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141.
A Study on Lateral Control of Autonomous Vehicles via Fired Fuzzy Rules Chromosome Encoding Scheme 总被引:1,自引:0,他引:1
In this paper, we propose a novel Fired Rules Chromosomes (FRC) encoding scheme for a fuzzy controller tuned by Genetic Algorithms
(GA). The proposed method improves the optimization speed through the reduction of the search space. In addition, an improvement
in convergence is demonstrated. The fuzzy controller optimized by the FRC scheme is employed to maintain the lateral position
of an autonomous vehicle. The robustness of the controller to parameter variation is studied by Monte-Carlo analysis. Simulation
and experimental studies demonstrate the performance of the lateral controller. 相似文献
142.
This paper focuses on the performance evaluation of complex man-made systems, such as assembly lines, electric power grid,
traffic systems, and various paper processing bureaucracies, etc. For such problems, applying the traditional optimization
tool of mathematical programming and gradient descent procedures of continuous variables optimization are often inappropriate
or infeasible, as the design variables are usually discrete and the accurate evaluation of the system performance via a simulation
model can take too much calculation. General search type and heuristic methods are the only two methods to tackle the problems.
However, the “goodness” of heuristic methods is generally difficult to quantify while search methods often involve extensive
evaluation of systems at many design choices in a large search space using a simulation model resulting in an infeasible computation
burden. The purpose of this paper is to address these difficulties simultaneously by extending the recently developed methodology
of Ordinal Optimization (OO). Uniform samples are taken out from the whole search space and evaluated with a crude but computationally
easy model when applying OO. And, we argue, after ordering via the crude performance estimates, that the lined-up uniform
samples can be seen as an approximate ruler. By comparing the heuristic design with such a ruler, we can quantify the heuristic
design, just as we measure the length of an object with a ruler. In a previous paper we showed how to quantify a heuristic
design for a special case but we did not have the OO ruler idea at that time. In this paper we propose the OO ruler idea and
extend the quantifying method to the general case and the multiple independent results case. Experimental results of applying
the ruler are also given to illustrate the utility of this approach.
Zhen Shen received the B.E. degree from Department of Automation, Tsinghua University, Beijing, China in 2004. Currently, he is a Ph.D. candidate of Center for Intelligent and Networked Systems (CFINS), Department of Automation, Tsinghua University. He was a Visiting Scholar from Oct. 2007 to Apr. 2008 at Department of Manufacturing Engineering and Center for Information and Systems Engineering, Boston University, MA, USA. He specializes in the area of the discrete event dynamic systems (DEDS) theory and applications, and the optimization of complex systems. He is a student member of IEEE. Yu-Chi 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 Systems Engineering at Harvard and as visiting professor to the Cockrell Family Regent’s Chair in Engineering at the University of Texas, Austin. In 2001, he retired from teaching duties at Harvard and became a Research Professor (2001–2006) and also was appointed to be a chair professor and chief scientist (part time), at the Center for Intelligent and Networked Systems (CFINS), Department of Automation, Tsinghua University, Beijing China. Qian-Chuan Zhao received the B.E. degree in automatic control in July 1992, the B.S. degree in applied mathematics in July 1992, and the Ph.D. degree in control theory and its applications in July 1996, all from Tsinghua University, Beijing, China. He is currently a Professor and Associate Director of the Center for Intelligent and Networked Systems (CFINS), Department of Automation, Tsinghua University. He was a Visiting Scholar at Carnegie Mellon University, Pittsburgh, PA, and Harvard University, Cambridge, MA, in 2000 and 2002, respectively. He was a Visiting Professor at Cornell University, Ithaca, NY, in 2006. His research interests include discrete event dynamic systems (DEDS) theory and applications, optimization of complex systems, and wireless sensor networks. Dr. Zhao is an associate editor for the Journal of Optimization Theory and Applications. 相似文献
Zhen ShenEmail: |
Zhen Shen received the B.E. degree from Department of Automation, Tsinghua University, Beijing, China in 2004. Currently, he is a Ph.D. candidate of Center for Intelligent and Networked Systems (CFINS), Department of Automation, Tsinghua University. He was a Visiting Scholar from Oct. 2007 to Apr. 2008 at Department of Manufacturing Engineering and Center for Information and Systems Engineering, Boston University, MA, USA. He specializes in the area of the discrete event dynamic systems (DEDS) theory and applications, and the optimization of complex systems. He is a student member of IEEE. Yu-Chi 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 Systems Engineering at Harvard and as visiting professor to the Cockrell Family Regent’s Chair in Engineering at the University of Texas, Austin. In 2001, he retired from teaching duties at Harvard and became a Research Professor (2001–2006) and also was appointed to be a chair professor and chief scientist (part time), at the Center for Intelligent and Networked Systems (CFINS), Department of Automation, Tsinghua University, Beijing China. Qian-Chuan Zhao received the B.E. degree in automatic control in July 1992, the B.S. degree in applied mathematics in July 1992, and the Ph.D. degree in control theory and its applications in July 1996, all from Tsinghua University, Beijing, China. He is currently a Professor and Associate Director of the Center for Intelligent and Networked Systems (CFINS), Department of Automation, Tsinghua University. He was a Visiting Scholar at Carnegie Mellon University, Pittsburgh, PA, and Harvard University, Cambridge, MA, in 2000 and 2002, respectively. He was a Visiting Professor at Cornell University, Ithaca, NY, in 2006. His research interests include discrete event dynamic systems (DEDS) theory and applications, optimization of complex systems, and wireless sensor networks. Dr. Zhao is an associate editor for the Journal of Optimization Theory and Applications. 相似文献
143.
This paper investigates the use of artificial intelligent models as virtual sensors to predict relevant emissions such as
carbon dioxide, carbon monoxide, unburnt hydrocarbons and oxides of nitrogen for a hydrogen powered car. The virtual sensors
are developed by means of application of various Artificial Intelligent (AI) models namely; AI software built at the University
of Tasmania, back-propagation neural networks with Levenberg–Marquardt algorithm, and adaptive neuro-fuzzy inference systems.
These predictions are based on the study of qualitative and quantitative effects of engine process parameters such as mass
airflow, engine speed, air-to-fuel ratio, exhaust gas temperature and engine power on the harmful exhaust gas emissions. All
AI models show good predictive capability in estimating the emissions. However, excellent accuracy is achieved when using
back-propagation neural networks with Levenberg–Marquardt algorithm in estimating emissions for various hydrogen engine operating
conditions with the predicted values less than 6% of percentage average root mean square error. 相似文献
144.
In an open railway access market, the Infrastructure Provider (IP), upon the receipts of service bids from the Train Service Providers (TSPs), assigns track access rights according to its own business objectives and the merits of the bids; and produces the train service timetable through negotiations. In practice, IP chooses to negotiate with the TSPs one by one in such a sequence that IP optimizes its objectives. The TSP bids are usually very complicated, containing a large number of parameters in different natures. It is a difficult task even for an expert to give a priority sequence for negotiations from the contents of the bids. This study proposes the application of fuzzy ranking method to compare and prioritize the TSP bids in order to produce a negotiation sequence. The results of this study allow investigations on the behaviors of the stakeholders in bid preparation and negotiation, as well as evaluation of service quality in the open railway market. 相似文献
145.
Xiao-Dong Li Mang-Mang Lv John K. L. Ho 《International journal of systems science》2016,47(10):2279-2289
In this article, two adaptive iterative learning control (ILC) algorithms are presented for nonlinear continuous systems with non-parametric uncertainties. Unlike general ILC techniques, the proposed adaptive ILC algorithms allow that both the initial error at each iteration and the reference trajectory are iteration-varying in the ILC process, and can achieve non-repetitive trajectory tracking beyond a small initial time interval. Compared to the neural network or fuzzy system-based adaptive ILC schemes and the classical ILC methods, in which the number of iterative variables is generally larger than or equal to the number of control inputs, the first adaptive ILC algorithm proposed in this paper uses just two iterative variables, while the second even uses a single iterative variable provided that some bound information on system dynamics is known. As a result, the memory space in real-time ILC implementations is greatly reduced. 相似文献
146.
Xiaojun Ban 《International journal of systems science》2016,47(15):3646-3655
In this paper, the control problem for a class of linear parameter varying (LPV) plant subject to actuator saturation is investigated. For the saturated LPV plant depending on the scheduling parameters in linear fractional transformation (LFT) fashion, a gain-scheduled output feedback controller in the LFT form is designed to guarantee the stability of the closed-loop LPV system and provide optimised disturbance/error attenuation performance. By using the congruent transformation, the synthesis condition is formulated as a convex optimisation problem in terms of a finite number of LMIs for which efficient optimisation techniques are available. The nonlinear inverted pendulum problem is employed to demonstrate the effectiveness of the proposed approach. Moreover, the comparison between our LPV saturated approach with an existing linear saturated method reveals the advantage of the LPV controller when handling nonlinear plants. 相似文献
147.
Ian Scott Evans Jessica Miki Jessee Ho Derek T. Robinson 《International journal of remote sensing》2016,37(6):1411-1430
Topographic and elevation data are essential in the development of supporting infrastructure around mining sites. The de facto standard for acquiring elevation data is through light detection and ranging (lidar). The high labour and monetary cost of acquiring lidar has fostered more cost-effective approaches for creating elevation models that use stereo photogrammetry. To assess the accuracy of stereo-photogrammetry-derived elevation models and their potential application, we benchmark satellite (Worldview-2) and aircraft (South Central Ontario Orthoimagery Project; SCOOP) stereo-derived digital surface models (DSMs) against a lidar-derived DSM. Our results show that both stereo-derived DSMs have strong monotonic correlations with lidar across a range of land-cover types and slopes. The overall vertical accuracy of Worldview-2 and SCOOP DSMs are similar and do not meet the United States National Digital Elevation Program (NDEP) standards. However, accuracy assessment across land-cover types and slope categories show that specific land cover types (i.e. grass, row crops/pasture, sparse vegetation and marsh) on gently sloping terrain compare well to lidar data and meet NDEP accuracy standards. We situate the presented research in the context of northern resource development and discuss opportunities to improve the vertical accuracy of stereo-derived DSMs, for example, through unmanned aerial systems. 相似文献
148.
In this paper, we propose a method to jointly transfer the color and detail of multiple source images to a target video or image. Our method is based on a probabilistic segmentation scheme using Gaussian mixture model (GMM) to divide each source image as well as the target video frames or image into soft regions and determine the relevant source regions for each target region. For detail transfer, we first decompose each image as well as the target video frames or image into base and detail components. Then histogram matching is performed for detail components to transfer the detail of matching regions from source images to the target. We propose a unified framework to perform both color and detail transforms in an integrated manner. We also propose a method to maintain consistency for video targets, by enforcing consistent region segmentations for consecutive video frames using GMM-based parameter propagation and adaptive scene change detection. Experimental results demonstrate that our method automatically produces consistent color and detail transferred videos and images from a set of source images. 相似文献
149.
150.