Sharif Digital Repository

In this paper, a new approach for behavior based architecture in mobile robot navigation in unknown environments is presented. In this approach, the general actions of a mobile robot are classified into three thoroughly separated tasks. Then, an individual fuzzy controller is designed and implemented for each task (behavior). Finally, a behavior selector is designed to switch between the robot tasks (behavior patterns) and manage all separated fuzzy controllers to navigate a mobile robot in a fully unknown environment. Another case considered in this paper is to test and examine the proposed algorithm in an environment including the static and dynamic (moving) obstacles. The most difficult... 

This paper is concerned with the design and simulation of an intelligent stop and go cruise control system in an automated vehicle. In this paper Active learning method is used to extract driver's behavior and to derive control rules for cruise control system. First, there is a brief introduction to ALM (Active Learning Method) and its specifications. Then a one-line space for driving is assumed and its parameters are extracted. By using IDS, the processing engine of ALM, effective parameters in controller are derived. A simulation program is written to produce learning samples and also to evaluate controller's parameters. To apply controller's output, appropriate acceleration of the... 

Welding is an important manufacturing process that can be automated and optimized. In this paper we discuss the Gas Metal Arc Welding (GMAW) control and modeling problem. For modeling the process recently developed highly nonlinear fifth order mathematical model is used, for controlling the GMAW process we use a new Mixed Fuzzy Control (MFC) structure. In this work first a Traditional Fuzzy Controller (TFC) is designed from the viewpoint of a Single-Input Single-Output (SISO) system for controlling each state of GMAW process. Then, an appropriate coupling fuzzy controller is also designed according to the characteristics of gas metal arc welding process and incorporated into a TFC. We then... 

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... 

Human bodies use the electrical currents to make the muscles move. Disconnection of the electrical signals between the brain and the muscles as a result of spinal cord injuries, causes paralysis below the level of injury. Functional electrical stimulation (FES) is used to stimulate the peripheral nerves of the disabled limbs. The level of these electrical signals should be selected so that the desired tasks are done successfully. Applying the appropriate controller which can result a human like behaviour and the accomplishment of the desired tasks has become a significant research area. In this paper, the multi-input multi-output (MIMO) musculoskeletal model of human arm with six muscles is... 

This paper discusses a novel and detailed approach for dynamic modeling and control design of a coupled hydraulic dynamometer/turbine-engine system. This study presents a comprehensive model to reveal the coupling effects and an adaptive multiobjective controller to ensure a safe and reliable operation. A fuzzy-based strategy is employed to dynamically adjust the controller gains to keep the state variables and power loading within the desirable operational limits. This approach uses the dynamometer inlet, outlet, and trim valves as well as the turbine fuel flow rate and bleed valve in order to control the system performance during the engine testing process. The proposed fuzzy control... 

The anesthesia community has recently witnessed numerous advances in monitoring of the anesthetic state. This development has spurred a renewed interest in the automation of the clinical anesthesia. The absence of a precise model in biomedical field has motivated the authors to propose a novel approach capable of handling the uncertainties present in the model and moreover, to design a new approach which is subjective and can be adopted to patient specific requirements. In this regard a study has been conducted in this paper, in order to fit the intelligence of fuzzy controllers based on reinforcement learning in this clinical application. This study suggests that the chosen approach fits... 

This paper presents a Mixed Fuzzy-GA Controller (MFGAC) for trajectory tracking of an industrial Selective Compliance Assembly Robot Arm (SCARA), which is one of the most employed manipulators in industrial environments. In this robot nonlinear effects due to centrifugal, coriolis and internal forces are more important than friction and gravity forces, unlike most industrial robots. The control procedure of MFGAC is consisting of a mixed fuzzy controller which is optimized by genetic algorithm. In this work we first design a Traditional Fuzzy Controller (TFC) from the viewpoint of a Single-Input Single-Output (SISO) system for controlling each degree of freedom of the robot. Then, an... 

This paper deals with growth control of cancer cells population using type-1 and interval type-2 fuzzy logic. A type-1 fuzzy controller is designed in order to reduce the population of cancer cells, adjust the drug dosage in a manner that allows normal cells re-grow in treatment period and maintain the maximum drug delivery rate and plasma concentration of drug in an appropriate range. Two different approaches are studied. One deals with reducing the number of cancer cells without any concern about the rate of decreasing, and the other takes the rate of malignant cells damage into consideration. Due to the fact that uncertainty is an inherent part of real systems and affects controller... 

Recently, fuzzy variable linear programming problems have attracted some interests. We introduce the dual of fuzzy variable linear programming problem, and then deduce some important duality results. COPYRIGHT © ENFORMATIKA  

In the last decade, the intelligent control community has paid great attention to the topic of intelligent control systems for nuclear plants (core, steam generator). Papers mostly used approximate and simple mathematical SISO (single-input-single-output) model of nuclear plants for testing and/or tuning of the control systems. They also tried to generalize theses models to a real MIMO (multi-input-multi-output) plant, while nuclear plants are typically of complex nonlinear and multivariable nature with high interactions between their state variables and therefore, many of these proposed intelligent control systems are not appropriate for real cases. In this paper, we designed an on-line... 

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... 

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  

In this paper a fuzzy control strategy of autonomous multiagent systems is presented. The main purpose is to obtain an improvement on the results of designed sliding mode controllers in previous articles using supervisory fuzzy controller. Similarly, a quasi-static swarm model in ndimensional space is introduced wherein the inter-individual interactions are based on artificial potential functions; and the motions of members are in direction with the negative gradient of the combined potentials which are the result of a balance between inter-individual interactions and the simultaneous interactions of the swarm members with their environment. Then a general model for vehicle dynamics of each...