Sharif Digital Repository

Using the combination of fuzzy clustering estimation and sliding mode control, a technique for controlling the magnetic levitation (ML) systems is introduced. This technique is applied to an experimental setup of an ML system for investigating the method derived. The system considered, is a symmetric rotor supported by a cantilever load cell beam and excited by only one electromagnet of a 4-pole magnetic bearing setup. After demonstrating the experimental setup instruction and the specifications of its parts, the clustering, and the sliding mode control methods are explained briefly, then the quality of implementing the techniques to the setup is described step by step. Finally, the results... 

A practical design method is presented which used the fuzzy logic advantages in adaptation of sliding mode control. The combined Fuzzy Adaptive Sliding Control (FASC) is designed in such a way to enhance satisfactory sliding performance and robustness with good level of chattering alleviation. The design approach is valid for a class of nonlinear uncertain MIMO systems. This control algorithm does not require the system model. A supervisory term is appended to the controller to assure the stability of fuzzy sliding mode control through Lyapunov theory. The design approach has been applied to a 2DOF twin propeler system with large uncertainty. Simulation results verified effectiveness of... 

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  

In this paper optimization of energy consumption in an electric vehicle is presented. The main idea of this optimization is based on selecting the best gear level in driving the vehicle. Two algorithms for optimization are introduced which are based on fuzzy rules and fuzzy controllers. In first algorithm, fuzzy controller simulates energy consumption in different gear levels, and chooses the optimum gear level. While in second method, fuzzy controller detects the optimum gear level by measuring the vehicle's average speed and acceleration. To investigate the performance of these controllers, a model of TOSAN vehicle is developed and the controllers outputs are checked in simulation of TOSAN... 

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... 

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 an approach based on system identification is used for fault detection in a nuclear reactor. A continuous-time Extended Kalman Filter (EKF) is presented, which allows the parameters of the nonlinear system to be estimated. Also a fault tolerant control system is designed for the nuclear reactor during power changes operation. The proposed controller is an adaptive critic-based neuro-fuzzy controller. Performance of the controller in terms of transient response and robustness against failures is very good and considerable  

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 new highly convergent, efficient, and fast response control technique entitled as fuzzy-Padé control method is introduced. It provides a simple methodology to exploit the heuristic knowledge in controlling a system. Fuzzy-Padé controllers originate from a unification of heuristic knowledge expressed as the rule base, and Padé approximants. In this method, fuzzy singleton rules are used to generate the rule base. Accordingly, unknown parameters in the Padé approximant are determined using these rules. The fuzzy-Padé controllers possess certain advantages over fuzzy controllers, and they can be applied in situations where fuzzy controllers previously failed. To demonstrate the... 

Fuzzy Control of rowing exercise using Functional Electrical Stimulation (FES) concerns ankle, knee and hip joints. Muscular Modeling for each joint may contain two groups of muscles, namely extension and flexion. In the proposed method, joint controllers provide electrical stimulation pulses to the appropriate muscle group based on the trajectory error and according to a prescribed pattern designed for rowing exercise. Results indicate that the simulated Fuzzy control of desired angles closely match the experimental values for prescribed joints. Moreover, the robustness of the controller in presence of external disturbance is examined and the results show that the tracking of each joint... 

In this paper, a novel decentralized adaptive control scheme for multiagent formation control is proposed based on an integration of artificial potential functions with robust control techniques. Fully actuated mobile agents with partially unknown models are considered, where an adaptive fuzzy logic system is used to approximate the unknown system dynamics. The robust performance criterion is used to attenuate the adaptive fuzzy approximation error and external disturbances to a prescribed level. The advantages of the proposed controller can be listed as robustness to input nonlinearity, external disturbances, and model uncertainties, and applicability on a large diversity of autonomous... 

In this paper, an optimized control strategy is proposed for a split parallel hydraulic hybrid truck. The model of the vehicle was simulated in Simulink. According to a global optimization technique, a fuzzy control strategy is developed for the vehicle. This strategy shows flexibility for different drive cycles and a desirable fuel consumption reduction, especially for a low speed drive cycle, which is extracted according to an urban utility vehicle mission  

Magnetorheological (MR) damper is a prominent semi-active control device to vibrate mitigation of structures. Due to the inherent non-linear nature of MR damper, an intelligent non-linear neuro-fuzzy control strategy is designed to control wave-induced vibration of an offshore steel jacket platform equipped with MR dampers. In the proposed control system, a dynamic-feedback neural network is adapted to model non-linear dynamic system, and the fuzzy logic controller is used to determine the control forces of MR dampers. By use of two feedforward neural networks required voltages and actual MR damper forces are obtained, in which the first neural network and the second one acts as the inverse... 

A novel intelligent semi-active control system for an eleven degrees of freedom passenger car's suspension system using magnetorheological (MR) damper with neuro-fuzzy (NF) control strategy to enhance desired suspension performance is proposed. In comparison with earlier studies, an improvement in problem modeling is made. The proposed method consists of two parts: a fuzzy control strategy to establish an efficient controller to improve ride comfort and road handling (RCH) and an inverse mapping model to estimate the force needed for a semi-active damper. The fuzzy logic rules are extracted based on Sugeno inference engine. The inverse mapping model is based on an artificial neural network... 

Drug administration using infusion pumps can find application in treating patients with arrhythmias. These pumps can obviate the need to use drugs several times a day and automatically adapt the dosage to patient situation. Considering the importance of administration of right dosage, a perfect-controlled pump is needed to approach this goal. This paper focuses on controlling Atrial fibrillation (AF) arrhythmia. The abnormal heart rhythm that affects RR interval sequence and there have been some attempts to model these effects. One of these models is proposed by Cohen and colleges. Searching through the variables of this model, selecting the potential control variable (the one that its... 

Purpose - The purpose of this paper is to present a novel approach in terrain following (TF) flight using fuzzy logic. The fuzzy controller as presented in this work decides where and how the aircraft needs to change its altitude. The fast decision-making nature of this method promises real-time applications even for tough terrains in terms of shape and peculiarities. The method could always assist to design trajectories in an off-line manner. Design/methodology/approach - To achieve the aforementioned goal, the method effectively incorporates the dynamics of the aircraft. Basically, the mathematical method employs special relationships among existing slope of the terrain and its derivative... 

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  

This paper addresses design of an observer-based adaptive fuzzy controller for a class of single-input-single-output (SISO) nonlinear systems with unknown dynamics subject to input nonlinearity and unknown direction. The proposed controller is singularity free. A high-gain observer is designed to estimate the unmeasured states, and the Lipschitz condition for proving boundedness of the estimated states is relaxed. The Nussbaum function is used to handle the unknown virtual control directions and the backstepping technique has been applied for controller design. It is proved that all closed loop signals are semi-globally uniformly ultimately bounded (SGUUB) and the output tracking error...