{"title":"A Game-inspired Modeling Framework for Multiple Intelligent Agents Control Systems - A Water Resources Regulation Problem Application","authors":"Eliezer Arantes da Costa, C. Bottura","doi":"10.1109/ISIC.2007.4450937","DOIUrl":"https://doi.org/10.1109/ISIC.2007.4450937","url":null,"abstract":"Some interesting papers apply concepts and modeling approaches for multiple interacting intelligent autonomous agents control systems analysis and design inspired in game theory, where 'players' are treated as 'agents', in several conflicts of interests situations. This paper presents and uses the named strategic games matrix (SGM) as a general framework for these new types of control problems. A methodology for analysis of hierarchical multilevel architectures models based on the SGM concept is applied to a water resources regulation control problem, with multiple interacting autonomous stakeholders, as posed by Hamalaien et al as \"The Paijanne lake regulation policy\" case.","PeriodicalId":184867,"journal":{"name":"2007 IEEE 22nd International Symposium on Intelligent Control","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131042452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Random Scaling of Quasi-Newton BFGS Method to Improve the O(N2)-operation Approximation of Covariance-matrix Inverse in Gaussian Process","authors":"Yunong Zhang, W. Leithead, D. Leith","doi":"10.1109/ISIC.2007.4450928","DOIUrl":"https://doi.org/10.1109/ISIC.2007.4450928","url":null,"abstract":"Gaussian process (GP) is a Bayesian nonparametric regression model, showing good performance in various applications. Similar to other computational models, Gaussian process frequently encounters the matrix-inverse problem during its model-tuning procedure. The matrix inversion is generally of O(N3) operations where N is the matrix dimension. We proposed using the O(N2)-operation quasi-Newton BFGS method to approximate/replace the exact inverse of covariance matrix in the GP context. As inspired during a paper revision, in this paper we show that by using the random-scaling technique, the accuracy and effectiveness of such a BFGS matrix-inverse approximation could be further improved. These random-scaling BFGS techniques could be widely generalized to other machine-learning systems which rely on explicit matrix-inverse.","PeriodicalId":184867,"journal":{"name":"2007 IEEE 22nd International Symposium on Intelligent Control","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130031061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Humanoid 3D Gait Generation Based on Inverted Pendulum Model","authors":"Zhe Tang, M. Er","doi":"10.1109/ISIC.2007.4450908","DOIUrl":"https://doi.org/10.1109/ISIC.2007.4450908","url":null,"abstract":"A planning method for humanoid walking is proposed in this paper. In this method, IPM (inverted pendulum model) is used as a dynamic model for humanoid robots. Whereby ZMP (zero moment point) constraints of the robot are analyzed in the IPM motion, and the COG (center of gravity) motion of IPM is to approximate the COG motion of robots. The kinematic model of the robot for walking planning is based on a typical model with 12 DOFs (degree of freedom) of legs. After the robot COG motion and two legs motion are generated, and 3D kinematic constraints are satisfied, the angles of every DOFs are obtained. These angular trajectories are used to control the real robots. Simulation experiments are conducted to verify the effectiveness of our proposed walking planning method.","PeriodicalId":184867,"journal":{"name":"2007 IEEE 22nd International Symposium on Intelligent Control","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125505820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Exponentially Stable Sliding Mode Based Approach for a Class of Uncertain Multi-Time-Delay Systems","authors":"Tung-Sheng Chiang, Pingfang Wu","doi":"10.1109/ISIC.2007.4450931","DOIUrl":"https://doi.org/10.1109/ISIC.2007.4450931","url":null,"abstract":"This paper presents an adaptive fuzzy sliding mode control for a class of uncertain nonlinear systems with multiple time delays. The proposed control scheme guarantees to achieve an exponentially stable sliding surface even if mismatched uncertainty and unknown delays are considered. Compared to traditional schemes, the stability analysis is transformed into an LMI problem independent of each delay but a known upper bound of delay. Note that the uncertain dynamics is not canonical form. However, the novel sliding surface design can be derived based on the Lyapunov-Krasovskii method. Then, an SMC-based adaptive fuzzy control scheme is proposed to achieve asymptotic stability. Combined with the adaptive fuzzy algorithm, the chattering phenomenon will be reduced effectively. Moreover, the fuzzy membership functions are tuned on-line. The advantages of the proposed controller are to drive the states to converge to zero asymptotically and to alleviate the chattering phenomenon when the states are around zero.","PeriodicalId":184867,"journal":{"name":"2007 IEEE 22nd International Symposium on Intelligent Control","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122903256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Liu Hai-ming, Huang Yue-ming, Yuan Peng, G. Hong-xia, Zhang Mei
{"title":"A Heuristic Optimization Algorithm for Multi-head Mounter","authors":"Liu Hai-ming, Huang Yue-ming, Yuan Peng, G. Hong-xia, Zhang Mei","doi":"10.1109/ISIC.2007.4450915","DOIUrl":"https://doi.org/10.1109/ISIC.2007.4450915","url":null,"abstract":"This paper analyzes optimization algorithms of assembly time for a multi-head mounter. A step-by-step heuristic optimization algorithm is proposed to minimize the PCB assembly time for a multi-head mounter. By relaxing the restrictions on the problem and employing a flexible approach for feeder and head assignment, the algorithm reduces the assembly time by minimizing cycles of pick and placement, constructing the simultaneous pickup and implementing the nearest placement. The production results show that the proposed algorithm has good performance in practice.","PeriodicalId":184867,"journal":{"name":"2007 IEEE 22nd International Symposium on Intelligent Control","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124175224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Incremental Learning Bayesian Networks for Financial Data Modeling","authors":"Da Shi, Shaohua Tan","doi":"10.1109/ISIC.2007.4450858","DOIUrl":"https://doi.org/10.1109/ISIC.2007.4450858","url":null,"abstract":"Discovering underlying relationships among financial variables will strongly support various financial researches. In this paper, A novel incremental learning algorithm for Bayesian networks is proposed to build up the relationships among financial variables automatically. Our algorithm can partially update the learned structure according to the new generated financial data, which provide a realtime guarantee on our algorithm. Experiment results show that our algorithm outperforms all the available incremental learning algorithms, even some widely used batch learning algorithms for Bayesian networks both on classic data sets and real financial data sets.","PeriodicalId":184867,"journal":{"name":"2007 IEEE 22nd International Symposium on Intelligent Control","volume":"348 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125624004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Model-free Redundancy Resolution Technique for Visual Motor Coordination of a 6 DOF robot manipulator","authors":"S. Kumar, Amit Shukla, A. Dutta, L. Behera","doi":"10.1109/ISIC.2007.4450944","DOIUrl":"https://doi.org/10.1109/ISIC.2007.4450944","url":null,"abstract":"In this paper, visual motor coordination of a 6 DOF robot manipulator is considered. It is difficult to analytically derive inverse kinematic relationships for such manipulators. The problem becomes more challenging owing to the presence of multiple solutions for the inverse-kinematic relationship between robot end-effector position and joint angle vector. Many of the current redundancy resolution techniques necessitate explicit orientation information which cannot be obtained from visual feedback. Hence such techniques cannot be used for visual motor coordination of redundant manipulators. In this paper, it is demonstrated that a feasible inverse kinematic solution may be obtained by using input-output space clustering along with the KSOM algorithm. The method is innovative in the sense that it does not require any orientation information for resolving redundancy and it is model-independent. The efficacy of the proposed method is illustrated through simulations on a 6 DOF PUMA 560 manipulator model.","PeriodicalId":184867,"journal":{"name":"2007 IEEE 22nd International Symposium on Intelligent Control","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129243005","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Multilayer Generalized Mean Neuron model for Blind Source Separation","authors":"Meenakshi Singh, Deepak Singh, P. Kalra","doi":"10.1109/ISIC.2007.4450947","DOIUrl":"https://doi.org/10.1109/ISIC.2007.4450947","url":null,"abstract":"The fundamental issue in blind source separation (BSS) is to find a set of independent signals from the output of the mixing system, without the aid of information about the nature of the mixing system, for which most of the BSS algorithms use the concept of Independent component analysis. This paper proposes a new neuron model for independent component analysis (ICA) which can be used for separation of non-linear and noisy mixtures of signals. The technique proposed here utilizes generalized mean neuron (GMN) model, consisting of an aggregation function which is based on the generalized mean of all the inputs applied to signal mixtures. The proposed technique results in faster convergence, and is highly efficient for underdetermined system, with low CPU time.","PeriodicalId":184867,"journal":{"name":"2007 IEEE 22nd International Symposium on Intelligent Control","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123543800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Bidirectional Flow Shop Scheduling with Multi-Machine Capacity and Critical Operation Sequencing","authors":"Z. Zhao, T. Leong, S. Ge, H. Lau","doi":"10.1109/ISIC.2007.4450927","DOIUrl":"https://doi.org/10.1109/ISIC.2007.4450927","url":null,"abstract":"We study a special bidirectional flow shop problem with multi-machine capacity and sequencing constraints on critical operations. A formulation is proposed in continuous time domain and compared with a mixed integer programming (MIP) formulation in discrete time domain. Of particular interest to us is the formulation of the machine utilization function -both in continuous time and in discrete time domain. Fast heuristics are proposed with the relaxation of the machine capacity. The performance of the heuristic and Lagrangian relaxation are compared with optimal solutions experimentally.","PeriodicalId":184867,"journal":{"name":"2007 IEEE 22nd International Symposium on Intelligent Control","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116293819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Hybrid Mobile Wireless Sensor Network Cooperative Localization","authors":"Chee Keong Seovv, Winston K.G. Seah, Zheng Liu","doi":"10.1109/ISIC.2007.4450856","DOIUrl":"https://doi.org/10.1109/ISIC.2007.4450856","url":null,"abstract":"Although there has been much effort to improve localization in both wireless sensor networks and robotics, few have combined the localization techniques of both worlds so that they can cooperatively and mutually benefit each other. Therefore, we seek to design a localization algorithm based on statistical framework that can combine the localization methodology of both autonomous robotics and sensor networks, such that a two-way cooperative localization can be accomplished instead of the usual one-way only cooperation. To achieve this, we need to integrate three important research areas: wireless sensor networks, robotics and statistical filtering. In this paper, we will present the key elements of our approach and simulation results to validate the scheme. We prove that mobile robots and static sensor nodes can cooperatively help each other in their localization by first localizing the mobile robots with the static nodes, after which the mobile robots will provide feedback to the static nodes so that the static nodes can then refine their own location estimates.","PeriodicalId":184867,"journal":{"name":"2007 IEEE 22nd International Symposium on Intelligent Control","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121870035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}