Sharif Digital Repository

In this thesis, in order to improve the performance of the mobile robot navigation, a Fuzzy approach is used for making a safe path in the cluttered environment with hurdles in the work space of the robot. To this end, based on data collected from instantaneous location of the robot and location of the robot, heuristic rules are extracted. Also, in order to obtain optimal data fusion of the sensors, Kalman filter is used to localize the robot. In this regards, by using the kinematics of the robot and supposing the white noise in the process and measurements, the position and orientation of the mobile robot are estimated in a real-time and adaptive manner  

Due to the inherent non-linear nature of the MR damper, an intelligent non-linear neuro-fuzzy control strategy is designed for control of wave-induced vibration of an offshore steel jacket platform equipped with MR dampers. In the proposed control system, a dynamic-feedback neural network is employed to model non-linear dynamic system and the fuzzy logic controller is used to determine the control forces of MR dampers. Required voltages and actual forces of MR dampers are obtained by use of two feedforward neural networks, in which the first neural network and second one act as the inverse and forward dynamics model of the MR dampers, respectively. The most important characteristic of the... 

This thesis is presented to introduce a semi-active control of the suspension systems. The currently available semi-active damper technologies can be divided into two main groups. The first uses controllable electromagnetic valves and the second uses Magnetorheological (MR) fluid to control the damping characteristics of the system. A mass-spring model with eleven degrees of freedom, considering constant velocity for the car, is developed to model the suspension system. A semi-active vibration control system is presented to reduce the amplitude of automotive vibrations caused by the alteration of the road profile. The gravel road profile with Gaussian white noise as the road irregularity... 

The present study discusses the problem of enabling a PUMA 560 electrical robot manipulator to interact with the environment using impedance control concept. The impedance control strategy maintains a pre-specified desired second order dynamic relation between the end-effector position and force and enables a stable transmission between unconstrained and constrained motion. In this study Position-Based Impedance Control (PBIC) is used which is more suitable for industrial manipulators. PBIC requires a position controller with high accuracy. Therefore, a nonlinear PID controller is used in the position loop which is capable of both tracking and regulating of the input signals and shows better... 

The main concept of this thesis is to simulate, develop, and analyze the performance of force control method by applying to a Unimate MK-II hydraulic manipulator. In this investigation, simulation studies are based on the concept of impedance control technique. Position-based formulation of impedance control is employed. First in this research, a PID controller is employed and is shown to be capable of performing position control task precisely despite the fact that inertia, joint stiction, valve deadband and other nonlinearities are presented. Although trajectory tracking is performed well after several investigations, we have concluded that the impedance control cannot perform a desirable... 

Hexapod Robots give us the ability to study walking robots without facing problems such as stability. It has a great deal of exibility in movement even if some legs become malfunctioned or face some diculties. Control of legged robots compared to other kind of locomotions is di- cult and requires fairly heavy on-line computations to be done in real time. Therefore, a machine-learning solution may be more convenient in such prob- lems. One method of machine-learning which is used for legged robots with outstanding potential is Reinforcement Learning (RL). RL is a promising ap- proach for achieving complex robots control in dynamic environments. RL techniques are interesting subjects in... 

The huge capability of high resolution satellite imageries (HRSI), that includes spatial, spectral, temporal and radiometric resolutions as well as stereoscopic vision introduces them as a powerful new source for the Photogrammetric,Remote Sensing and GIS communities. High resolution data increases the need for higher accuracy of data modeling.The satellite orbit, position, attitude angles and interior orientation parameters have to be adjusted in the geometrical model to achieve optimal accuracy with the use of a minimum number of Ground Control Points (GCPs). In order to obtain high resolution and definition imaging for many applications including surveillance, target tracking, and... 

Reflective telescopes are devices which commonly use two mirrors, to gather and reflect light rays. In these types of telescopes, the main responsibility of the secondary mirror is to lead the reflected light from primary to detection place. The purpose of this project is to adjust the secondary mirror’s position to reduce the optical errors. So, we are going to study the M2 unit of the telescope. The M2 unit consists of a Hexapod made with six linear actuators in the conventional 3-3 arrangement, and its function is the accurate positioning of the secondary mirror. The main performance required for the M2 unit is the active mirror position adjustment in 5 axes to compensate the existing... 

Recent investigations on organs-on-chip devices have broadened our insight into the functions of the organs and their responses to pharmaceuticals. Studies on improving the efficiency of these chips are on going. The development of chips for growing various organs and possibly their possible interconnection are other hot topics in this field. This research is an attempt to simulate a Lung-on-a-Chip (LOC) device using Ansys Fluent software. Currently a new experimental technique for setting up a lung-on-a-chip device has been made public (Zamprogno et.al.ˏ̎ Second-generation lung-on-a-Chip with an array of stretchable alveoli made with a biological memvrane ̎ ˏComm. Biologyˏ2021ˏ4:168.). This... 

Cryptocurrencies are not only regarded as a trustworthy method of financial transaction validated by a decentralized cryptographic system as opposed to a centralized authority, but also as one of the most popular and lucrative forms of trade and investing. Predicting the price of a cryptocurrency is a challenging topic in time-series research. Its intricacy is due to the volatility and large swings of cryptocurrencies' price. The emergence of brand-new cryptocurrencies, which might present a profitable trading opportunity but lack sufficient historical data for technical analysis, prompted us to develop a trading strategy that could be applied universally. The forecast of the next timestep's... 

In this thesis, the Artificial Neural Networks (ANN) will be used in Automatic Speech Recognition (ASR) instead of Hidden Markov Models (HMM). Hidden Markov Model is one of the most dominant Bayesian network technologies and is the most successful model in current ASR systems. However, excessive training time is a major issue in speech recognition based on Hidden Markov Model (HMM). This thesis presents an Artificial Neural Network language model for human speech by mapping the spectral features of speech namely the formants, cepstrum (Mel-Frequency Cepstral Coefficients (MFCCs)) and Power Spectral Density (PSD) as features of samples of specific words into a discrete vector space. The... 

After the rise of the automotive industry, aluminum wheels have superseded steel counterparts due to their numerous advantages. Foremost among these benefits is their reduced weight, leading to fuel savings and diminished environmental impact. Moreover, aluminum wheels offer enhanced aesthetics and greater strength in comparison to steel alternatives. This thesis focuses on the geometrical optimization of an aluminum wheel model conforming to the standards set by Iran's Department of Standards, aiming to achieve a higher strength-to-weight ratio. While prior research works have mainly focused on weight reduction while maintaining strength within approved standards, this thesis aims at the... 

Herein, an introduction to optimization, aiming to help knowledge development in design optimization techniques is given. Besides, a new method of using the theory of topology optimization to optimize a microgripper system, with a piezoelectric ceramic driver (PZT) microactuator is presented as well. An optimization method is also presented to generate better control conditions. In this study a micro object gripper of 9200 µm length, 8100 µm width, and 500 µm thickness is optimized, and performances improvement is analyzed. This thesis is to investigate best practice and give advice on how to understand the process of topology optimization and how to setup an optimization run. At first, an... 

Control of line of sight (LOS) orientation is a fundamental prerequisite for virtually all dynamic applications in which an optical sensor is used to obtain images. In this research, a 3 DOF parallel mechanism is utilized to build a stable platform for high precision satellite photography. The platform may be designed based on the Stewart platform concept. The stability is obtained by controlling the roll, pitch and yaw of the mechanism. To apply linear control techniques and to use roll-pitch and yaw rates and also their absolute values, an active stable platform is designed. Line Of Sight (LOS) is a position vector from origin of a topocentric-horizontal system to the satellite of... 

Energy management in vehicles is ann important issue, because it can significantly influence the performance of the vehicles and component sizing., Although the bbatteries have been widely used in electric vehicles (EVs), However the large current impact of battery cycle life is still a difficult problem that remains to be resolved and because of that, Hybrid Electric Vehicles (HEVs) areis the way that allows to to achievinge the advantages of both engines.Hybrid cars uses both an electric motor and internal combustion engine (ICE) used together, so, itwhich can benefit from the advantages of both engine types. ImprovImprovement ofing energy management in (HEVs) can providedeliver important... 

Nowadays, industrial companies deal with a wide range of serious problems in the field of power transmission maintenance and also fault detection. A large amount of money and time is spent on these issues in order to solve them; consequently, there is an essential need for this subject. In this thesis, in order to tackle those major issues which were referred above, an artificial neural network is trained with only one hidden layer. Also, a suitable database for training an efficient neural network is needed. Thus, a one-stage gearbox system with appropriate degrees of freedom is used to set up referred database. In this system, a crack is imposed to a tooth of spur gear with different sizes... 

In this thesis, kinematic, dynamic modeling and simulation, and control of SQ15-06N industrial robot have been presented. This robot is mostly used in the painting industry. Studying the robot requires familiarity with the robot programming and the hardware used in the robot. In this research, robot characteristics such as repeatability, load carrying capacity and accessibility have been investigated. The principles of industrial robot programming and robot programming language have been studied. The use of simulation software is common due to cost savings, reduced time, no need for robots and controllers, and the ability to test programs in a virtual environment. For this purpose, the... 

This thesis describes different neural networks models and an approximation based neural network controller for autonomous underwater vehicles (AUVs). The online multilayer perceptron neural networks (OMLPNN) have been designed to perform modeling of AUVs of which the dynamics are highly nonlinear and time varying. The online recurrent multilayer perceptron neural networks (ORMLPNN) have been additionally designed to generate a memory to pervious states and increase the performance of the modeling. The designed OMLPNN and ORMLPNN with the use of backpropagation learning algorithm have advantages and robustness to model the highly nonlinear functions. The proposed neural networks architecture... 

In the recent years, increasing concerns about the environmental issues necessitatecientists and industrial people to introduce clean and zero emissions vehicles to the global market. Relying on this acute demand,Hybrid Electric Vehicles (HEVs) are knownas one potential solution to lessen the negative effects of transportation industry on ecological systems.HEVs combine an Internal Combustion Engine (ICE) with an Electric Motor/Generator (EMG) and an Energy Storage System (ESS) to produce a fuel efficient and low or zero pollutant powertrain. Increasing the number of components in the powertrain requires a sophisticated strategy to control all drive-line components suitably. Surely, the best... 

Advanced Driver Assistance System (ADAS) is a major area of research in today’s vehicle control and safety. In General ADAS can be seen as a mother system with various subsystems to help the driver from pre-crash to post-crash situations. One of the subsystems for ADAS is the Collision Avoidance System (CAS). Nowadays, many researchers are working on different Aspects of CAS, from perception to decision making. Many challenges exist while developing a CAS, but today the greatest challenge is decision making of CAS and its interaction with driver’s behavior. Driving is a complex task and since driver’s consciousness, gender, age and reflexes can cause different behaviors; it is, therefore,...