scholarly journals Design of a semi-autonomous modular robotic vehicle for gas pipeline inspection

2003 ◽  
Vol 217 (2) ◽  
pp. 109-122 ◽  
Author(s):  
J K Ong ◽  
D Kerr ◽  
K Bouazza-Marouf
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Autonomous Vehicle ◽  
Robotic System ◽  
Rate Of Change ◽  
Control Technique ◽  
Background Information ◽  
Pipe System ◽  
Robotic Vehicle ◽  
Proprioceptive Sensors

This paper presents a new solution for inspecting and repairing defects in live gas pipelines. The proposed approach is the development of a modular and semi-autonomous vehicle system. The robotic system has a drive mechanism, capable of navigating and adjusting its orientation in various configurations of pipelines. Other features of the system are cable-free communications, semi-autonomous motion control as well as integration of sensory devices. The robotic system is designed to traverse in 150–300 mm diameter pipes through straight and curved sections, junctions and reducers. The vehicle control and navigation technique is implemented using a two-mode controller consisting of a proportional-integral-derivative (PID) and fuzzy logic control. Unlike other available systems, the vehicle employs proprioceptive sensors to monitor its own states. The fuzzy logic controller is used to evaluate the sensor outputs such as speed, climbing angle and rate of change of climbing angle. This control technique allows the vehicle to drive and adapt in a partially observable gas pipe system. Laboratory experiment results are presented. The paper also describes a cable-free communication method for the system. A brief account of typical pipe environments and currently available inspection tools is presented as background information.

scholarly journals Fuzzy logic control for use in in-pipe mobile robotic system navigation

2003 ◽  
Vol 217 (5) ◽  
pp. 401-419 ◽  
Author(s):  
J K Ong ◽  
K Bouazza-Marouf ◽  
D Kerr
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Mimo System ◽  
Autonomous Vehicle ◽  
Fuzzy Model ◽  
Robotic System ◽  
Navigation Problem ◽  
Logic Control ◽  
Environment Recognition

This paper presents a fuzzy logic control for the navigation of a mobile robotic system in gas pipelines. The robotic system is designed for a local gas distribution pipeline network with 150–300mm diameter pipes; common pipe fittings in use are straight and bend sections, reducers and slope pipe sections. The navigation problem forms a part of the current development of a new modular and semi-autonomous vehicle system. The vehicle control and navigation technique is implemented using a two-mode controller consisting of a proportional-integral-derivative (PID) and fuzzy logic control. The PID controller is responsible for direct control of the actuators, while the fuzzy logic controller is used to evaluate as well as to define the sensor outputs such as speed, climbing angle and rate of climbing angle in order to perceive the different types of pipe environment and vehicle actions. Since the navigation problem involves a multivariable input-output (MIMO) system, a cascaded hierarchical fuzzy model configuration is used to reduce the dimensionality of the fuzzy model. The fuzzy navigation controller is thus an interlink fuzzy subsystem of the pipe environment recognition and action adjustment subsystems. Results of simulations and laboratory experiments are presented to demonstrate the ability of the control strategy. A brief description of the mobile robotic system used is presented as background.

scholarly journals Design and Lyapunov Stability Analysis of a Fuzzy Logic Controller for Autonomous Road Following

2010 ◽  
Vol 2010 ◽  
pp. 1-20 ◽  
Author(s):  
Yi Fu ◽  
Howard Li ◽  
Mary Kaye
Keyword(s):  
Fuzzy Logic ◽  
Stability Analysis ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Intelligent Vehicles ◽  
Intelligent Vehicle ◽  
Rule Base ◽  
Control Laws ◽  
Robotic Vehicle ◽  
Road Following

Autonomous road following is one of the major goals in intelligent vehicle applications. The development of an autonomous road following embedded system for intelligent vehicles is the focus of this paper. A fuzzy logic controller (FLC) is designed for vision-based autonomous road following. The stability analysis of this control system is addressed. Lyapunov's direct method is utilized to formulate a class of control laws that guarantee the convergence of the steering error. Certain requirements for the control laws are presented for designers to choose a suitable rule base for the fuzzy controller in order to make the system stable. Stability of the proposed fuzzy controller is guaranteed theoretically and also demonstrated by simulation studies and experiments. Simulations using the model of the four degree of freedom nonholonomic robotic vehicle are conducted to investigate the performance of the fuzzy controller. The proposed fuzzy controller can achieve the desired steering angle and make the robotic vehicle follow the road successfully. Experiments show that the developed intelligent vehicle is able to follow a mocked road autonomously.

scholarly journals Dynamic response improvement of hybrid system by implementing ANN-GA for fast variation of photovoltaic irradiation and FLC for wind turbine

2015 ◽  
Vol 64 (2) ◽  
pp. 291-314 ◽  
Author(s):  
Maziar Izadbakhsh ◽  
Alireza Rezvani ◽  
Majid Gandomkar
Keyword(s):  
Fuzzy Logic ◽  
Wind Speed ◽  
Dynamic Response ◽  
Wind Turbine ◽  
Hybrid System ◽  
Pitch Angle ◽  
Fuzzy Logic Controller ◽  
Control Method ◽  
Control Technique ◽  
Power Curves

Abstract In this paper, dynamic response improvement of the grid connected hybrid system comprising of the wind power generation system (WPGS) and the photovoltaic (PV) are investigated under some critical circumstances. In order to maximize the output of solar arrays, a maximum power point tracking (MPPT) technique is presented. In this paper, an intelligent control technique using the artificial neural network (ANN) and the genetic algorithm (GA) are proposed to control the MPPT for a PV system under varying irradiation and temperature conditions. The ANN-GA control method is compared with the perturb and observe (P&O), the incremental conductance (IC) and the fuzzy logic methods. In other words, the data is optimized by GA and then, these optimum values are used in ANN. The results are indicated the ANN-GA is better and more reliable method in comparison with the conventional algorithms. The allocation of a pitch angle strategy based on the fuzzy logic controller (FLC) and comparison with conventional PI controller in high rated wind speed areas are carried out. Moreover, the pitch angle based on FLC with the wind speed and active power as the inputs can have faster response that lead to smoother power curves, improving the dynamic performance of the wind turbine and prevent the mechanical fatigues of the generator

Design of fuzzy logic controller for load frequency control in an isolated hybrid power system

2020 ◽  
Vol 39 (6) ◽  
pp. 8273-8283
Author(s):  
N. Kirn Kumar ◽  
V. Indra Gandhi
Keyword(s):  
Fuzzy Logic ◽  
Power System ◽  
Fuzzy Logic Controller ◽  
Frequency Control ◽  
Pso Algorithm ◽  
Green Energy ◽  
Load Frequency Control ◽  
Control Technique ◽  
Hybrid Power System ◽  
Hybrid Power

As the world is moving towards green energy generation to reduce the pollution by renewable sources such as wind, solar, geothermal and more. These sources are intermittent in nature, to coordinate and control with traditional power generating units a control technique is necessary. This paper mainly focuses on the design of fuzzy based classical controller using a PSO algorithm for optimal controller gains to control the frequency variations in island hybrid power system. The considered mathematical model comprises of a diesel generating model, wind turbine generator and a battery storage system. Fuzzy is an intelligent controller which is designed with trial and error rules or on the basis of past experience provided by experts or by optimization methods for optimized gains using computational algorithms. To give best solution for these kinds of problems with FLCs traditional controllers are integrated with fuzzy logic. The PSO algorithm is applied to tune the classical controller gains to decrease the frequency deviation of the island power system, during the different load and wind disturbances. The Fuzzy PID classical controller shows the best performance compared with the only fuzzy and Fuzzy-PI controller configurations by illustrating the under shoot, overshoot and settling time and the proposed method is robust for various loading conditions and different wind changes.

Fuzzy Logic Control of a Laboratory Magnetic Levitation System

2003 ◽  
Author(s):  
V. Ram Mohan Parimi ◽  
Piyush Jain ◽  
Devendra P. Garg
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Magnetic Levitation ◽  
Rate Of Change ◽  
Control Laboratory ◽  
Logic Control ◽  
Levitation System ◽  
Magnetic Levitation System ◽  
And Control

This paper deals with the Fuzzy Logic control of a Magnetic Levitation system [1] available in the Robotics and Control Laboratory at Duke University. The laboratory Magnetic Levitation system primarily consists of a metallic ball, an electromagnet and an infrared optical sensor. The objective of the control experiment is to balance the metallic ball in a magnetic field at a desired position against gravity. The dynamics and control complexity of the system makes it an ideal control laboratory experiment. The student can design their own control schemes and/or change the parameters on the existing control modes supplied with the Magnetic Levitation system, and evaluate and compare their performances. In the process, they overcome challenges such as designing various control techniques, choose which specific control strategy to use, and learn how to optimize it. A Fuzzy Logic control scheme was designed and implemented to control the Magnetic Levitation system. Position and rate of change of position were the inputs to Fuzzy Logic Controller. Experiments were performed on the existing Magnetic Levitation system. Results from these experiments and digital simulation are presented in the paper.

scholarly journals Technological Advances of Speed Control of Induction Motor with PI and Fuzzy Logic Controllers

2020 ◽  
Vol 8 (6S) ◽  
pp. 41-45
Keyword(s):  
Fuzzy Logic ◽  
Induction Motor ◽  
Fuzzy Logic Controller ◽  
Induction Motors ◽  
Control Technique ◽  
Fuzzy Logic Controllers ◽  
Technological Advances ◽  
Three Phase ◽  
Soft Computing Techniques ◽  
Recent Trends

At the present scenario, three-phase induction motors (IM) are having wide applications in the industries. So, the need for an effective controlling technique is compulsory. Various techniques are there to control the speed of IM. Soft computing techniques are having in a great improvement in the recent trends. This paper discusses on the scalar control technique of induction motor for conventional PI and fuzzy logic controller. The performance of an induction motor is simulated using MATLAB/Simulink with PI and fuzzy controllers, the results are analyzed and the techno feasibility of both the controllers is presented in detail. Torque-speed (T-N) characteristics of an induction motor for a traditional PI model are considered and compared with rules-based fuzzy logic

scholarly journals Investigations on stability and performance of a varia-ble frequency based fuzzy logic controller for induction cooking system

2017 ◽  
Vol 7 (1.2) ◽  
pp. 15 ◽  
Author(s):  
Pradeep Vishnuram ◽  
Booma Nagarajan ◽  
A. Sureshkumar
Keyword(s):  
Fuzzy Logic ◽  
Power Control ◽  
Fuzzy Logic Controller ◽  
Frequency Control ◽  
Power Level ◽  
Heating System ◽  
Stability Study ◽  
Control Technique ◽  
Stability Range ◽  
Induction Cooking

Load variability and perturbation is an important issue in the induction cooking applications as it hinders the performance of the heating system considerably .Therefore a precise power control technique is required for induction heating applications by considering the stability issues and dynamic response of the system. Also, the safety operating ranges need to be confirmed to ascertain the competency of the controller. In this paper, a Fuzzy logic based power control scheme is introduced by considering the load uncertainties. The suggested power control technique uses variable frequency control of the inverter for reaching the target power level. Also, a detailed stability study is done for investigating stability range within which the system operation is safe and stable. The said work is simulated in MATLAB/Simulink environment and realized as a prototype where advanced FPGA controller renders its hand .The simulation and hardware results reveal that the suggested technique is versatile.

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