Pub Date : 2010-06-28DOI: 10.1109/ICCIS.2010.5518579
Biao Wang, Xiangxu Dong, Ben M. Chen
The objective of the paper is to design the control system of following a predefined 3D path while maintaining a specified flight speed and considering the timing constraint. This can be accomplished by a cascaded solution framework based on theoretical dynamic error modeling. The controller for each loop can thus be designed separately so that the design problem is simplified and the control system can be implemented easily in pratice. A promising performance has be demonstrated by an accurate nonlinear simulation at current stage.
{"title":"Cascaded control of 3D path following for an unmanned helicopter","authors":"Biao Wang, Xiangxu Dong, Ben M. Chen","doi":"10.1109/ICCIS.2010.5518579","DOIUrl":"https://doi.org/10.1109/ICCIS.2010.5518579","url":null,"abstract":"The objective of the paper is to design the control system of following a predefined 3D path while maintaining a specified flight speed and considering the timing constraint. This can be accomplished by a cascaded solution framework based on theoretical dynamic error modeling. The controller for each loop can thus be designed separately so that the design problem is simplified and the control system can be implemented easily in pratice. A promising performance has be demonstrated by an accurate nonlinear simulation at current stage.","PeriodicalId":445473,"journal":{"name":"2010 IEEE Conference on Cybernetics and Intelligent Systems","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115101053","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}
Pub Date : 2010-06-28DOI: 10.1109/ICCIS.2010.5518551
Wen-chih Yang, Wei-Tzer Huang
This work proposes a load transfer scheme for radial distribution feeders with distributed generation units. A distribution feeder may be operated with distributed generation units in parallel. Conventional load transfer schemes do not consider this kind of operating condition. Hence, they are not suitable for power distribution systems including distributed generation units. In this paper, the load transfer scheme considering distributed generation is presented first. Then the difference between the proposed scheme and conventional one is explored. Second, the effects of distributed generation units on the operating states of supported distribution feeders after load transfer are analyzed via computer simulation. Final, a test case is carried out to examine the function of the proposed load transfer scheme.
{"title":"A load transfer scheme of radial distribution feeders considering distributed generation","authors":"Wen-chih Yang, Wei-Tzer Huang","doi":"10.1109/ICCIS.2010.5518551","DOIUrl":"https://doi.org/10.1109/ICCIS.2010.5518551","url":null,"abstract":"This work proposes a load transfer scheme for radial distribution feeders with distributed generation units. A distribution feeder may be operated with distributed generation units in parallel. Conventional load transfer schemes do not consider this kind of operating condition. Hence, they are not suitable for power distribution systems including distributed generation units. In this paper, the load transfer scheme considering distributed generation is presented first. Then the difference between the proposed scheme and conventional one is explored. Second, the effects of distributed generation units on the operating states of supported distribution feeders after load transfer are analyzed via computer simulation. Final, a test case is carried out to examine the function of the proposed load transfer scheme.","PeriodicalId":445473,"journal":{"name":"2010 IEEE Conference on Cybernetics and Intelligent Systems","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115246888","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}
Pub Date : 2010-06-28DOI: 10.1109/ICCIS.2010.5518540
B. Faria, Luis Paulo Reis, N. Lau, Gladys Castillo
Machine Learning (ML) and Knowledge Discovery (KD) are research areas with several different applications but that share a common objective of acquiring more and new information from data. This paper presents an application of several ML techniques in the identification of the opponent team and also on the classification of robotic soccer formations in the context of RoboCup international robotic soccer competition. RoboCup international project includes several distinct leagues were teams composed by different types of real or simulated robots play soccer games following a set of pre-established rules. The simulated 2D league uses simulated robots encouraging research on artificial intelligence methodologies like high-level coordination and machine learning techniques. The experimental tests performed, using four distinct datasets, enabled us to conclude that the Support Vector Machines (SVM) technique has higher accuracy than the k-Nearest Neighbor, Neural Networks and Kernel Naïve Bayes in terms of adaptation to a new kind of data. Also, the experimental results enable to conclude that using the Principal Component Analysis SVM achieves worse results than using simpler methods that have as primary assumption the distance between samples, like k-NN.
{"title":"Machine Learning algorithms applied to the classification of robotic soccer formations and opponent teams","authors":"B. Faria, Luis Paulo Reis, N. Lau, Gladys Castillo","doi":"10.1109/ICCIS.2010.5518540","DOIUrl":"https://doi.org/10.1109/ICCIS.2010.5518540","url":null,"abstract":"Machine Learning (ML) and Knowledge Discovery (KD) are research areas with several different applications but that share a common objective of acquiring more and new information from data. This paper presents an application of several ML techniques in the identification of the opponent team and also on the classification of robotic soccer formations in the context of RoboCup international robotic soccer competition. RoboCup international project includes several distinct leagues were teams composed by different types of real or simulated robots play soccer games following a set of pre-established rules. The simulated 2D league uses simulated robots encouraging research on artificial intelligence methodologies like high-level coordination and machine learning techniques. The experimental tests performed, using four distinct datasets, enabled us to conclude that the Support Vector Machines (SVM) technique has higher accuracy than the k-Nearest Neighbor, Neural Networks and Kernel Naïve Bayes in terms of adaptation to a new kind of data. Also, the experimental results enable to conclude that using the Principal Component Analysis SVM achieves worse results than using simpler methods that have as primary assumption the distance between samples, like k-NN.","PeriodicalId":445473,"journal":{"name":"2010 IEEE Conference on Cybernetics and Intelligent Systems","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123919649","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}
Pub Date : 2010-06-28DOI: 10.1109/ICCIS.2010.5518578
F. Lin, Ben M. Chen, Tong-heng Lee
Determining the motion of an unmanned aerial vehicle in GPS-denied environments is a challenging work. In this paper, we present a systematic design and implementation of a vision aided motion estimation approach for an unmanned helicopter in such a condition. A hierarchical vision scheme is proposed to detect a structured landmark, and find the correspondence between the 3D reference points and the projected 2D image points. Based on the obtained correspondence, a motion estimation scheme is presented to compute the relative position and velocity of the vehicle with respect to the local reference. The robust and accurate estimates are achieved by using the Kalman filter fusing the vision information with outputs of the inertial measurement unit (IMU). The robustness and efficiency of the proposed motion estimation approach is verified by using the data collected in ground and flight tests.
{"title":"Vision aided motion estimation for unmanned helicopters in GPS denied environments","authors":"F. Lin, Ben M. Chen, Tong-heng Lee","doi":"10.1109/ICCIS.2010.5518578","DOIUrl":"https://doi.org/10.1109/ICCIS.2010.5518578","url":null,"abstract":"Determining the motion of an unmanned aerial vehicle in GPS-denied environments is a challenging work. In this paper, we present a systematic design and implementation of a vision aided motion estimation approach for an unmanned helicopter in such a condition. A hierarchical vision scheme is proposed to detect a structured landmark, and find the correspondence between the 3D reference points and the projected 2D image points. Based on the obtained correspondence, a motion estimation scheme is presented to compute the relative position and velocity of the vehicle with respect to the local reference. The robust and accurate estimates are achieved by using the Kalman filter fusing the vision information with outputs of the inertial measurement unit (IMU). The robustness and efficiency of the proposed motion estimation approach is verified by using the data collected in ground and flight tests.","PeriodicalId":445473,"journal":{"name":"2010 IEEE Conference on Cybernetics and Intelligent Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130059895","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}
Pub Date : 2010-06-28DOI: 10.1109/ICCIS.2010.5518546
A. Khodayari, R. Kazemi, A. Ghaffari, N. Manavizadeh
The control of car following is essential to its safety and its operational efficiency. For this purpose, this paper builds a linear, continuous and time-delay model of car following. And then, presents a controller based on an adaptive network fuzzy inference system (ANFIS) for the car-following collision avoidance system to adaptively control the speed of the vehicle. The relative distance and relative speed to the in front car are measured and are applied to the controller. The output acceleration or deceleration rate of the controller is based on the characteristics of the vehicles. The presented ANFIS controller can solve the problems of the oscillations for final distance between the leader vehicle (LV) and the follower vehicle (FV) and their relative speed. The designed ANFIS controller is linked to the car following model. The simulation results show that the ANFIS control design is more effective and can provide a safe, reasonable, and comfortable drive than real driver.
{"title":"Modeling and intelligent control design of car following behavior in real traffic flow","authors":"A. Khodayari, R. Kazemi, A. Ghaffari, N. Manavizadeh","doi":"10.1109/ICCIS.2010.5518546","DOIUrl":"https://doi.org/10.1109/ICCIS.2010.5518546","url":null,"abstract":"The control of car following is essential to its safety and its operational efficiency. For this purpose, this paper builds a linear, continuous and time-delay model of car following. And then, presents a controller based on an adaptive network fuzzy inference system (ANFIS) for the car-following collision avoidance system to adaptively control the speed of the vehicle. The relative distance and relative speed to the in front car are measured and are applied to the controller. The output acceleration or deceleration rate of the controller is based on the characteristics of the vehicles. The presented ANFIS controller can solve the problems of the oscillations for final distance between the leader vehicle (LV) and the follower vehicle (FV) and their relative speed. The designed ANFIS controller is linked to the car following model. The simulation results show that the ANFIS control design is more effective and can provide a safe, reasonable, and comfortable drive than real driver.","PeriodicalId":445473,"journal":{"name":"2010 IEEE Conference on Cybernetics and Intelligent Systems","volume":"31 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132975841","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}
Support vector regression (SVR) has revealed the strong potential in accurate electric load forecasting, particularly by employing effective evolutionary algorithms to determine suitable values of its three parameters. Based on previous research results, these employed evolutionary algorithms themselves also have drawbacks, such as premature convergence, slowly reaching the global optimal solution, and trapping into a local optimum in parameters determination of a SVR model. This paper presents a short-term electric load forecasting model which applies a novel algorithm, namely chaotic ant swarm optimization (CAS), to improve the forecasting performance by searching suitable parameters combination in a SVR forecasting model. The proposed CAS combines with the chaotic behavior of single ant and self-organization behavior of ant colony in the foraging process to overcome premature local optimum. The empirical results indicate that the SVR model with CAS (SVRCAS) results in better forecasting performance than the other methods, namely SVRCPSO (SVR with chaotic PSO), SVRCGA (SVR with chaotic GA), regression model, and ANN model.
支持向量回归(SVR)在准确预测电力负荷方面显示出强大的潜力，特别是通过采用有效的进化算法来确定其三个参数的合适值。从以往的研究结果来看，这些采用的进化算法本身在SVR模型的参数确定中也存在过早收敛、达到全局最优解速度慢、陷入局部最优等缺点。本文提出了一种短期电力负荷预测模型，该模型采用混沌蚁群优化算法，通过在支持向量回归预测模型中搜索合适的参数组合来提高预测性能。该算法将蚁群觅食过程中的混沌行为和蚁群的自组织行为相结合，克服了蚁群觅食过程中过早的局部最优行为。实证结果表明，结合CAS的SVR模型(SVRCAS)的预测效果优于SVRCPSO (SVR with chaotic PSO)、SVRCGA (SVR with chaotic GA)、回归模型和ANN模型。
{"title":"Electric load forecasting by SVR with chaotic ant swarm optimization","authors":"Wei‐Chiang Hong, Chien-Yuan Lai, Wei-Mou Hung, Yucheng Dong","doi":"10.1109/ICCIS.2010.5518572","DOIUrl":"https://doi.org/10.1109/ICCIS.2010.5518572","url":null,"abstract":"Support vector regression (SVR) has revealed the strong potential in accurate electric load forecasting, particularly by employing effective evolutionary algorithms to determine suitable values of its three parameters. Based on previous research results, these employed evolutionary algorithms themselves also have drawbacks, such as premature convergence, slowly reaching the global optimal solution, and trapping into a local optimum in parameters determination of a SVR model. This paper presents a short-term electric load forecasting model which applies a novel algorithm, namely chaotic ant swarm optimization (CAS), to improve the forecasting performance by searching suitable parameters combination in a SVR forecasting model. The proposed CAS combines with the chaotic behavior of single ant and self-organization behavior of ant colony in the foraging process to overcome premature local optimum. The empirical results indicate that the SVR model with CAS (SVRCAS) results in better forecasting performance than the other methods, namely SVRCPSO (SVR with chaotic PSO), SVRCGA (SVR with chaotic GA), regression model, and ANN model.","PeriodicalId":445473,"journal":{"name":"2010 IEEE Conference on Cybernetics and Intelligent Systems","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133176315","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}
Pub Date : 2010-06-28DOI: 10.1109/ICCIS.2010.5518547
C. Hametner, S. Jakubek
Local model networks (LMNs) offer a versatile structure for the identification of nonlinear static and dynamic systems. In this paper an algorithm for the construction of a tree-structured LMN with axis-oblique partitioning using particle swarm optimisation (PSO) is presented. The PSO algorithm allows the optimisation of arbitrary performance criteria but is only used for a certain subtask which helps to reduce the search space for the evolutionary algorithm very effectively. A comparison using an Expectation-Maximisation (EM) algorithm is presented. The differences and advantages of the LMN with PSO and the EM algorithm, respectively, are highlighted by means of an illustrative example. The practical applicability of the proposed LMN with particle swarm optimisation is demonstrated using real measurement data of an internal combustion engine.
{"title":"Comparison of EM algorithm and particle swarm optimisation for local model network training","authors":"C. Hametner, S. Jakubek","doi":"10.1109/ICCIS.2010.5518547","DOIUrl":"https://doi.org/10.1109/ICCIS.2010.5518547","url":null,"abstract":"Local model networks (LMNs) offer a versatile structure for the identification of nonlinear static and dynamic systems. In this paper an algorithm for the construction of a tree-structured LMN with axis-oblique partitioning using particle swarm optimisation (PSO) is presented. The PSO algorithm allows the optimisation of arbitrary performance criteria but is only used for a certain subtask which helps to reduce the search space for the evolutionary algorithm very effectively. A comparison using an Expectation-Maximisation (EM) algorithm is presented. The differences and advantages of the LMN with PSO and the EM algorithm, respectively, are highlighted by means of an illustrative example. The practical applicability of the proposed LMN with particle swarm optimisation is demonstrated using real measurement data of an internal combustion engine.","PeriodicalId":445473,"journal":{"name":"2010 IEEE Conference on Cybernetics and Intelligent Systems","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133603620","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}
Pub Date : 2010-06-28DOI: 10.1109/ICCIS.2010.5518565
Narges Peyravi, S. Jafari
In this article, individual's biometric index, radio frequency identification (RFID), and image processing are brought together in order to offer a new model of identity authentication. The suggested system has been designed in two phases: producing identity authentication card and identity confirmation. The individual's biometric image are put on a contact-less card equipped with an RFID tag and for each identity authentication, the data on the card are compared with the online biometric image. If the individual's identity is authenticated, then there will be no need for him/her to punch in the personal information since his/her information will be retrieved from the database through their electronic personal code (EPLC).
{"title":"Optimization and integration of electronic identity authentication using a biometric indicator and RFID","authors":"Narges Peyravi, S. Jafari","doi":"10.1109/ICCIS.2010.5518565","DOIUrl":"https://doi.org/10.1109/ICCIS.2010.5518565","url":null,"abstract":"In this article, individual's biometric index, radio frequency identification (RFID), and image processing are brought together in order to offer a new model of identity authentication. The suggested system has been designed in two phases: producing identity authentication card and identity confirmation. The individual's biometric image are put on a contact-less card equipped with an RFID tag and for each identity authentication, the data on the card are compared with the online biometric image. If the individual's identity is authenticated, then there will be no need for him/her to punch in the personal information since his/her information will be retrieved from the database through their electronic personal code (EPLC).","PeriodicalId":445473,"journal":{"name":"2010 IEEE Conference on Cybernetics and Intelligent Systems","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116397172","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}
Pub Date : 2010-06-28DOI: 10.1109/ICCIS.2010.5518568
P. Abreu, José Moura, Daniel Castro Silva, Luis Paulo Reis, J. Garganta
A soccer game can be seen as a confrontation between two teams of agents where each player, communicating with his teammates, try to interpret in the best way as possible the game situations, achieving its main goals. Today the most important factors in a soccer clubs life and in its coach success are the game results they achieve. They represent the success of the club and in many cases the coachs future. Because of that club coaches usually use automated tools to measure their teams performance all over a soccer competition. Based only in Cartesian coordinates and in a sequential time frame analysis, this research work presents an automatic tool capable to calculate many technical aspects in a soccer match. For the validation tool process, games of simulation 2d RoboCup international competition were used. The results achieved were quite satisfactory. In what concerns to the set of statistics collected more than 92% of the total events were detected and only for the shot event this number dropped to between 74% and 85%. The future work will be concerned in incorporating this project with a real time tracking system and increasing the number of technical aspects calculated by the system.
{"title":"Football scientia- an automated tool for professional soccer coaches","authors":"P. Abreu, José Moura, Daniel Castro Silva, Luis Paulo Reis, J. Garganta","doi":"10.1109/ICCIS.2010.5518568","DOIUrl":"https://doi.org/10.1109/ICCIS.2010.5518568","url":null,"abstract":"A soccer game can be seen as a confrontation between two teams of agents where each player, communicating with his teammates, try to interpret in the best way as possible the game situations, achieving its main goals. Today the most important factors in a soccer clubs life and in its coach success are the game results they achieve. They represent the success of the club and in many cases the coachs future. Because of that club coaches usually use automated tools to measure their teams performance all over a soccer competition. Based only in Cartesian coordinates and in a sequential time frame analysis, this research work presents an automatic tool capable to calculate many technical aspects in a soccer match. For the validation tool process, games of simulation 2d RoboCup international competition were used. The results achieved were quite satisfactory. In what concerns to the set of statistics collected more than 92% of the total events were detected and only for the shot event this number dropped to between 74% and 85%. The future work will be concerned in incorporating this project with a real time tracking system and increasing the number of technical aspects calculated by the system.","PeriodicalId":445473,"journal":{"name":"2010 IEEE Conference on Cybernetics and Intelligent Systems","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124451616","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}
Pub Date : 2010-06-28DOI: 10.1109/ICCIS.2010.5518573
H. Anh
In this paper, a novel inverse fuzzy NARX model is used for modeling and identifying the IPMC-based actuator's inverse dynamic model. The highly nonlinear features of the IPMC-based actuator are thoroughly modeled based on the inverse fuzzy NARX model-based identification process using experimental input-output training data. This paper proposes the novel use of a modified particle swarm optimization (MPSO) to generate the inverse fuzzy NARX (IFN) model for a highly nonlinear IPMC actuator system. The results show that the novel inverse fuzzy NARX model optimized by MPSO yields outstanding performance and perfect accuracy.
{"title":"Particle swarm optimization identification of IPMC actuator using fuzzy NARX model","authors":"H. Anh","doi":"10.1109/ICCIS.2010.5518573","DOIUrl":"https://doi.org/10.1109/ICCIS.2010.5518573","url":null,"abstract":"In this paper, a novel inverse fuzzy NARX model is used for modeling and identifying the IPMC-based actuator's inverse dynamic model. The highly nonlinear features of the IPMC-based actuator are thoroughly modeled based on the inverse fuzzy NARX model-based identification process using experimental input-output training data. This paper proposes the novel use of a modified particle swarm optimization (MPSO) to generate the inverse fuzzy NARX (IFN) model for a highly nonlinear IPMC actuator system. The results show that the novel inverse fuzzy NARX model optimized by MPSO yields outstanding performance and perfect accuracy.","PeriodicalId":445473,"journal":{"name":"2010 IEEE Conference on Cybernetics and Intelligent Systems","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126035745","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}
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