License plate extraction is an important stage in the vehicle license plate recognition for an automated transport system. This paper presents a novel and practical license plate extraction algorithm based on the edge...
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License plate extraction is an important stage in the vehicle license plate recognition for an automated transport system. This paper presents a novel and practical license plate extraction algorithm based on the edge statistics and the morphology. The proposed approach can be divided into four sections, which are vertical edge extraction, background curve and noise removing, edge statistical analysis and morphology-based license plate extraction. The proposed approach is designed to work in a wide range of acquisition conditions, including unrestricted scene environments, different camera-to-car distances, etc. Under the available database, the average accuracy of locating vehicle license plate is 84%.
Fast transportation of the loads without unintentional load sway has become a regular problem with cranes. Any improvement in the time of load transportation leads to higher rate of load accommodation and thus lower c...
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Fast transportation of the loads without unintentional load sway has become a regular problem with cranes. Any improvement in the time of load transportation leads to higher rate of load accommodation and thus lower costs. In this paper, a four step process is taken to design an optimized fuzzy controller independent and free of any large and expensive computer help. Such a controller can suppress the load sway faster compared to previous reported results of fuzzy crane controls. The proficiency of this controller is confirmed through experimental results.
In this paper a Fuzzy Logic Controller (FLC) for path following of a four-wheel differentially skid steer mobile robot is presented. Fuzzy velocity and fuzzy torque control of the mobile robot is compared with classic...
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In this paper a Fuzzy Logic Controller (FLC) for path following of a four-wheel differentially skid steer mobile robot is presented. Fuzzy velocity and fuzzy torque control of the mobile robot is compared with classical controllers. To assess controllers robot kinematics and dynamics are simulated with parameters of P2-AT mobile robot. Results demonstrate the better performance of fuzzy logic controllers in following a predefined path.
In this paper, robust sliding mode fuzzy logic control of a four-wheel differentially driven skid steer mobile robot, for path following is considered. This approach combines basic principles of sliding mode control (...
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In this paper, robust sliding mode fuzzy logic control of a four-wheel differentially driven skid steer mobile robot, for path following is considered. This approach combines basic principles of sliding mode control (SMC) with fuzzy logic control (FLC). The path comprises a sequence of discrete waypoints. A novel approach in path extraction interpolates waypoints by means of quadratic curve to generate a continuous reference path. The positional data of waypoints are obtained using a vision system mounted on the mobile robot. Experimental study has been carried out to evaluate the performance of the proposed controller and to compare its performance with a conventional fuzzy logic controller performance. The experimental results show that the proposed controller has achieved superior performance in the presence of model uncertainties and external disturbances with minimum reaching time, minimum distance error, and smooth control actions.
作者：
M. FeemsterD.M. DawsonA. BehalW. DixonMatthew Feemster received the B.S degree in Electrical Engineering from Clemson University
Clemson South Carolina in December 1994. Upon graduation he remained at Clemson University and received the M.S. degree in Electrical Engineering in 1997. During this time he also served as a research/teaching assistant. His research work focused on the design and implementation of various nonlinear control algorithms with emphasis on the induction motor and mechanical systems with friction present. He is currently working toward his Ph.D. degree in Electrical Engineering at Clemson University. Darren M. Dawson was born in 1962
in Macon Georgia. He received an Associate Degree in Mathematics from Macon Junior College in 1982 and a B.S. Degree in Electrical Engineering from the Georgia Institute of Technology in 1984. He then worked for Westinghouse as a control engineer from 1985 to 1987. In 1987 he returned to the Georgia Institute of Technology where he received the Ph.D. Degree in Electrical Engineering in March 1990. During this time he also served as a research/teaching assistant. In July 1990 he joined the Electrical and Computer Engineering Department and the Center for Advanced Manufacturing (CAM) at Clemson University where he currently holds the position of Professor. Under the CAM director's supervision he currently leads the Robotics and Manufacturing Automation Laboratory which is jointly operated by the Electrical and Mechanical Engineering departments. His main research interests are in the fields of nonlinear based robust adaptive and learning control with application to electro-mechanical systems including robot manipulators motor drives magnetic bearings flexible cables flexible beams and high-speed transport systems. Aman Behal was born in India in 1973. He received his Masters Degree in Electrical Engineering from Indian Institute of Technology
Bombay in 1996. He is currently working towards a Ph.D in Controls and Robotics at Clemson University. His research focuses on the control of no
In this paper, we extend the observer/control strategies previously published in [25] to an n -link, serially connected, direct drive, rigid link, revolute robot operating in the presence of nonlinear friction effects...
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In this paper, we extend the observer/control strategies previously published in [25] to an n -link, serially connected, direct drive, rigid link, revolute robot operating in the presence of nonlinear friction effects modeled by the Lu-Gre model. In addition, we also present a new adaptive control technique for compensating for the nonlinear parameterizable Stribeck effects. Specifically, an adaptive observer/controller scheme is developed which contains a feedforward approximation of the Stribeck effects. This feedforward approximation is used in a composite controller/observer strategy which forces the average square integral of the position tracking error to an arbitrarily small value. Experimental results are included to illustrate the performance of the proposed controllers.
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