Sharif Digital Repository

In this paper, we exploit a fuzzy controller on a flexible bevel-tip needle to manipulate the needle's base in order to steer its tip in a preset obstacle-free and target-tracking path. Although the needle tends to follow a curvature path, spinning the needle with an extremely high rotational velocity makes it symmetric with respect to the tissue to follow a straight path. The fuzzy controller determines an appropriate spinning to generate the planned trajectory and, the closed-loop system tries to match the needle body with that trajectory. The swine's brain tissue model, extracted from an in-vitro experimental setup, is a non-homogenous, uncertain and fast-updatable network to model real... 

Evolutionary Algorithms are vastly used in development of rule based classifier systems in data mining where the rule base is usually a set of If-Then rules and an evolutionary trait develops and optimizes these rules. Genetic Algorithm is usually a favorite solution for such tasks as it globally searches for good rule-sets without any prior bias or greedy force, but it is usually slow. Also, designing a good genetic algorithm for rule base evolution requires the design of a recombination operator that merges two rule bases without disrupting the functionalities of each of them. To overcome the speed problem and the need to design recombination operator, this paper presents a novel algorithm... 

This paper addresses the design of an observer-based adaptive fuzzy controller for a class of uncertain non-strict nonlinear systems subject to time-delays, unknown direction, input saturation, and output constraint. The Barrier Lyapunov Function (BLF) has been utilized to keep the system output inside the desired bounds. The state and input delays have been handled by using the Lyapunov–Krasovskii function and including an integral compensator term in the controller, respectively. A state observer has been designed to estimate the unmeasured states. The Lipschitz condition for proving boundedness of the estimated states has been relaxed. The Nussbaum gain function has been exploited to deal... 

In this paper, GyroSym, a compact highly-stable single-wheel robot is introduced. Symmetrical flywheels have been used as its stabilization mechanism to keep the wheel upright. Thanks to the type of the flywheel used, the dynamic equations of the robot is simplified, the torque needed to tilt the spin axis is reduced, and the space is drastically minimized. Besides, a centrifugal clutch is used to smooth the motion of the robot in forward motion. Two controllers, fuzzy and fuzzy-Padé, were implemented based on their ability to stabilize the robot. Although both prevented the GyroSym from falling over, neither can entirely cancel out the effects of nonlinear behaviors that is present in the... 

In this paper by using a combination of fuzzy identification and the sliding mode control a fuzzy adaptive sliding mode scheme is designed to stabilize the unstable periodic orbits of chaotic systems. The chaotic system is assumed to have an affine form x(n) = f(X) + g(X)u where f and g are unknown functions. Using only the input-output data obtained from the underlying dynamical system, two fuzzy systems are constructed for identification of f and g. Two distinct methods are utilized for fuzzy modeling, the least squares and the gradient descent techniques. Based on the estimated fuzzy models, an adaptive controller, which works through the sliding mode control, is designed to make the... 

Too much effort has been done for manipulating individual atoms, using nano-manipulators and Scanning Tunneling Microscopes (STM). On the other hand, characterization and manipulation of nano-flows is of great concern. In the current work a molecular valve has been considered, which is made up of six atoms placed on the circumstance of a circle. A fuzzy controller has been designed for controlling the diameter of this molecular valve. The designed fuzzy controller used singleton fuzzifier, Mamdani inference engine, center average defuzzifier and exponential membership functions. A model based on the classical Molecular Dynamics (MD) is used for modeling the nano-system and passing the states... 

The mechatronic design of a novel mechanism for ball and plate system is discussed. A webcam provides the system with feedback of the ball's position. A heuristic technique for image processing is introduced. The kinematics and dynamics of the system are also described. Supervisory fuzzy control and sliding control techniques are proposed to perform position control for the system. Experimental results corroborate the validity of the controllers. © 2008 IEEE  

In this paper, a novel generalized predictive control (GPC) strategy using multiple models approach has been presented. The proposed strategy is realized based on the Takagi-Sugeno-Kang (TSK) fuzzy-based modeling for control of a tubular heat exchanger system. In this strategy, different operating environments of the system with varying parameters are first identified. Then for each environment, a linear model and its corresponding fuzzy predictive controller are designed. For demonstrating the effectiveness of the proposed approach, simulations are done and the results are compared with those obtained using the single model predictive control approach. The results can verify the validity of... 

In the present work, a fuzzy supervisory control approach combined with an adaptive model predictive controller (AMPC), has been proposed to maximize the productivity of an anaerobic digestion (AD) process, while keeping the operation stable. In the proposed hierarchal control strategy, the set-point of the inner loop is provided by a supervisory controller. In the inner loop an AMPC has been applied to achieve the desired methane production rate by manipulating the feed flow rate. The AMPC is designed based on the auto-regressive moving average (ARMA) model whose parameters are updated at each sampling time to make the controller more robust against uncertainties and external loads. In the... 

The aim of this article is design, fabricate, and control a conceptual prototype of a flexible wearable robot to increase fingers’ force using a novel cable mechanism. In this robot, force and position are controlled in separate phases by a fuzzy system equipped with emotional learning. A Flexible structure has been chosen for this robot, because flexible gloves are lighter and much more suitable for use in daily tasks compared to rigid structures. Since this system is supposed to be substituted for weak or damaged limb, it should have a behavior similar to the body organs as much as possible. Therefore, a novel mechanism, inspired by the natural movement mechanism of the human hand, has... 

As wind energy is becoming one of the fastest-growing renewable energy resources, controlling large-scale wind turbines remains a challenging task due to its system model nonlinearities and high external uncertainties. The main goal of the current work is to propose an intelligent control of the wind turbine system without the need for model identification. For this purpose, a novel model-independent nonsingular terminal sliding-mode control (MINTSMC) using the basic principles of the ultra-local model (ULM) and combined with the single input interval type-2 fuzzy logic control (SIT2-FLC) is developed for non-linear wind turbine pitch angle control. In the suggested control framework, the... 

The aim of this article is design, fabricate, and control a conceptual prototype of a flexible wearable robot to increase fingers’ force using a novel cable mechanism. In this robot, force and position are controlled in separate phases by a fuzzy system equipped with emotional learning. A Flexible structure has been chosen for this robot, because flexible gloves are lighter and much more suitable for use in daily tasks compared to rigid structures. Since this system is supposed to be substituted for weak or damaged limb, it should have a behavior similar to the body organs as much as possible. Therefore, a novel mechanism, inspired by the natural movement mechanism of the human hand, has... 

As wind energy is becoming one of the fastest-growing renewable energy resources, controlling large-scale wind turbines remains a challenging task due to its system model nonlinearities and high external uncertainties. The main goal of the current work is to propose an intelligent control of the wind turbine system without the need for model identification. For this purpose, a novel model-independent nonsingular terminal sliding-mode control (MINTSMC) using the basic principles of the ultra-local model (ULM) and combined with the single input interval type-2 fuzzy logic control (SIT2-FLC) is developed for non-linear wind turbine pitch angle control. In the suggested control framework, the... 

Purpose - To devise a new technique to synthesise optimal feedback control law for non-linear dynamic systems through fuzzy logic. Design/methodology/approach - The proposed methodology utilizes the open-loop optimal control solutions (OCSs) of the non-linear systems for the training of the fuzzy system in the process of developing closed-loop fuzzy logic guidance (FLG). This is achieved through defining a set of non-dimensionalised variables related to the system states. Findings - FLG is capable of generating closed-loop control law for the non-linear problem investigated. Since the proposed fuzzy structure is independent of the system equations, the approach is potentially applicable to... 

The stability issue of mobile manipulators, particularly when the end-effector and the vehicle have to follow a predefined trajectory (for some special duties like painting a plane or carrying a light load), is a crucial subject and needs special attention. In this paper, by utilizing the manipulator compensation motions, the instantaneous proper configuration for a redundant mobile robot is determined. A fast methodology taking into account the dynamic interaction between the manipulator and the vehicle is proposed for enhancing the tipover stability (i.e. stability against overturning) of the mobile manipulator by employing the soft computing approach including a genetic algorithm, neural... 

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...