate control input to it. Classical multimodel controller works based on switching and tuning, while fuzzy logic is used in construction of fuzzy multimodel controller. The basic control signal for each model is calculated using the sliding mode control and the final control input is inferred as the weighted average of the local control inputs. A new algorithm is proposed in order to use the fuzzy multimodel control for time variant linear systems. To show the... 

In this paper, the goal is to propose an optimal handoff algorithm for hybrid networks (HNs), which are constructed by interworking between wireless LANs (WLANs) and mobile networks. The proposed algorithm is an adaptive fuzzy logic based algorithm that can adapt itself with the dynamic conditions in HNs. It uses mobile terminal speed estimation and traffic in the WLAN as additional input parameters. This algorithm is designed to meet special requirements of HNs. The simulation results show that it has much better performance than conventional algorithms. ©2002 IEEE  

In this study, the effect of protection methods regarding the corrosion decrement of steel in concrete was simulated by artificial neural networks (ANNs) and fuzzy logic (FL) approaches. Hot dip galvanizing as a protective coating, Ferrogard 901 corrosion inhibitor, a pozzolanic component, such as fly ash (FA) and micro-silica (MS), and eventually rebar AISI-304 were employed in concrete. Reinforced concrete samples were held under impressed voltage of 30 V in 3.5 % NaCl electrolyte for 350 hours toward a stainless-steel auxiliary electrode. Corrosion currents have been modelled using feed forward back propagation ANNs and FL methods. The results demonstrate good consistency between... 

According to the world health organization, major depressive disorder (MDD) is considered as the fourth main cause of death and premature weakness in the whole world. Abnormality in the hormones and neurotransmitters level is the one of the main factors which may result in this disorder. In this article melatonin is chosen among these hormones, which is the most implicated to control sleep and depression. Because the measurement of melatonin is crucial important, the fuzzy logic approach as the mathematical method is utilized to making melatonin behavior model. In this paper, two effective factors on melatonin are modeled by fuzzy logic. This model is only a part of our project which is... 

A Real-Time Optimization (RTO) strategy incorporating the fuzzy sets theory is developed, where the problem constraints obtained from process considerations are treated in fuzzy environment. Furthermore, the objective function is penalized by a fuzzified form of the key process constraints. To enable using conventional optimization techniques, the resulting fuzzy optimization problem is then reformulated into a crisp programming problem. The crisp programming problem is solved using both Sequential Quadratic Programming (SQP) and Heuristic Random Optimization (HRO) techniques for comparison purposes. The proposed fuzzy RTO strategy is demonstrated via the Tennessee Eastman benchmark process,... 

In this paper, the fuzzy system has been used for fault detection and diagnosis of a yeast fermentation bioreactor based on measurements corrupted by noise. In one case, parameters of membership functions are selected in a conventional manner. In another case, using certainty factors between normal and faulty conditions the optimal values of these parameters have been obtained through the genetic algorithm. These two cases are compared based on their performances in fault diagnosis of a yeast fermentation bioreactor for three different conditions. The simulation results indicate that the fuzzy-genetic system is superior in multiple fault detection for the conditions where the minimum and... 

A univariate iterative method for the optimization of nonlinear trusses with fuzzy constraints is proposed. The method is based on the control of elemental strains rather than stresses and hence it is called the desirable strain design criteria method. The objective of the fuzzy optimization is to find a design so that the weight or volume of the truss as well as all of the constraints on the elemental strains and joint deflections are desirable and satisfactory according to the fuzzy designer expressions. Such expressions are made in the form of fuzzy membership functions. Two illustrative examples, a 3- and a 10-bar truss, are optimized by the proposed method, where it is shown that in... 

This paper focuses on the sliding mode control which incorporates a fuzzy tuning technique. In this scheme, first, a control input based on classical sliding mode control is designed. Then, for performance enhancement and chattering elimination, an additional fuzzy control term is used together with the control signal. Furthermore the Lyapunov stability method is used to prove the asymptotic convergence of control strategies. To illustrate the usefulness of the proposed approach, classical and fuzzy sliding mode control are both applied to a flexible transmission system. The results verify the validity of the proposed control scheme. © 2004 IEEE  

Controlling dynamic biped robots is a complex challenge. Almost all researches in this field assume that the internal structure and dynamics of the robot is known to the controller. But in real-world problems we don't have exact model of the robot or this model is very complicated and is not useful in real-time control. As a matter of fact, we use many devices without any knowledge about their internal structure or analytical models. Some researchers used learning algorithms to control bipeds, but their performance is not comparable to human's learning. Fuzzy controllers can control the bipeds with lower cost, but they need sufficient rules. In the previous works we proposed a linguistic... 

This paper first will describe @Home Mobile Robot and DC motors. In continuous, is designed a Direct current (DC) motor for special task due to specific speed diagram for considered robot. This robot wants to work in intermittent operation condition. Finally is done a speed control on a selected permanent magnet brushed DC motor using of Linear-Quadratic-Regulator (LQR), Linear-Quadratic-Gaussian (LQG) and Fuzzy logic controllers  

In this paper a fuzzy logic based controller for STATCOM is used to improve power system transient stability. As opposed to the modern control theory, fuzzy logic design is not based on the mathematical model of the process. The controller designed using fuzzy logic implements human reasoning that can be programmed into fuzzy logic language (membership functions, rules and the rule interpretation). The nonlinear fuzzy controller is proposed to supply a supplementary control signal to STATCOM to increase the critical clearing time and overcome the uncertainties existing in the power systems. Proposed method is implemented in a single machine infinite bus system and the results are compared... 

In this paper, designing of the LQR controller and observer with intelligent tools for the triple inverted pendulum is investigated. Intelligent tools are considered as GA and GA-PSO optimization algorithms and fuzzy logic to qualify achieving LQR gains. The pendulum is swung up from the vertical position to the unstable position. The rules for the controlled swing up are heuristically achieved such that each swing results are controlled. The inverted pendulum and cart system are modeled and constructed their equation based on energy method. Also, the performances of the proposed fuzzy logic controller, GA and GA-PSO tuning LQR gains are investigated and compared. Simulation results show... 

Many factors affect the yield loss in wheat harvesting with a grain combine harvester. Grain harvesting is a non-linear process, is of considerable complexity, and there is no mathematical model to describe the behavior of this complex system. In this paper, a fuzzy logic controller (FLC) incorporating human expert knowledge is designed for automatic adjustment and control of the harvester to achieve minimal grain losses especially at the position of straw walker and upper sieve. The FLC automatically adjusts cylinder speed, concave clearance, fan speed and forward speed of the combine based on the measured losses at straw walker and sieve sections. The designed FLC expert system consists... 

With the stricter limitations on both fuel consumption and air pollution, the advantages of a hybrid electric vehicle are becoming more evident than ever. In the present study, an energy management system for a hybrid electric vehicle is developed. Because the plant under consideration is nonlinear, multi-domain, time-varying, has multiple uncertainties and, in addition, the designed control strategy must be able to obey the driver's commands and achieve the par-internship for a new generation of vehicle regulations, the fuzzy logic approach is chosen. A feed-forward hybrid vehicle simulation model is used to demonstrate the validity and the convenience of the current approach and its...