Sharif Digital Repository

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... 

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 design and evaluation of an adaptive critic- based neurofuzzy controller for the stabilizing periodic orbits of chaotic systems has been presented in detail. The main superiority of the proposed controller over previous analogous fuzzy logic controller design approaches, e.g., genetic fuzzy logic controller, is its online tuning characteristic and remarkable reduced amount of computations used for parameter adaptation, which makes it desirable for real time applications. Considering the simplicity of this controller and its independence from the system model, this control method has the advantage of online learning and control, and can be applied to a large variety of systems.... 

In this paper design and evaluation of an adaptive critic- based neurofuzzy controller for the stabilizing periodic orbits of chaotic systems has been presented in detail. The main superiority of the proposed controller over previous analogous fuzzy logic controller design approaches, e.g., genetic fuzzy logic controller, is its online tuning characteristic and remarkable reduced amount of computations used for parameter adaptation, which makes it desirable for real time applications. Considering the simplicity of this controller and its independence from the system model, this control method has the advantage of online learning and control, and can be applied to a large variety of systems.... 

Biological systems are highly nonlinear, and there is a significant amount of variability from one patient to another. A controller for drug infusion has to be able to achieve good performance for most of the potential patient population. These controllers are designed for the general population, as no knowledge is available before hand for each particular patient. This necessitates perforce an algorithm that will be able to compensate for the differences between individuals and external factors. Of the possibilities, fuzzy logic direct model reference adaptive control (DMRAC) is the choice for Insulin infusion control for diabetes type I as results presented herein. Safety and robustness... 

In this paper design and evaluation of an adaptive critic-based neurofuzzy controller for the stabilizing periodic orbits of chaotic systems has been presented in detail. The main superiority of the proposed controller over previous analogous fuzzy logic controller design approaches, e.g., genetic fuzzy logic controller, is its online tuning characteristic and remarkable reduced amount of computations used for parameter adaptation, which makes it desirable for real time applications. Considering the simplicity of this controller and its independence from the system model, this control method has the advantage of online learning and control, and can be applied to a large variety of systems.... 

This paper presents an active suspension system for passenger cars, using adaptive critic-based neurofuzzy controller. The model is described by a system with seven degrees of freedom. The car is subjected to excitation from a rode surface and wheel unbalance. The main superiority of the proposed controller over previous analogous fuzzy logic controller designed approaches, e.g., genetic fuzzy logic controller, is its online tuning characteristic and remarkable reduced amount of computations used for parameter adaptation, which makes it desirable for real time applications. Considering the simplicity of this controller and its independence from the system model, this control method has the... 

Renewable energy (RE) as a new player in the generation sector of power systems imposes new challenges to the system operators. The intermittent nature of REs for systems where are autonomous calls for new operational and planning strategies to reach more efficient power management. An autonomous hybrid green power system (HGPS) should be able to meet the load while keeping the cost of the HGPS as low as possible. Many studies have presented different un-optimal and optimal operational strategies, a few of which were optimally sized. In this regard, this paper develops a new thorough framework for designing and optimizing an autonomous HGPS. To reach this goal, the proposed model (a)... 

Many actions have been taken by researchers to design an appropriate controller for a quadruped robot. These efforts can be divided into two main categories: analytical and intelligent methods. The analytical method is based on the motion equations of the robot which are mostly complicated. These complication leads to difficulty in implementation. In contrast, there exists intelligent method which is based on the learning algorithms. Despite lots of improvements in the controlling of the quadruped robots, their ability of walking is still far less from the four legged animals' capability. Many researchers believe that four legged animals owe this priority to the learning attribute. Therefore... 

In this paper a fuzzy controller is developed for automatic landing of fixed wing Unmanned Aerial Vehicles (UAVs). It is assumed that the vehicle has a built in vision system which provides the runway relative position and orientation to be used in the designed tracking system. The stability of the controller was analyzed through vector field diagrams, and the system performance is tested through a complete 6DOF computer simulation. The results show a satisfactory performance of the controller all through the automatic landing phase. ©2009 IEEE  

Differential Evolution (DE) and Genetic Algorithms (GA) are population based search algorithms that come under the category of evolutionary optimization techniques. In the present study, these evolutionary methods have been utilized to conduct the optimum design of a fuzzy controller for mobile robot trajectory tracking. Comparison between their performances has also been conducted. In this paper, we will present a fuzzy controller to the problem of mobile robot path tracking for a CEDRA rescue robot. After designing the fuzzy tracking controller, the membership functions will be optimized by evolutionary algorithms in order to obtain more acceptable results  

To have a complete model of a thunniform Fish-Robot, models of both body and tail are required. The dynamic model of the body is developed according to the parameters of a thunniform Fish-Robot built in MIT University, while, as the main part of this paper, the dynamic model of the tail is developed using fuzzy logic. Using experimental data and table look-up scheme, a fuzzy black box is introduced that gives the value of thrust force generated for any value of the Fish-Robot's input parameters: frequency of tail oscillation, amplitude of tail oscillation and speed of the Fish-Robot. In the second part, a trajectory fuzzy controller is designed for the Fish-Robot. The output of trajectory... 

Differential Evolution (DE) and Genetic Algorithms (GA) are population based search algorithms that come under the category of evolutionary optimization techniques. In the present study, these evolutionary methods have been utilized to conduct the optimum design of a fuzzy controller for mobile robot trajectory tracking. Comparison between their performances has also been conducted. In this paper, we will present a fuzzy controller to the problem of mobile robot path tracking for a CEDRA rescue robot. After designing the fuzzy tracking controller, the membership functions will be optimized by evolutionary algorithms in order to obtain more acceptable results  

To have a complete model of a thunniform Fish-Robot, models of both body and tail are required. The dynamic model of the body is developed according to the parameters of a thunniform Fish-Robot built in MIT University, while, as the main part of this paper, the dynamic model of the tail is developed using fuzzy logic. Using experimental data and table look-up scheme, a fuzzy black box is introduced that gives the value of thrust force generated for any value of the Fish-Robot's input parameters: frequency of tail oscillation, amplitude of tail oscillation and speed of the Fish-Robot. In the second part, a trajectory fuzzy controller is designed for the Fish-Robot. The output of trajectory... 

This paper addresses the effect of different optimization criteria for the control purpose of vehicle suspension. In the present study, active vibration control system for a 5 degree-of-freedom (DoF) pitch-plane suspension model with bounce and pitch motions is investigated. In the proposed vehicle model, the impact of the wheel-axle-brake assemblies' masses is also considered. The developed model is controlled using a fuzzy logic controller (FLC) to minimize the vibration of the driver's seat. The controller is designed to control the applied force to the seat. Furthermore, in order to determine the optimal value of fuzzy system parameters, genetic algorithm (GA) optimization search is used... 

This paper will first describe the Linear Quadratic Regulator (LQR) and Fuzzy logic controller when the Proportional-Integral-Derivative (PID) controllers are inactive for procedures that have large delay time (LDT) in transfer stage. Therefore in those states, LQR and Fuzzy controllers perform better than the PID controllers. The constrained LQR is optimal and stabilizing. The solution algorithm is guaranteed to terminate in finite time with a computational cost that has a reasonable upper bound compared to the minimal cost for computing the optimal solution. The system determines the amount of fuel required from a fuzzy algorithm to arrive at the desired temperature. The parameters of the...