At present, various target detection algorithms are used in detection and classification. It is a problem to improve the accuracy and speed of target detection by using deep learning and neural network model to train ...
详细信息
Currently, most commercial robot manipulators are equipped with conventional PID controllers due to their simplicity in structure and ease of design. Using such a controller, however, it is difficult to achieve a desi...
Currently, most commercial robot manipulators are equipped with conventional PID controllers due to their simplicity in structure and ease of design. Using such a controller, however, it is difficult to achieve a desired control performance since the dynamic equations of a mechanical manipulator are tightly coupled. In addition, they are highly nonlinear and uncertain. This paper uses a new hybrid control scheme to control a direct drive two-link manipulator under inertial parameters changes. The proposed hybrid control scheme consists of a fuzzy logic proportional controller and a conventional integral and derivative controller (FUZZY P+ID). In comparison with a conventional PID controller, only one additional parameter has to be adjusted to tune the FUZZY P+ID controller. The outlined experimental results demonstrate the effectiveness and the robustness of the new FUZZY P+ID controller.
Modular process plants enable the process industry to adapt to volatile and fluctuating markets. The preferred process technology concept for these market scenarios is realized through combining pre-engineered process...
ISBN:
(数字)9781728189567
ISBN:
(纸本)9781728189574
Modular process plants enable the process industry to adapt to volatile and fluctuating markets. The preferred process technology concept for these market scenarios is realized through combining pre-engineered process equipment assemblies (PEA) from different manufacturers with standardized interfaces. While the flexibility gain for this type of plants is high, the design of the safety systems of these modular plants in terms of exchangeability and compatibility is challenging. One solution could be the development of a safety-interface for PEAs to create flexible and scalable safety systems. The principles of modular basic processcontrol are analyzed and requirements with respect to safety design are discussed. The authors provide a differentiation of the intramodular safety concept of a single PEA from the intermodular safety concept of a complete modular plant. A concept for safe and modular interaction of PEAs in a modular plant is developed and additionally validated on a basic demonstrator. Finally, from these findings, standardization requirements are provided and aspects for further research are pointed out.
Several data compressors have been proposed in distributed optimization frameworks of network systems to reduce communication overhead in large-scale applications. In this paper, we demonstrate that effective informat...
详细信息
作者：
F.L. LewisDept. of Electical Engineering
The University of Texas at Arlington U.S.A. F. L. Lewis was born in Wärzburg. Germany
subsequently studyning in Chile and Goruonstoun School in Scotland. He obtained the Bachelor's Degree in Physics/Electrical Engineering and the Master's of Electrical Engineering Degree at Rice University in 1971. He spent six years in the U.S. navy serving as Navigator aboard the frigate USS Trippe (FF-1075) and Executive Officer and Acting Commanding Officer aboard USS Salinan (ATF-161). In 1977 he received the Master's of Science in Aeronautical Engineering from the University of West Florida. In 1981 he obtained the Ph.D. degree at The Georgia Institute of Technology in Atlanta where he was employed as a professor from 1981 to 1990 and is currently an Adjunct Professor. He is a Professor of Electrical Engineering at The University of Texas at Arlington where he was awarded the Moncrief-O'Donnell Endowed Chair in 1990 at the Automation and Robotics Research Institute. Dr. Lewis has studied the geometric analytic and structural properties of dynamical systems and feedback control automation. His current interests include robotics intelligent control neural and fuzzy systes nonlinear systems and manufacturing process control. He is the author/co-author of 2 U.S. patents 124 journal papers 20 chapters and encyclopedia articles 210 refereed conference papers seven books: Optimal Control Optimal Estimation Applied Optimal Control and Estimation Aircraft Control and Simulation Control of Robot Manipulators Neural Network Control High-Level Feedback Control with Neural Networks and the IEEE reprint volume Robot Control. Dr. Lewis is a registered Professional Engineer in the State of Texas and was selected to the Editorial Boards of International Journal of Control Neural Computing and Applications and Int. J. Intelligent Control Systems. He is the recipient of an NSF Research Initiation Grant and has been continuously funded by NSF since 1982. Since 1991 he has received $1.8 m
A framework is given for controller design using Nonlinear Network Structures, which include both neural networks and fuzzy logic systems. These structures possess a universal approximation property that allows them t...
详细信息
A framework is given for controller design using Nonlinear Network Structures, which include both neural networks and fuzzy logic systems. These structures possess a universal approximation property that allows them to be used in feedback control of unknown systems without requirements for linearity in the system parameters or finding a regression matrix. Nonlinear nets can be linear or nonlinear in the tunable weight parameters. In the latter case weight tuning algorithms are not straightforward to obtain. Feedback control topologies and weight tuning algorithms are given here that guarantee closed-loop stability and bounded weights. Extensions are discussed to force control, backstepping control, and output feedback control, where dynamic nonlinear nets are required.
暂无评论