Lyapunov methods and density functions provide dual characterizations of the solutions of a nonlinear dynamic system. This work exploits the idea of combining both techniques, to yield stability results that are valid...
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Lyapunov methods and density functions provide dual characterizations of the solutions of a nonlinear dynamic system. This work exploits the idea of combining both techniques, to yield stability results that are valid for almost all the solutions of the system. Based on the combination of Lyapunov and density functions, analysis methods are proposed for the derivation of almost input-to-state stability, and of almost global stability in nonlinear systems. The techniques are illustrated for an inertial attitude observer, where angular velocity readings are corrupted by non-idealities.
In this paper a system for control and 3D visualization of a manipulator for weld inspection of nuclear reactor vessels is described. Based on client-server TCP/IP software architecture, the presented control system e...
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In this paper a system for control and 3D visualization of a manipulator for weld inspection of nuclear reactor vessels is described. Based on client-server TCP/IP software architecture, the presented control system enables an operator to perform the entire inspection procedure remotely over a network, avoiding exposure to dangerous radiation which is commonly present in nuclear reactor environments. The developed graphical user interface provides all necessary tools needed for planning robot scan trajectories, their verification on a virtual 3D model and execution on a remote robot. In addition, the weld inspection process can be observed in parallel on a virtual robot and reactor vessel model and on live video streams captured by two special cameras mounted on the robot.
This paper presents a method for extension of matrix model of manufacturing system in order to provide an efficient tool for analysis of systems with various dispatching sequences of shared resources. Proposed method ...
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This paper presents a method for extension of matrix model of manufacturing system in order to provide an efficient tool for analysis of systems with various dispatching sequences of shared resources. Proposed method is used for transformation of system matrices in linear max-plus model. Once the linear model is determined sequence feasibility can be checked. Furthermore, the method provides a straightforward procedure for production cycle calculation and resource utilisation. Efficiency of presented technique is demonstrated on a manufacturing system example at the end of the paper.
This paper presents the analytical and the experimental investigation of common-mode (CM) current generation in a half-bridge converter (HBC) circuit comparison to a full-bridge converter (FBC) circuit by the viewpoin...
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This paper presents the analytical and the experimental investigation of common-mode (CM) current generation in a half-bridge converter (HBC) circuit comparison to a full-bridge converter (FBC) circuit by the viewpoint of circuit unbalance. Because of the CM current generation is the effect of the circuit unbalance. The circuit unbalance is mainly caused by the switching action, and parasitic capacitances occurrence in the circuit with respect to the frame ground or chassis. The HBC and FBC circuits analysis by equivalent circuit model is resultant that the HBC is the unbalanced switching circuit, especially unbalanced transmission path (sending and returning line) impedances, however, the FBC is the balanced switching circuit (especially balanced Transmission path impedances). The experimental results show that HBC circuit mostly generates the unbalanced CM voltages at the dc source terminals and produces the CM current, 348 mA flowing into the frame ground, however, the generated CM voltages of the FBC circuit at the dc source terminals are equal or balanced voltage, so that the production of CM current flowing into the frame ground is greatly reduced to 100 mA.
In this paper we present a methodology for decision making in multi agent system comprised of agents driven by repulsive force and attracting force. Navigation functions are expressed as a set of fuzzy rules obtained ...
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ISBN:
(纸本)9781424422241
In this paper we present a methodology for decision making in multi agent system comprised of agents driven by repulsive force and attracting force. Navigation functions are expressed as a set of fuzzy rules obtained by fuzzy Lyapunov stability criteria, thus ensuring stability of the overall system. The goal of the proposed methodology is to create desired formations by moving agents from their initial positions to formation targets, while in the same time avoiding collisions. The destination targets are dynamically permutated as long as the required formation is achieved.
Initially introduced as a model-free control design method, in today practice fuzzy control is dominantly used as yet another nonlinear control technique based either on a linear or nonlinear model of a process. This ...
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Initially introduced as a model-free control design method, in today practice fuzzy control is dominantly used as yet another nonlinear control technique based either on a linear or nonlinear model of a process. This paper addresses the stability assessment of a fuzzy logic control system based only on the partial knowledge of a controlled process. Lyapunov stability conditions are derived and analyzed by using fuzzy numbers and fuzzy arithmetic. The experimental results obtained for a non-stable second-order system confirmed that this approach could be successfully implemented. Some questions, addressed in the paper, remained open for further investigation.
作者：
Omid ShakerniaYi MaT. John KooShankar SastryDept. of Electrical Engineering & Computer Science
University of California at Berkeley Berkeley CA94720-1774 U.S.A. Tak-Kuen John Koo received the B.Eng. degree in 1992 in Electronic Engineering and the M.Phil. in 1994 in Information Engineering both from the Chinese University of Hong Kong. From 1994 to 1995
he was a graduate student in Signal and Image Processing Institute at the University of Southern California. He is currently a Ph.D. Candidate in Electrical Engineering and Computer Sciences at the University of California at Berkeley. His research interests include nonlinear control theory hybrid systems inertial navigation systems with applications to unmanned aerial vehicles. He received the Distinguished M.Phil. Thesis Award of the Faculty of Engineering The Chinese University of Hong Kong in 1994. He was a consultant of SRI International in 1998. Currently he is the team leader of the Berkeley AeRobot Team and a delegate of The Graduate Assembly University of California at Berkeley. He is a student member of IEEE and SIAM. S. Shankar Sastry received his Ph.D. degree in 1981 from the University of California
Berkeley. He was on the faculty of MIT from 1980-82 and Harvard University as a Gordon McKay professor in 1994. He is currently a Professor of Electrical Engineering and Computer Sciences and Bioengineering and Director of the Electronics Research Laboratory at Berkeley. He has held visiting appointments at the Australian National University Canberra the University of Rome Scuola Normale and University of Pisa the CNRS laboratory LAAS in Toulouse (poste rouge) and as a Vinton Hayes Visiting fellow at the Center for Intelligent Control Systems at MIT. His areas of research are nonlinear and adaptive control robotic telesurgery control of hybrid systems and biological motor control. He is a coauthor (with M. Bodson) of “Adaptive Control: Stability Convergence and Robustness Prentice Hall 1989.” and (with R. Murray and Z. Li) of “A Mathematical Introduction to Robotic Manipulati
In this paper, we use computer vision as a feedback sensor in a control loop for landing an unmanned air vehicle (UAV) on a landing pad. The vision problem we address here is then a special case of the classic ego-mot...
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In this paper, we use computer vision as a feedback sensor in a control loop for landing an unmanned air vehicle (UAV) on a landing pad. The vision problem we address here is then a special case of the classic ego-motion estimation problem since all feature points lie on a planar surface (the landing pad). We study together the discrete and differential versions of the ego-motion estimation, in order to obtain both position and velocity of the UAV relative to the landing pad. After briefly reviewing existing algorithm for the discrete case, we present, in a unified geometric framework, a new estimation scheme for solving the differential case. We further show how the obtained algorithms enable the vision sensor to be placed in the feedback loop as a state observer for landing control. These algorithms are linear, numerically robust, and computationally inexpensive hence suitable for real-time implementation. We present a thorough performance evaluation of the motion estimation algorithms under varying levels of image measurement noise, altitudes of the camera above the landing pad, and different camera motions relative to the landing pad. A landing controller is then designed for a full dynamic model of the UAV. Using geometric nonlinear control theory, the dynamics of the UAV are decoupled into an inner system and outer system. The proposed control scheme is then based on the differential flatness of the outer system. For the overall closed-loop system, conditions are provided under which exponential stability can be guaranteed. In the closed-loop system, the controller is tightly coupled with the vision based state estimation and the only auxiliary sensor are accelerometers for measuring acceleration of the UAV. Finally, we show through simulation results that the designed vision-in-the-loop controller generates stable landing maneuvers even for large levels of image measurement noise. Experiments on a real UAV will be presented in future work.
作者：
Tak Wing Edward LauYu-Chi HoDivision of Engineering and Applied Sciences
Harvard University Cambridge MA02138 U.S.A. Yu-Chi (Larry) Ho received his S.B. and S.M. degrees in Electrical Engineering from M.I.T. and his Ph.D. in Applied Mathematics from Harvard University. Except for three years of full time industrial work he has been on the Harvard Faculty. Since 1969 he has been Gordon McKay Professor of Engineering and Applied Mathematics. In 1988
he was appointed to the T. Jefferson Coolidge Chair in Applied Mathematics and Gordon McKay Yu-Chi (Larry) Ho received his S.B. and S.M. degrees in Electrical Engineering from M.I.T. and his Ph.D. in Applied Mathematics from Harvard University. Except for three years of full time industrial work he has been on the Harvard Faculty. Since 1969 he has been Gordon McKay Professor of Engineering and Applied Mathematics. In 1988 he was appointed to the T. Jefferson Coolidge Chair in Applied Mathematics and Gordon McKay Professor of Engineering at Harvard and as visiting professor to the Cockrell Family Regent's Chair in Engineering at the University of Texas Austin. He has published over 120 articles and three books one of which (co-authored with A.E. Bryson Jr.) has been translated into both Russian and Chinese and made the list of Citation Classics as one of the most referenced works on the subject of optimal control. He is on the editorial boards of several international journals and is the editor-in-chief of the new international Journal on Discrete Event Dynamic Systems. He is the recipient of various fellowships and awards including the Guggenheim (1970) and the IEEE Field Award for Control Engineering and Science (1989) the Chiang Technology Achievement Award (1993). He is a fellow of IEEE a Distinguished Member of the Control Systems Society and a member of the U.S. National Academy of Engineering. In addition to serving on various governmental and industrial panels and professional society administrative bodies he was the President of the IEEE Robotics & Automation Society in 1988
Combinatorial problems are known to be difficult because of the shear size of the solution space and the lack of polynomial time algorithms to “solve” them. Heuristics are often devised to produce acceptable solutio...
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Combinatorial problems are known to be difficult because of the shear size of the solution space and the lack of polynomial time algorithms to “solve” them. Heuristics are often devised to produce acceptable solutions in an affordable time. In this paper, we propose a method called super-heuristic that expands the capabilities of heuristics using randomization and sampling techniques. We submit that heuristics are in general strategies that map from available information of a problem instance to decisions in solution constructions/improvement. We show that it is important to utilize the information effectively in the randomization process. More importantly, the possibility of randomization around a heuristic spells out the demarcation between the roles of human and machines in complex optimization problems.
In this paper we have considered systems in which agents communicate via their environment. In these systems the agents do not have direct and explicit communication with each other and instead they have implicit comm...
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In this paper we describe a procedure that exploits geometric properties of state space in the investigation of the system stability. Although this method is cumbersome, its practical value becomes clear in the situat...
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In this paper we describe a procedure that exploits geometric properties of state space in the investigation of the system stability. Although this method is cumbersome, its practical value becomes clear in the situation when state space is reduced to a phase plane, which is the case in a second-order system. Then phase plane analysis offers well known procedures (especially in case f(.) is linear) for the determination of the system stability. Simulation results, obtained by implementation of the proposed method on the fuzzy controller design, are given at the end of the paper
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